{
 "cells": [
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   "cell_type": "code",
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   "metadata": {
    "tags": [
     "hide_input"
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```{note}\n",
    "This chapter by [Todd M. Gureckis](https://gureckislab.org/~gureckis) and is released under the [license for this book](../../LICENSE). Small introductory parts are adapted from Danielle Navarro's excellent [Learning Statistics with R](https://learningstatisticswithr.com) book.  In addition the general structure borrows elements of several classic text about data visualization including Keiran Healy's [Data Visualization](https://socviz.co). Much of the Matplotlib materials comes from the [library documentation](https://matplotlib.org/tutorials/index.html) and most of the seaborn example code is drawn from the outstanding [official seaborn tutorial](https://seaborn.pydata.org/tutorial.html) by [Michael Waskom](https://www.cns.nyu.edu/~mwaskom/index.html).\n",
    "```\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The art of seeing things in data\n",
    "\n",
    "In the previous chapter we discussed the organization and manipulation of data by a computer.  However, data is lifeless and inert without our ability to detect and describe patterns in it. One part of that involves quantitative data analysis such as statistical inference, [estimation](../../chapters/08/02-estimation), or [hypothesis testing](../../chapters/09/00-hypothesistesting), topics we will review later.  However, an equally important part of analysis can be to **perceive patterns in data** and **communicate** them to others.  In order for these later two tasks to be successful, we often have to find ways to represent the data that align with our perceptual and cognitive abilities for seeing patterns.\n",
    "\n",
    "The present chapter is therefore concerned with the visualization of data for the purpose of understanding and communication.  Visualizing data means taking features of a dataset and assigning them to graphic elements of a picture.  Using our processes of visual pattern recognition we can then detect patterns that are in the data by detecting them in an image.  The process of creating visualizations of data is itself an art but also draws a lot from ideas in the visual arts about contrast, color, spacing, typography, context, and design.\n",
    "\n",
    "\n",
    "### What is a visualization?\n",
    "\n",
    "One of the most famous data visualizations of all time is John Snow’s 1854 map of cholera deaths, a digital reproduction is shown in {numref}`fig:snowmap`:\n",
    "\n",
    "```{figure} ./images/snowmap1-1.png\n",
    ":width: 650px\n",
    ":name: fig:snowmap\n",
    "\n",
    "Reproduction of Snow's Cholera Map of London.  Orange dots show cases and the spatial layout show a clustering in a particular area of the city.\n",
    "```\n",
    "\n",
    "The visualization is elegant in its simplicity. In the background we have a street map, which helps orient the viewer and provides a **frame of reference**.  Over the top, we see a large number of small dots, each one representing the location of a cholera case.   The approximate location of the cholera case has been translated into a spatial position in the map although almost certainly began as the street address of the infected individual.  This represent the mapping between features of the data (address) to a visual feature (spatial position of an orange symbol).  The larger symbols show the location of water pumps, labeled by name. Even the most casual inspection of the graph makes it very clear that the outbreak is clustered around the Broad Street pump. Upon viewing this graph, Dr Snow arranged to have the handle removed from the pump, ending the outbreak that had killed over 500 people. Such is the power of a good data visualization.\n",
    "\n",
    "The visual nature of the representation of the data is critical.  Imagine instead the data were simple a spreadsheet listing the name, gender, age and address of the people who were infected.  Unless you had a perfect knowledge of the streets in this area, it is unlikely just scanning the tabular data would allow the same insight afforded by the visual representation in {numref}`fig:snowmap`.\n",
    "\n",
    "However, there are elements of the visual and stylistic choices which help as well. Here the lines of the streets are a lighter shade of gray helping them fade into the background (the layout of the street map is not as important actually), meanwhile the cholera cases are a very strong orange helping them \"jump\" off the page (or \"popout\").  Likewise the pumps are a distinct color and shape helping to prevent confusion between them and cholera cases.  These are the types of choices we will discuss below that make some visualizations better and more useful than others."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Why create visualizations?\n",
    "\n",
    "Why do we \"visualize\" data (implying seeing it with our eyes) instead of listen to data, touch it, or taste it?  Well as it turns out there is an entire approach to data \"sonification\" which actually does map features of a dataset to sounds which can be both beautiful as well as informative/insightful [^datasounds].  However, it turns out our visual reasoning capacities are very strong and thus are able to detect many types of patterns easily in a picture compared to a sound [^sound].\n",
    "\n",
    "[^sound]: Many of the features one might use to map data to in a sound or music we have relatively poor absolute judgment about.  For instance people have trouble detecting the pitch of sounds, separating multiple overlaid sound sources, etc...  This often makes sound less ideal.  The same goes for other senses like touch and taste.  If our brains worked differently and didn't devote so much of our cortex to vision it might well be we'd explore data with sound more regularly.\n",
    "\n",
    "[^datasounds]: Data Sonification.  Brian Romans, Wired: [https://www.wired.com/2007/04/data-sonification/](https://www.wired.com/2007/04/data-sonification/)\n",
    "\n",
    "Another answer to the question of \"why create visualizations?\" has to do with the power of visualization to clearly point out things we were not expecting via a more traditional statistical analysis.  For example, Anscomb's Quartet ({cite}`Anscombe1973`) is often used in teaching to illustrate the power of visualization and is recreated in a few lines using Python here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x126056828>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 576x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.set(style=\"ticks\")\n",
    "\n",
    "# Load the example dataset for Anscombe's quartet\n",
    "df = sns.load_dataset(\"anscombe\")\n",
    "\n",
    "# Show the results of a linear regression within each dataset\n",
    "sns.lmplot(x=\"x\", y=\"y\", col=\"dataset\", hue=\"dataset\", data=df,\n",
    "           col_wrap=2, ci=None, palette=\"muted\", height=4,\n",
    "           scatter_kws={\"s\": 50, \"alpha\": 1})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The quartet consists of four panels each depicting a single dataset plotted as a scatterplot with a regression line.  What is interesting about these four data sets is that they share several numerical quantities with one another.  For example, the mean of the values along either the X or Y dimension is nearly identical.  Likewise the correlation between variable x and y is basically the same in each figure.  A regression line fit to each panel will result in identical coefficients.  However, clearly by looking at each panel and comparing it to the other we can see that these dataset are quite different from one another.  Some (like data set 1 plotted in blue) do seem to depict a linear relationship (i.e., a connection between the x and y values that roughly follows a line).  However data set 2 (plotted in orange) seem clearly to show a non-linear relationship such as a parabola.  Dataset 4 (red) show data that are heavily influenced by single \"outlier\" points.\n",
    "\n",
    "The key insight here is that if we calculated various descriptive statistics on these datasets we might conclude they are nearly identical.  It is only by visualizing the data in this specific way that we can see patterns we might not have expected to see.  In this way visualization can enable **discovery** of new features of a dataset and lead to new scientific hypotheses."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Why create visualizations?\n",
    "\n",
    "Hopefully you are now sold on the exciting concept of data visualization. How do we make a data visualization?  This chapter will step through this both conceptually and technically (using Python/Pandas).  However, first it is useful to distinguish between the two main purposes of data visualization: exploratory data analysis and communication.\n",
    "\n",
    "- **Exploratory Data Analysis** refers to an approach to analyzing a data set to summarize the main patterns or findings.  Exploratory data analysis often begins without many clear hypotheses about the data, but instead takes the form of a kind of dialog where the experimenter or data analysts \"asks a question\" of a data set by designing a particular visualization or analysis and then tries to assess perceptually the answer to that question by visually processing the resulting outputs/graphics.  Exploratory data analysis is deeply related to the cognitive process of \"sensemaking\" and is a key skill I hope you take from this course.\n",
    "- **Communication** refers to using figures to communicate the known and understood results of a dataset or experiment to the public.  This might be in the context of a publication (meaning a figure printed into the page of the paper) or a presentation (meaning a figure displayed on poster or oral presentation with slides).  Several of the design elements of a visualization used for communication differ somewhat from those for exploratory data analysis.\n",
    "\n",
    "### What is \"sensemaking\"\n",
    "\n",
    "As mentioned exploring data is an act of \"sensemaking.\"  Sensemaking refers to the process of generating meaningful explanations or understandings for possibly incomplete or noisy data patterns in the environment {cite}`Klein:2006a`, {cite}`Klein:2006b`. In contrast to simple  pattern recognition or categorization, sensemaking is a highly-volitional process that  involves the continual evaluation of new evidence or data, and repeated information  gathering.  When we explore a data set by probing it with several different types of visualizations and analyses we are performing a type of \"sensemaking\" hoping to develop an easy-to-communicate summary of what the data show.\n",
    "\n",
    "Often times it helps to begin this process without too much of a specific hypothesis in mind[^hypothesis].  One brilliant behavioral experiment performed on students of statistics makes this point.  {cite}`Yanai:2020` had students analyze a dataset of the body mass index of a large collection of individuals.  The data were provided in two files (one for men, one for women).  In one condition of this experiment, students were told to evaluate several specific hypotheses (e.g., to assess if there is a negative correlation between exercise and BMI for women, etc...).  In addition students were asked if there was any other things they could conclude from the data.  The second group was just asked to analyze the dataset to see \"what they could conclude\".\n",
    "\n",
    "```{figure} ./images/gorillaexp.png\n",
    ":width: 550px\n",
    ":name: fig:gorilla\n",
    "\n",
    "Figure from {cite}`Yanai:2020` which shows the \"Gorilla\" dataset hiding in the scatterplot between two variables across two files, as well as the results counting the number of participants in each condition that \"discovered\" the hidden pattern.\n",
    "```\n",
    "\n",
    "A key feature of the experiment was that if students plotted the number of steps versus the body mass index of both the men and women at the same time they would see that it clearly formed the shape of a gorilla!  Panel C of {numfig}`fig:gorilla` show how often the gorilla was or was not discovered by the students.  Interesting many more of the students found the gorilla when they were not given a specific hypothesis compared to when the were told to evaluate a specific hypothesis.\n",
    "\n",
    "The goal of exploratory data analysis is to enable the type of discovery that would let you find this strange pattern in your data.  The problem is that you never exactly know where the interesting patterns might lie (e.g., here it was in the relationship between steps and BMI however it could have been between $log(steps)$ and BMI or some other more complex relationship).  As a result, when performing exploratory analyses we want to be on the lookout for several different patterns by exploring the data several different ways.  This means we might have a Jupyter notebook containing several plots for a single data set rather than there being one \"right\" plot for a given dataset.  In fact, there is rarely one \"right\" plot to make but instead several different ways to posing questions to a data set (i.e., \"what is the relationship between steps and BMI?\") give the best chance of making discoveries.\n",
    "\n",
    "\n",
    "[^hypothesis]: Not all analyses should be hypothesis-free.  In fact, much of the later content of the course discusses cases where having a hypothesis is important.  Also hypotheses are often important in the design of an experiment as we have already discussed.  So don't say I told you to not develop hypotheses!  What I mean here is that when analyzing data it is useful to be too constrained at first by perceptions. \n",
    "\n",
    "\n",
    "### Style and substance\n",
    "\n",
    "At various points in this chapter we will discuss the visual style of a plot or graphic.  This includes the colors, fonts, spacing, and other visual attributes which you can usually customize endlessly when making a plot.  The world if full of very bad visualizations which are distracting confusing or downright misleading.  The principles of visual design that go into making plots is itself a very interesting topic but beyond the full scope of this chapter.  However, several excellent resources exists for learning more about this including the classic \"The visual display of information\" by Tufte {cite}`Tufte:2001` and \"Data Visualization: A practical introduction\" by Healy {cite}`Healy:2019` (focused on using R to create plots) [^healylink].\n",
    "\n",
    "[^healylink]: The entire text for this book is available [online](https://socviz.co/index.html#preface).\n",
    "\n",
    "It is still worthwhile to run through some of the classic examples just to highlight the differences between a better and worse plots.\n",
    "\n",
    "Some plots are somewhat famous for being \"bad visualizations\":\n",
    "\n",
    "\n",
    "```{figure} ./images/fastfood.jpeg\n",
    ":width: 650px\n",
    ":name: fig:fastfood\n",
    "\n",
    "A confusing plot showing the relative sales volume of different fast food chains and also the GDP of Afghanistan\n",
    "```\n",
    "\n",
    "{numref}`fig:fastfood` uses the logos themselves as a type of bar chart when a simple text label or legend would do.  As a result the **width** of the bars is another dimension varying across the examples which is distracting and makes visual comparison difficult.  The McDonald's logo appears so much lager even though it is hard to see it as twice as large as the GDP of Afghanistan.  Also the types of data mixed here seem confusing and ill conceived.\n",
    "\n",
    "While {numref}`fig:fastfood` is simply comical, {numref}`fig:gundeaths` is disturbing:\n",
    "\n",
    "```{figure} ./images/gundeaths.jpg\n",
    ":width: 450px\n",
    ":name: fig:gundeaths\n",
    "\n",
    "A line plot from a newspaper trying to summarize the effect of a policy on gun deaths.\n",
    "```\n",
    "\n",
    "The black line plots the number of gun deaths and usually people assume bigger numbers would appear \"taller\" from the x-axis (bottom on plot).  However, in this case the mapping between the data and spatial position is with reference to the **top** of the figure meaning that when the line is closer to the bottom of the plot it means **more** deaths.  If someone interprets this graph in a more conventional way it appears that following the passage of the 2005 gun law in Florida allowing people to \"stand their ground\" gun deaths dropped (favoring the policy position of those opposed to gun control).  However, in fact the plots shows gun deaths as increasing somewhat dramatically following the passage of the law reversing a trends towards public safety that had been developing over the prior decade.  This is sometimes seen as an \"evil\" use of data visualization and one that you should be on the lookout in newspapers and TV reports which often attempt to sway your opinion with poor presentations of data.  The key to not being tricked is to **always check the axes when looking at a plot**.\n",
    "\n",
    "The problem of making a nice looking informative plot is somewhat complicated by some of the default options for certain software programs.  For example, several years ago Excel would provide default line plots that were rendered in 3d (e.g., {numref}`fig:excel`.  While 3d looked \"cool\" and novel it doesn't add much over a simple line and in fact makes it harder to visually compare multiple lines plotted in the same figure:\n",
    "\n",
    "\n",
    "```{figure} ./images/excel.png\n",
    ":width: 350px\n",
    ":name: fig:excel\n",
    "\n",
    "A 3d line plot which was a easy to create default in Excel several years ago.  It can be hard to compare the lines to one another given the distracting perspective on the data.\n",
    "```\n",
    "\n",
    "Given the array of options provided by modern data visualization software it can be hard to not get pulled towards bad color schemes and plot layouts/designs, especially if you are not particularly artistically inclined.  Fortunately, newer software packages made more sensible choices that work for most cases.  For instance, we will focus on the [seaborn](https://seaborn.pydata.org) library in this class which is an easy to use plotting library for Python but also which make several choices about colors and plot layout/design that are already known to make visually [pleasing plots](https://seaborn.pydata.org/examples/index.html).  Of course it it still up to you to make the plot informative and not misleading, but these libraries help remove the number of choices available to you and letting you focus on data analysis and interpretation itself to a large degree."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How to make plots in Python\n",
    "\n",
    "The goals in this chapter are twofold: firstly, to discuss several fairly standard graphs that we use a lot when analysing and presenting data, and secondly, to show you how to create these graphs in Python. The graphs themselves tend to be pretty straightforward, so in that respect this chapter is pretty simple.\n",
    "\n",
    "However, the difficulty usually come when trying to customize your plot.  Here there can be a lot of options and sometimes doing something that seems simple ends up being more complex than you anticipated.  Getting to the point of mastery with these things tends to elude even the most accomplished scientist or data scientist.  Usually solving these problems involve a fair amount of google searches, looking for solutions online or borrowing code from others.  As a result you will not feel a complete sense of \"mastery\" after reading this chapter.  However, you can get far enough that you can understand how to make most common plots and also know the right terms to search for when trying to solve more complex problems."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The wild world of plotting in Python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most of this chapter will focus on the matplotlib library ( [https://matplotlib.org](https://matplotlib.org)) and related libraries.  Matplotlib is a general putpose graphics and plotting library for Python.  It aims to adopt must of the same syntax as the plotting routines used in [Matlab](https://www.mathworks.com/products/matlab.html), another popular scientific programming language.  Matplotlib is very powerful but is just one of the plotting options for Python.  Others include [plotly](https://plot.ly), [Bokeh](https://docs.bokeh.org), etc...  Indeed, {refnum}`fig:pythonmap` by Jake VanderPlas shows all the different options and how they relate to one other as of around 2020.\n",
    "\n",
    "\n",
    "```{figure} ./images/PythonVisLandscape.jpg\n",
    ":width: 550px\n",
    ":name: fig:pythonmap\n",
    "\n",
    "Jake VaderPlas' landscape of python plotting libraries (circa 2019).\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The reason this class will focus on matplotlib is the close link between matplotlib and the [pandas](https://pandas.pydata.org) data frame library, and [seaborn](https://seaborn.pydata.org) which is visible in the plot above.  I have found that seaborn can make many complex plots very easy (often as short as 1-2 lines).  For more complex plots one can drop back to \"raw\" matplotlib and customize as you like.  However, for some things other libraries can be better.  For instance Bokeh has some really nice ways of making interactive graphics and visualizations.\n",
    "\n",
    "The relationship between matplotlib and seaborn is that seaborn wraps around matplotlib and provides very nice looking graphs without requiring you to do so much work choosing colors and things.  As a result you can quickly get views on your data that are mostly publication-ready.\n",
    "\n",
    "Mostly in this class we will work with seaborn to make scientific plots.  However, knowing a little bit about matplotlib is useful even when using seaborn to be able to change certain things in your figures."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction to matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we get too deep in the weeds lets look at a few very simple graphs.  Let's begin by making a small list called `fibonacci` that contains a few numbers we'd like python to draw for us.  Then, we'll ask python/matplotlib to plot it.  Here is a simple line plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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ZfbfygZkdB+yKXyQRkW+3dece/uOeuXy1cSc3XzKJiSPSwo7UKAUdu/28mZUROxspCnwvrqlERGrYsr2Ym+7NZtO2Ym659HDGHNIr7EiNVpBZSQvMbAAwEigDVrp7abyDiYhU2rS1mBvvncu2nXv45azJjBzUI+xIjVqQs5KOARa6+2Iggs5KEpEEKigs4oa757B9Vwm/uixLpZAAQY4x/BGdlSQiIcjbvIsb7ppDUXEpv7kii2EDvnUQgzQwnZUkIklpfcFOfnHXXPaWlnP7lVM4pF+3sCM1GTorSUSSzrr8HfzHPXOJRKP89sopDDqoS9iRmhSdlSQiSeWLvO3cdG82LVs04zdXTKFfn05hR2pygp6V1B8YTeysJHf3vXFPJiJNzmfrt3Hzfdm0bd2C26+cQkavjmFHapKCnJXUmtg9E0YB44Dzzez2eAcTkaZl5bpCbrp3Lu3bteJ3Vx+hUghRkF1JTwGDiN2GczEwidhIbhGRBrHs8y388m/z6NqxLb+5Move3dqHHalJC3LweSwwHniR2L2Ys4Cu8QwlIk1HzmebuPWBeXTv3I7fXT1FpZAEghRDnruXAauAUe6+HNDfnIjU2ye+kV8+MJ/e3drzu6um0KNLu7AjCcGKYbeZnUfsXs3nmNloQJceiki9fLyigN88tICDenfkd1dNoVvntmFHkgpBiuFqYruT3iI2EuMDYvdoEBGpk3m5+dz+8AIOTuvE7VdOoUtHXTObTIKcrroauL7i4Yz4xhGRxm7Okq/5r78vYki/rtw2azId27UKO5LUUGsxmNlRwG1Ad6BZ5XJ3z4xfLBFpjN5btJ47nvyEYQO6c+ulh9O+rUohGQU5XfUu4CHgE2JXPYuIHLC3P/qSO59ezOjBPbnp4km0axPkx4+EIcjfzF53/1Pck4hIo/X6vLXc9ewSxg7txY0XTaRta5VCMgty8HlpxZlIIiIH7JU5n3PXs0s4bHgfbr54kkohBQT5GxoELDKzdUBx5cL6HGMws9OIHbfoALzh7tfU9XuJSPJ6/r3PeOjlZRw+Ko3rfziBVi2D/C4qYQtSDDc25ArNbBBwL7HRGgXAu2Z2kru/1pDrEZFwPf32Kh57bQVTxmRw3fnjadlCpZAqav2bcvf3gT3A0cDUKsvqahrwlLt/VXHv6BnAgnp8PxFJItFolCfeWMljr63g6EP78u8qhZQT5HTVHwK/BWYTK5InzOw2d3+gjuscAuw1szeANOBl4OYa6+zK/53H1LeO6xORBIlGozz22gqeeWc1x03ox4/PGUeL5s1qf6EklSC7kn4GTHT3fAAz+0/gTaCuxdAS+A6xLZBdxIbzXQg8UuU51wK31vH7i0gIotEoD728jBfeX8N3Jw/gyu9l0lylkJKCbN81rywFAHfPA8rrsc4NwNvuvsndi4EXgIk1nvNnYGCNjyPrsU4RiaNIJMr9z+fywvtrOPWIgVw1XaWQyoJsMWwxszPc/UUAMzsT2FqPdb4CPFqxu2gncBKxcviGu28DtlVdZmb1WKWIxEskEuXu2Ut4Y/46zjxqMBefNpJmzVQKqSxIMfwYeNHM/kpsJEYJcGZdV1hxq9A/AHOAVsSG8z1c1+8nIuEpj0T5y9OLeWfhes4+7hB+eNJwlUIjEGSI3jKL/bo+lNiuJ6+4P0OduftDxMZsiEiKKi+PcMeTi3l/8Vecd+Iwvj91qEqhkQhyz+cOwG+Ax4C/Ab+ouA+0iDRRZeUR/vj4It5f/BUXnDycc08wlUIjEmRX0t3ECuR6YruSLgPuBK6IYy4RSVKlZeX8/n8+ZsGyDVxy+kjOPGpI2JGkgQUphnFVx1+Y2XvE7uYmIk3M3tJyfvfoQj5eUcDl00Zz6hGDwo4kcRDkdNWtZta9yuOO1DhjSEQavz17y/j1QwtYtLKAq88ao1JoxPa5xWBmd1Z8WUpsiN5zxK5fOB1YnoBsIpIkikvK+PWDC1j6+WZ+cs44jp/YP+xIEkf725W0peLzhxUflZ6MXxwRSTZFe0q57YH5+LpCfnbeeI4+VNNpGrt9FoO7/zKRQUQk+ewqLuW2++fx2Vfb+PcfHsYRYw4KO5IkwP52Jc1x9yPMbCffcktPd+8c12QiEqodu/dyy/3ZrMvfwQ0XTuDwUelhR5IE2d+upLsrPk+gyg16RKTx276rhJvuzebrTbu48aJJHDa8T9iRJIH2Vwy/AJ4AnnD3QxOUR0RCtnXHHm68N5uCwiJuvngS46x32JEkwfZXDDvMbBVwkJnl1PzD+tzaU0SS05btxdx4z1y2bN/DbZcezughPcOOJCHYXzF8FxgHPEhskJ6INFLRaJQPFn/N/S/kUloW4bZZkxk5qEfYsSQk+zsraSfwgZmd4u6rEphJRBJo87Zi7p69hIXLCxjavys/mTGOg9N0bklTFmS6qkpBpBGKRKK8uWAdD7+yjLLyKJecPorTjhykW3FKoFlJItLI5G3exV+fXkLums1kDunJj84eS3rPDmHHkiShYhBpQsrLI7z4wec8/voKWrZszo/OHssJk/prZLZUU2sxmFlH4PfAMOBs4HfAv7n7rjhnE5EGtDZ/B3c+tZjV67cxaWQaV07PpEeXdmHHkiQUZIvhTiAf6APsAToD9wPnxTGXiDSQ0rJynn57Nc+8s4qO7Vtx/Q8O44ixGdpKkH0Kej+Gi83sZHcvMrPzgaXxDiYi9efrCrnz6U/5csNOjh7fl0tPH0WXjm3CjiVJLkgxlNd43AKIxCGLiDSQPSVl/P31lbz04Rp6dG7LLZdMYsKItLBjSYoIUgwfmNnvgXZmdiLwI+Bf8Y0lInW1ZNUm/vLMpxQUFnFS1gBmnjKC9m1bhR1LUkiQYvg5cAOwHbgdeAP4dTxDiciB21VcysMvL+PNBevI6NmB3141hdGDNdJCDlyQC9xKiRWBykAkSc1fms89s5ewbWcJ048ZwrknDqNNqxZhx5IUFeR01aOJbTFUve8z7j4xTplEJKBtO0u4/4VcPvz0awakd+amiydxSL9uYceSFBdkV9LfiJ2yuqYhV2xmfwR6ufvMhvy+Ik1BNBrlvU++4oEXcikuKecH3x3G9GMPoWWL5mFHk0YgSDEUuPudDblSMzsOmAm82pDfV6Qp2LQ1NvTu4xUF2MHd+Mk5Y+mvoXfSgIIUw8tmdhWxg86llQvd/cu6rNDMuhM7iP1bYExdvodIUxSJRHl9/loeeWUZkSjMOmMUpxyhoXfS8IIUQy9iP8R3V1kWJXYFdF3cB9wI9NvXE8ysK9C1xuK+dVyfSMr7etMu/vL0pyz7fAtjD+nF1WePIa2Hht5JfAQphrOBdHcvqO/KzOxSYL27v2NmM/fz1GuBW+u7PpFUV14e4YX31/DEGytp1aoF18wYy3ETNPRO4ivQMQZgUwOtbwaQbmafEjvLqaOZ3eHuP63xvD8Dj9RY1hf4sIFyiCS9L/K28/+eWsyar7YzeXQ6V3wvk+6d24YdS5qAIMWwEJhjZi8DJZUL3f1PB7oyd59a+XXFFsPR31IKuPs2YFvVZWZ2oKsTSUmlZeU89dYqnn13NZ3at+aGCyaQlZmurQRJmCDF0A5wYGiVZdH4xBFp2lZ8UchfnlnM+oJdHHtYPy45fRSdO7QOO5Y0MUGufL4IwMwOBlq5+2cNsWJ3f4T/u7tIpEkqLinjsddW8Mqcz+nZtR23zTqc8cP6hB1LmqggVz4PAV4EMoDmZrYZOMXdV8Y7nEhTsNg38tdnl7CxsIhTpwzkhycP19A7CVWQXUl/Bf7g7o8CmNlFwN3AsfEMJtLY7Sray4MvLePthV9yUK+O/OfVRzByUI+wY4kEKoY+laUA4O4Pm9nP4phJpNGbl5vHPbNz2L57L2cfdwjfn2q01tA7SRJBiqGlmXV390IAM+uJDj6L1MnWHXu47/lc5ubkMSijC7dcejhD+ta8llMkXEGK4S/AfDN7quLxDOCO+EUSaXyi0Sjvfryev724lJLSci44eTjTjh6ioXeSlIKclXS/ma0Gvgs0B65y97fjnkykkdhYWMRdzy7hE9/I8AHd+fE5Y+nXp1PYsUT2KcgWA8A6d/+5mU0Hssxsobtvj2cwkVQXiUT5Z/YXPPrqcgAunzaak7MG0lxD7yTJBTld9b6Kz38mtlvpDeBB4Kz4RhNJXV9t3MmdT33KirWFHGq9ufqsMfTu3j7sWCKBBNliGA9MJHYXt0fd/RdmtjC+sURSU1l5hOff+4wn33TatGrBtd8fx7GH9dM4C0kpQYqhubtHzGwqsfHbAJr3K1LDmq+2cefTn/L519uZkpnB5dNG001D7yQFBSmGz8zsn8Ag4D0zexxYEt9YIqljV9FennvvM2b/6zM6d2jNLy6cQFZmRtixROosSDFcBEwD5rh7qZl9CPxPfGOJJLftu0qYvzSf7Jx8lqzeRHkkyvET+nPJ6SPp2F5D7yS1BTlddTfw9yqP741rIpEktWV7MfNyY2Ww7PPNRKKQ3qMDZx41mCPGHqQL1aTRCHq6qkiTVFBYRHZOHtk5eaxctxWAfn06cfbxQ5mSmcGA9M46sCyNjopBpIavN+36pgw++yp2uc6gjC784LvDyMrM0MVp0uipGKTJi0ajrNuw85syWLdhJwDWvxsXnTqCrMwM0nroRDxpOlQM0iRFo1HWfLWd7Nw85i7JI2/zbpo1gxEDezDrzFFMHpVBr27two4pEgoVgzQZkUgUX7eV7Nw8snPz2VhYRPPmzcgc3JMzjxrM4aPSdd2BCCoGaeTKyyMs+2IL2Tn5zMvNp3DHHlq2aM7Yob04d+pQJo5M1z2VRWpQMUijU1YeIWf1ZrJz85i/NJ/tu/bSulULxg/rTdbodCaMSKNDO906U2RfVAzSKOwtLWexbyQ7N58Fyzawu7iUdm1aMGF4GlmZGYwf1pu2bfS/u0gQ+pciKWtPSRmLVm5kbk4eH6/YQHFJOR3atWLSyDSmZGYwdmgv3S5TpA5UDJJSdheXsnD5BrJz81m0ciN7S8vp0rE13xnXl6zRGYwe0pNWLXVXNJH6UDFI0tuxey8LluaTnZvPp6s2UVYeoXvntpwwsT9ZmRmMGNidFrpFpkiDCaUYzOxW4JyKh6+6+/Vh5JDktXXHnm+G1OWs2UwkEqV3t3acesRApmRmMLR/N90JTSROEl4MZnY8cAIwDogCr5vZNHd/PtFZJLls2lrMvIprDJZ/sYVoFA7q1YHpxwwha3QGg/t20VwikQQIY4shH/g3d98LYGYrgP4h5JAksGHLbrJz8pibk8eqL7cBcHBaJ86damRlZtA/rZPKQCTBEl4M7r6s8mszOwSYAWRVfY6ZdQVqzjDuG/90kgjrCyrnEuXzeV5sSN2Qvl244OThZGVmcFCvjiEnFGnaQjv4bGYjgVeB69x9dY0/vha4NfGpJB6i0Shr83cwd0ke2bl5rC/YBcCwg7txyekjmTw6gz7d24ecUkQqhXXweQowG7jW3f/xLU/5M/BIjWV9gQ/jHE0aSDQaZfX6bd9sGeRv2U3zZjByUE9OzhrI5NHp9OiiIXUiySiMg8/9gBeAGe7+7rc9x923AdtqvC4B6aQ+yiNRVq4tjJVBbj6btxXTonkzxhzSi+nHDmHSyHS6dmoTdkwRqUUYWwzXAW2BP1X5YX+vbhmamsrLIyxds4W5uXnMz81n684SWrVszqHWmx+eNIyJI9J0D2SRFBPGwedrgGsSvV5pOKVlEZas3kR2Th7zl25gZ9Fe2rRuwWHD+pCVmc5hw/vQvq2G1ImkKl35LIGUlJbzycqNZOfk8dHyDRTtKaN925ZMHJFGVmY646w3bVvrfyeRxkD/kmWfivaUsmjFRubm5rFoRQF79pbTqX0rskZnkJWZztihvWjVUkPqRBobFYNUs6u4lI+WxUZRfOIbKS2L0LVTG44Z34+szHRGDe5JS80lEmnUVAzC9l0lzF+6gezcPHJWb6KsPErPLm05afIAsjIzGDagOy00l0ikyVAxNFFbthczPzc2sXTpms1EopDWoz2nHzmYrMx0DumnIXUiTZWKoQnZWFhEdm4+2Tl5rFxXSDQK/fp05OzjhpKVmcHAjM6aSyQiKobGLm/TLuZWXHD22frYNYMDMzpz3onDyBq5RVhaAAAGqElEQVSdTv+0ziEnFJFko2JoZKLRKF8W7CQ7J7ZlsDZ/BwBD+3dl5ikjmJyZTkZPDakTkX1TMTQC0WiUNV9v/2Yu0debdtGsGQwf0J1ZZ4xi8ugMenXTXCIRCUbFkKIikSir1m9l7pI85uXmU1BYRPPmzRg9uAenf2cQk0el061z27BjikgKahLFULSnlMWrNhGNRsOOUm+RSJQVawuZl5vPlu17aNmiGWOH9mbG8UOZODKNLh01pE5E6qdJFMObC9bx4EvLan9iimjdsjmHDuvNhadkMGFEGh3baS6RiDScJlEMpx85mPHD+hBpBFsMAL27taddmybxVyciIWgSP12aN29Gvz6dwo4hIpISNPRGRESqUTGIiEg1KgYREalGxSAiItWoGEREpBoVg4iIVJNKp6u2ANiwYUPYOUREUkaVn5mB78ObSsWQDnD++eeHnUNEJBWlA2uCPDGVimEhcCSQD5Qf4Gv7Ah9WvP6rBs6VaHovyaexvA/Qe0lW9XkvLYiVwsKgL0iZYnD3EmBOXV5rZpVffuXuaxsqUxj0XpJPY3kfoPeSrBrgvQTaUqikg88iIlKNikFERKpRMYiISDVNpRi2Ab+s+Jzq9F6ST2N5H6D3kqwS+l6aNYa7momISMNpKlsMIiISkIpBRESqSZnrGOrDzM4DbgJaA3e4+10hR6ozM+sMZAOnpvK52WZ2K3BOxcNX3f36MPPUh5n9CjgLiAIPuvufQo5UL2b2R6CXu88MO0tdmdm7QB+gtGLR5e6+IMRIdWZmpwG3AR2AN9z9mnivs9FvMZjZQcDtwBHAGOAyMxsRbqq6MbNJxC7yGxp2lvows+OBE4BxwFhgvJlNCzdV3ZjZUcCxQCZwGPBjq3I1Uqoxs+OAmWHnqA8zawYMA8a4+9iKj1QthUHAvcAZwGjgUDM7Kd7rbfTFABwPvOvuhe6+G3iW2G93qWgWcDWQF3aQesoH/s3d97p7KbAC6B9ypjpx9/eBY9y9DOhNbCt8d7ip6sbMuhP7Jeq3YWepJyO29faamS0xsx+FHagepgFPuftXFf9WZgBxL7mmsCspg9gPokr5wMSQstSLu18K1S6PT0nuvqzyazM7hNj/7FnhJaofdy81s18C1wHPAF+HHKmu7gNuBPqFHaSeugHvAFcC7YD3zMzd/a1wY9XJEGCvmb0BpAEvAzfHe6VNYYuh2bcsiyQ8hfwfZjYSeAu4zt1Xh52nPtz9VqAXsR+qs0KOc8DM7FJgvbu/E3aW+nL3ee5+gbvvdvfNwIPAyWHnqqOWxPZ6/AA4nNgvtRfGe6VNoRi+Jta0ldJJ/V0xKc/MphD7re4Gd3807Dx1ZWbDzGwsgLsXAc8RO96QamYAJ5jZp8CvgNPN7I6QM9WJmR1RcaykUjP+9yB0qtkAvO3um9y9GHiBBOzxaAq7kt4GbjOzXsT2/U4HLgs3UtNmZv2I/Q8+w93fDTtPPQ0CfmlmRxDbr30G8FC4kQ6cu0+t/NrMZgJHu/tPw0tUL12BX5lZFtCK2G/YV4Qbqc5eAR41s67ATuAkYv924qrRbzG4+9fE9pv+C/gUeMLdPwo3VZN3HdAW+JOZfVrxkZL/cN39n8A/gcXAIiDb3f8Rbqqmzd1fAV7lf/9OHnL3eeGmqpuKs6n+QOxsxOXAOuDheK9XIzFERKSaRr/FICIiB0bFICIi1agYRESkGhWDiIhUo2IQEZFqVAwiNZjZYWb27AE8v6eZ6fQ+aTSawgVuIgfE3T8mdQctitSbikGkBjM7Gvgr8DGwg9i4437ASuD77r7LzL5HbBJpEbCwxusvAa4itkW+BfgRsIrYXKhF7n59xejxR4Dx7l6QgLclEph2JYns33jgu8BwYpN6zzazPsTGXkx39/HErkYFvrk/w4XAke4+jthVq8+5e4TYILQLzOwMYlevnqdSkGSkYhDZv9fdvaRiFn4u0J3YTZ9y3X15xXPuq/L8U4iNSs6uGEj3B6C7mXV393xik1efB+539w8S9i5EDoB2JYnsX3GVr6PEJnVWfq5UVuXrFsBj7v5zADNrTmxLY2vFn48ECkjRe4JI06AtBpED9yEw0szGVDyeWeXP3gTONbP0isdXEBsvjplNBK4hdgvQrmYW93v3itSFikHkALn7JuA84HEz+wQYWOXP3gB+D7xlZjkVz/se0BF4EvhxxcTfmcAtZjYuwfFFaqXpqiIiUo22GEREpBoVg4iIVKNiEBGRalQMIiJSjYpBRESqUTGIiEg1KgYREalGxSAiItX8fyIAK4nQXcneAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fibonacci = [1,1,2,3,5,8,13]\n",
    "plt.plot(fibonacci)\n",
    "plt.ylabel('some fibonacci numbers')\n",
    "plt.xlabel(\"index\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code does a couple of things.  First is imports the matplotlib pyplot module (more on that in a moment) as `plt`.  That means that future calls to the matplotlib library can mostly be made using `plt`.  Next it creates a short list of fibonacci numbers.  Then is calls `plt.plot(fibonacci)` which create a basic plot.  The plot assumes the given numbers are the y values and assigned sequentially increasing x values to each point (going from 0 to 6 in this case).  Next, we add a y-label and then an x-label to the figure.  Finally we call `plt.show()` which displays the plot in the Jupyter notebook.\n",
    "\n",
    "The first reaction most people (particularly new users) have looking at a plot like this that they'd like to change a few things.  For example, maybe you don't like the boring blue color or something.  Well it is possible within the very basic matplotlib [pyplot](https://matplotlib.org/tutorials/introductory/pyplot.html) interface to change many of these things quite simply.  First let's plot a second line on the same plot which shows a linearly increasing sequence of integers for comparison:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fibonacci = [1,1,2,3,5,8,13]\n",
    "plt.plot(fibonacci)\n",
    "linear = [1,2,3,4,5,6,7]\n",
    "plt.plot(linear)\n",
    "plt.ylabel('some numbers')\n",
    "plt.xlabel(\"index\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we want to change the colors of the plot here we can specify them as an argment to the `plt.plot()` function.  There are a variety way to set colors in matplotlib but one simple one is through a single character reprenting common colors:\n",
    "\n",
    "| **code** | **color** |\n",
    "|-------|------------|\n",
    "| b | blue |\n",
    "| g | green |\n",
    "| r | red |\n",
    "| c | cyan |\n",
    "| m | magenta | \n",
    "| y | yellow |\n",
    "| k | black |\n",
    "| w | white |\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can read more about colors in matplotlib [here](https://matplotlib.org/tutorials/colors/colors.html).  Here's an example where we change the color of the two lines we plotted to be cyan and magenta."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fibonacci = [1,1,2,3,5,8,13]\n",
    "plt.plot(fibonacci,'c')\n",
    "linear = [1,2,3,4,5,6,7]\n",
    "plt.plot(linear,'m')\n",
    "plt.ylabel('some numbers')\n",
    "plt.xlabel(\"index\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also change the type of line that was drawn by specifying a single character after the color\n",
    "\n",
    "\n",
    "| **code** | **type** |\n",
    "|-------|------------|\n",
    "| - | solid line |\n",
    "| -- | dashed line |\n",
    "| -. | dash-dotted line |\n",
    "| : | dotted line |\n",
    "| '' | none | "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's an example where the fibomacci sequence was turned to a dashed line and the linear sequece to a dotted one.  Kind of looks nice in some ways."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fibonacci = [1,1,2,3,5,8,13]\n",
    "plt.plot(fibonacci,'c--')\n",
    "linear = [1,2,3,4,5,6,7]\n",
    "plt.plot(linear,'m:')\n",
    "plt.ylabel('some numbers')\n",
    "plt.xlabel(\"index\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Anytime we have multiple patterns in the same plot using colors to differentiate them we want to give the reader some type of **legend** which lets them lookup the meaning of the different colors.  In matplotlib this can be as simple as just calling the `plt.legend()` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fibonacci = [1,1,2,3,5,8,13]\n",
    "plt.plot(fibonacci,'c--', label='fibonacci')\n",
    "linear = [1,2,3,4,5,6,7]\n",
    "plt.plot(linear,'m:', label='count')\n",
    "plt.ylabel('some numbers')\n",
    "plt.xlabel(\"index\")\n",
    "plt.legend(loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The legend is a little box that appears within the plot (if there is space and it wouldn't cover up important data) that provides the meaning of what the lines show.  Notice we added a `label` option to each line we plotted so that the legend knows what to display.  You can of course customize this."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Speaking of customization, this chapter could go on for pages (and in fact could be an entire book) if we stepped through every possible customization available within matplotlib.  Instead, I am providing links here to a couple of the useful tutorials on the matplotlib website.  If you get interested in becoming a plotting master in matplotlib reading through these might be helpful.\n",
    "\n",
    "- [Intro to pyplot](https://matplotlib.org/tutorials/introductory/pyplot.html#sphx-glr-tutorials-introductory-pyplot-py): this is a very basic introductory mode of using matplotlib most similar to matlab\n",
    "- [Colors in matplotlib](https://matplotlib.org/tutorials/colors/colors.html): learn about all the color options\n",
    "- [A guide to legends](https://matplotlib.org/tutorials/intermediate/legend_guide.html): how to customize legends\n",
    "- [A gallery of examples with code](https://matplotlib.org/tutorials/introductory/sample_plots.html#sphx-glr-tutorials-introductory-sample-plots-py): Check here and perhaps you can get some starter code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Some (sometimes interesting) technical stuff"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is a bit of technical stuff about matplotlib which is not strictly *necessary* to know in order to make most plots, especially in seaborn but can help you understand a bit more about why certain commands exist.  First we want to decompose a figure into various parts:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "    \n",
    "<div style=\"text-align: center\">\n",
    "    <img src=\"https://matplotlib.org/_images/anatomy.png\" width=\"650\">\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are lots of graphic elements that you can modify in matplotlib but the most important conceptual ones are the **figure**, the **axes**, and the **axis**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Figure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The overall figure is a special object in matplotlib.  The figure keeps track of all the various elements of the figure.  A figure can have one or more **axes**, **legends**, **titles** and so on as well as the **canvas** which (like a painting) is where things are drawn.  To create a figure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()  # an empty figure with no axes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, since there is nothing in the figure yet it often doesn't display anything yet.  You don't need to explicitly create a figure in all cases.  For example, in the first example in this notebook we just called `plt.plot()` which by itself created a new figure.  However, at a lower level a figure object is the basic starting point for building a plot.  You rarely ever need to call the figure like this directly but it is useful to know the concept of a figure when reading some code snippets online."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Axes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A more interesting case is to add a set of *axes* to the figure.  Axes are what we typically would think of as a \"plot\".  The next command uses `plt.subplots(2,2)` to create a figure composed of two columns with two rows of plotting axes.  This is useful for making multi-panel figures.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_lst = plt.subplots(2, 2)  # a figure with a 2x2 grid of Axes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_lst = plt.subplots(1, 2)  # a figure with a 1x2 grid of Axes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 15 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_lst = plt.subplots(5, 3)  # a figure with a 5x3 grid of Axes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now something is displayed in Jupyter because there is something to draw.  Again notice we didn't need to call `plt.figure()` to explicitly create a plot because subplots does it for you. \n",
    "\n",
    "Notice that `plt.subplot()` returns two variables.  One is the figure (which we assigned to a variable `fig` and another which is a list containing the axes for the plot (which we assigned to `ax_lst`).\n",
    "\n",
    "Lets look inside `ax_lst`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x12aa03278>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x12aa10c88>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x12af7cdd8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x12b13ae80>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_lst = plt.subplots(2, 2)  # a figure with a 2x2 grid of Axes\n",
    "ax_lst"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice it contains an 2 dimensional array (2x2 in this case) which has a subplot object.  This is how we can configure or control individual subpanels (i.e., axes).  For example here are a few ways to add a title to each panel:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Panel 4')"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7tndKejdwMcXF0p3ACts372GZfy/ppvJum4Mp3v/zo8GtZbwSTURuA0j6ZWAVxetPPj+QldsH5RrDJCLpXcAbgW8DvwnssP1r5bt67gfOrIz+BooLoG8Ffh14n6TXAH8N/J7to4ATgdXlS99GVRaFMynuq38dcH2rKxaveBOR25KmUdw0cw7FcynR0IQcMUzWt7U2iOsDFOfvhoDHgI/a3i5pCcUvmR+Uo95ie3mDRR4gaVPZ/SrghxTr9ATwhKRHJZ0F/BbwX4AXJf1rOf5NtncCP5HUOQX0Y+Bw4B5JPwQOoNhW9wL/Doy6rWxfKWkVxfWGdRQPYO3RnrZX+W94XWX0mcB222/pY3s1Vh79bATe332f+SDzK7m922TI7T8F7rb9vyUd1yDm3SZrbo9XXo/7EcNkfVtrr7jKf5DVwG/Zngc8CKwoBy8APm17fvnXNBF+WpnmLbaPs31bubxPAn9FkZhvA1YCN1I8hHUg8NPKfA4qh58NPGB7ju35FNcMTqLYoYYoDs2713uepLcD2N4FXAMc1SvwXtvL9qbOugHvBrYDy8rBe7u9GpH0TuAeilMVIxlIfiW3ayY8t4HfA367LFDXAG+oFKtRTdbcHs+8nohTSZP1ba17jAvYDzi9fOAPip2nk4wLgCWSNktaUx729us3KNbxhxSvUFgE7Crjmtk17n8EPgh8GZgnaVG5HacD/4vihXD3ULy+odvbgL+WdGDZvwS4s0F8vbZX1eeBu2zfU/YPYntVnQacwQivqhhwfiW3mxmX3LY92/a88j/wU4FHyu5eJmtuj1teT0RhGO2tlb2GN36r5SDisv0j2zcASDqA4k6eGyrjrgDmA08AV7YQz58Bn6A4HF4E/BPFOdqtwC90RpJ0EMVh9P+k+HWzAfgKxatMXktxTvZxitvXfrF7Ibb/BvgH4AFJDwL/Gfh4g/h6/Tt24ptB8Uvwgq5xV9Du9trN9qm2N4wyeJD5ldxuZlxyuw+TMrfHM68n4hrDoN/WurcazV/SdIqdZrPtrwDY/lBl+CU0eIFVeX7woD0Mvwd4s6Q/Bg60fV45/1MpnthdV473HPCfKss/F7iW4pfFJbb/vhz098DHRlnW+YzyFtA9aPrvsRi4wfbTleWNeXu1aJD5ldxmcuV2ZZnfBJreqjoVc7vV3JqII4bR3lrZa/jut1qOMt2g40LSbIpfLZspDk2RNF3SpyqjDVGc/xyXuCTNlVTdKTrL77k+g4yr4oPA33Z6xmF79TLI/EputxhXcntMWs2tRoVB0sGSvqPiwZXuYfMl3S/p3yRdI+lVZftcSXdL+ldJ/1AeFkJxGHi8pJnlee2TgG905lceGr6g4qEUqLzVkiJxP1JtbxJ/Q3uMq9ywNwNft312eaEWikPdc8sLQ1Dcdtfm7Z57jIviQt0lko5Q8RTzGcD1o23HcYyr81T10RR3jnQMenvt0Qjb5ePAm4FDGZ5f9ye3k9sjxDXpcrvt3GryzedWr4R7kr6ttUFcJwJvB06WtKn8u8bFO/k/THFP9cMUyXLueMVl+xmK87U3UdyKNgRcVk4+2nYceFzlaDOBn9l+oTLdQLfXaEbJr8eAD/D/P9jTnV9vJbmd3J7EuT2o3Or5SgxJ11Bc8Pkb4DhX7p1VcSX8TttvKPuPpbgQ8xsUT8++1sV9tL9CceX+9SPMf6TPH+5P8UGT7wI/77USEWM0jeKQ+mMUD00lt2Nf0cnt+22/uLcz6Xnx2XbnfONIg9u4Ej7q5w8jBuxY2/ckt2MfdCzFmZ690u9dSW1cCR/p84eHAd/86le/yqxZs4ZPEdGHbdu2db65vHUPoyW3Y8ppmNs99VsY+v4urvfw+cNZs2YxZ06bt3NH1OzpVE5yO6ayvk5T9nW76gTeZRExUMnteCXbq8Iw0XdZRAxKcjtiDKeSbB9e6c53cWOfkdyOqMv3GCIioiaFISIialIYIiKiJoUhIiJqUhgiIqImhSEiImpSGCIioiaFISIialIYIiKiJoUhIiJqUhgiIqImhSEiImpSGCIioiaFISIialIYIiKiJoUhIiJqGn2oR9IpFF+p2h9YaXtVZdh86h88nwlst/0WSUuAi4EflMNusb28jcAjWnCipGUkryNqehYGSYcCFwFHAy8CGyWtt/0QgO1NwPxy3AOB+4Bl5eQLgE/b/toAYo/o1znAPJLXETVNjhgWAXfafhZA0jrgZODCEcb9PHCX7XvK/gXAGyV9DvgX4Czb26sTSJoBzOiaz5zmqxCx1zYOKq/LeSa3Y0pqco3hEGBrpX8rIyR3uRMsBS7oGncFxS+vJ4ArR5j/2cBjXX8bGsQV0a+nK91t5zUkt2OKanLEMDRC284R2hYDN9jevbPZ/lCnW9IlwKMjTHc59XO5UOyg2YFivLWZ15DcjimqSWHYAhxb6Z8NPDXCeB8EvtTpkTQd+JjtlWXTEPBS90S2dwA7qm2SGoQV0beZle5W8xqS2zF1NTmVdDtwvKSZ5UW4k4BvVEeQNERxcfreSvNzwLmS3ln2nwlc33/IEa1ZmLyOGK5nYbC9BVgOrAc2AWtt3yfpVknHlKPNBH5m+4XKdD8HPgyslvQwxQ52btsrENGHS0leRwzT6DkG22uBtV1tJ1S6nwZmjTDdBuCoPmOMGJQbbV9RbUheR+TJ54iI6JLCEBERNSkMERFRk8IQERE1KQwREVGTwhARETUpDBERUZPCEBERNSkMERFRk8IQERE1KQwREVGTwhARETUpDBERUZPCEBERNSkMERFR0+h7DJJOAc4D9gdW2l7VNfyLwMeB7WXT1bZXSZoPXA1MB+4Gltl+ua3gI/p0oqRlJK8janoeMUg6FLgIeA8wD1gq6c1doy0Aftf2/PKvs4OtAc6yfSTFt3FPay/0iL6dQ/I6YpgmRwyLgDttPwsgaR1wMnBhZZxjgM9Kej3FL6jPAL8MHGD7W+U41wEXAKvbCT2ibxuT1xHDNSkMhwBbK/1bgXd0eiQdBPwzxU7zPYod5QvAzSNMN6d75pJmADO6moeNFzEAT1e6W83rch7J7ZiSmhSGoRHadnY6bD8H7P5OrqTLgGuBW/Y0XcXZwPkN4ogYtDbzGpLbMUU1uStpC/UPos8Gnur0SJor6WOV4UPAS72mq7gcOKLr79gmwUf0aWalu+28huR2TFFNjhhuB1ZImgk8D5wELK0M/ylwiaT1FIfcZwDX235c0guSFtr+R2AJcFv3zG3vAHZU2yTtzbpEjNXCQeU1JLdj6up5xGB7C7AcWA9sAtbavk/SrZKOsf0M8AngJsAUv6wuKydfDKyU9DDwauCKAaxDxN66lOR1xDBDu3btmugYhpF0OPDYHXfcwZw5uVYX7XryySc5/vjjAY6w/b3xXHZyOwaprdzOk88REVGTwhARETUpDBERUZPCEBERNSkMERFRk8IQERE1KQwREVGTwhARETUpDBERUZPCEBERNSkMERFRk8IQERE1KQwREVGTwhARETUpDBERUZPCEBERNU0+7YmkU4DzgP2BlbZXdQ3/AHABxVeuHgM+anu7pCXAxcAPylFvsb28reAj+nSipGUkryNqehYGSYcCFwFHAy8CGyWtt/1QOfxgYDWwwPYWSRcCK4A/AhYAn7b9tQHFH9GPc4B5JK8japqcSloE3Gn7WdvPA+uAkyvD9wNOL78NDfAgMLfsXgAskbRZ0hpJr2kr8IgWbExeRwzX5FTSIcDWSv9W4B2dHts/Am4AkHQA8DngLyrjfhm4D/gScCXFh9R3kzQDmNG1zHwMN8bD05XuVvO6nC65HVNSk8IwNELbzu4GSdMpdqTNtr8CYPtDleGXAI+OMK+zgfMbRRsxWG3mNSS3Y4pqcippCzCr0j8beKo6gqTZwAZgM3Bq2TZd0qcqow0BL40w/8uBI7r+jm0Yf0Q/Zla6285rSG7HFNXkiOF2YIWkmcDzwEnA0s5ASdOAm4Gv2/6TynTPAedK2mj728CZwPXdM7e9A9hRbZM01vWI2BsLB5XXkNyOqatnYSjvyFgOrKe4re8a2/dJuhX4IvArwNuBaZI6F+8esH2qpA8Dq8tztP8GLBnIWkTsnUtJXkcM0+g5BttrgbVdbSeUnQ8wyikp2xuAo/oJMGKAbrR9RbUheR2RJ58jIqJLCkNERNSkMERERE0KQ0RE1KQwRERETQpDRETUpDBERERNCkNERNSkMERERE0KQ0RE1KQwRERETQpDRETUpDBERERNCkNERNSkMERERE0KQ0RE1DT6UI+kU4DzKL50tdL2qq7h84GrgenA3cAy2y9LmgusAX4JMLDY9nMtxh/RjxMlLSN5HVHT84hB0qHARcB7gHnAUklv7hptDXCW7SMpPo5+Wtl+FXCV7TdRfBHrC20FHtGCc0heRwzT5IhhEXCn7WcBJK0DTgYuLPsPAw6w/a1y/OuACyRdA7wX+GCl/S7gs9WZS5oBzOha5mEA27ZtG9vaRDRQyat7B5XX5TyS2zGuKnk1rZ/5NCkMhwBbK/1bgXf0GD4HeB3wY9svd7V3Oxs4f6QFL168uEF4EXvt5Up323kNye2YOL8KPLK3EzcpDEMjtO1sMLzXdB2XU/zqqno9cAfwPuD7vUMcN3OADcCxwJMTHEtV4hqbuRS/8nd0tbeZ15DcbkPiGptObj/az0yaFIYtFCvfMRt4qmv4rBGGPwMcLGma7Z+PMB0AtnfQtYNK6nR+3/b3GsQ4LipxPZm4epsCcb220txqXkNyuw2Ja2wqcf2sn/k0uV31duB4STMlHQicBHyjM9D248ALkhaWTUuA22y/RFFRP1Jt7yfYiJYtTF5HDNezMNjeAiwH1gObgLW275N0q6RjytEWAyslPQy8GriibD+d4m6PhyiOOs5rewUi+nApyeuIYRo9x2B7LbC2q+2ESvdm6hfuOu2PA8f1F2LEwNxo+4pqQ/I6YvI++bwDuIDhFwcnWuIam8Q1uZa9J4lrbPbpuIZ27drVTjgREbFPmKxHDBERMUFSGCIioqbRxee2TdaX8jWI6wMU5++GgMeAj9reLmkJcDHwg3LUW2wvH8e4vgh8HNheNl1te9Vo23E84iqXfV1l9JnAdttvGfT2Kpd/MLAReH/3feaDzK/kdutxJbfrcY1LXo/7EcNkfSlfr7jKf5DVwG/Zngc8CKwoBy8APm17fvnXZiI02V4LgN+tLL+TxKNtx4HHZXtTJx7g3RQ79rJKvAPZXmVs7wTuAY4cZZSB5Fdyu924KstPbjO+eT0Rp5J2v5TP9vNA5+VlwKgvL/sdSftRvLxsXbV9vOIC9gNOL5/rgGLnmVt2LwCWSNosaY2k14xjXADHAJ+V9KCkKyX94mjbcZzj6vg8cJfte8r+QW4vKHaIMxjhieQB51dyu924ILldNW55PRGFYbSXk/UaPpaXl7Uel+0f2b4BQNIBwOeAGyrjrgDmA08AV45XXJIOAv4Z+AxwFMXbPL/Qa7pBx1WJbwawlOI0RXXcFQxme2H7VNsbRhk8yPxKbrcYV3K7bjzzeiKuMQz6pXx7q9H8JU2n2Gk22/4KgO0PVYZfQp8vsBpLXOW5wt0PZUm6DLgWuGVP0w06rorFwA22n+40DHh79TLI/EputxhXcntMWs2tiThiGO3lZL2G73552SjTDTouJM2meE/OZuDUsm26pE9VRhsCXhqvuCTNlfSxEZbfc30GGVfFB4G/7fSMw/bqZZD5ldxuMa7k9pi0mlsTURgm60v59hhXuWFvBr5u+2zbnScDnwPOLS8MAZwJXD9ecQE/BS6RdISkIYpzkNePth3HMS7KeI4G7q00D3p77dGA8yu53WJcJLcbazu3xr0weJK+lK9BXCcCbwdOlrSp/LvGxauXPwysLuM9Gjh3vOKy/QzwCeAmilvRhoDLyslH244Dj6scbSbwM9svVKYb6PYazXjkV3K73biS270NKrfySoyIiKjJk88REVGTwhARETUpDBERUZPCEBERNSkMERFRk8IQERE1KQwREVGTwhARETX/D++/pEmS/t8mAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_lst = plt.subplots(2, 2)  # a figure with a 2x2 grid of Axes\n",
    "ax_lst[0,0].set_title(\"Panel 1\")\n",
    "ax_lst[0,1].set_title(\"Panel 2\")\n",
    "ax_lst[1,0].set_title(\"Panel 3\")\n",
    "ax_lst[1,1].set_title(\"Panel 4\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So this steps through each axes we created and adds a title to the corresponding plot.  We can do other things as well like add a x-label:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'x')"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_lst = plt.subplots(2, 2)  # a figure with a 2x2 grid of Axes\n",
    "ax_lst[0,0].set_title(\"Panel 1\")\n",
    "ax_lst[0,0].set_xlabel(\"x\")\n",
    "ax_lst[0,1].set_title(\"Panel 2\")\n",
    "ax_lst[0,1].set_xlabel(\"x\")\n",
    "ax_lst[1,0].set_title(\"Panel 3\")\n",
    "ax_lst[1,0].set_xlabel(\"x\")\n",
    "ax_lst[1,1].set_title(\"Panel 4\")\n",
    "ax_lst[1,1].set_xlabel(\"x\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It can be a little hard to see, but we added here a label 'x' to each panel.  Let's fix it by calling the `plt.tight_layout()` command which spacing things out a little:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_lst = plt.subplots(2, 2)  # a figure with a 2x2 grid of Axes\n",
    "ax_lst[0,0].set_title(\"Panel 1\")\n",
    "ax_lst[0,0].set_xlabel(\"x\")\n",
    "ax_lst[0,1].set_title(\"Panel 2\")\n",
    "ax_lst[0,1].set_xlabel(\"x\")\n",
    "ax_lst[1,0].set_title(\"Panel 3\")\n",
    "ax_lst[1,0].set_xlabel(\"x\")\n",
    "ax_lst[1,1].set_title(\"Panel 4\")\n",
    "ax_lst[1,1].set_xlabel(\"x\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can see what is happening better.  Looks so nice!  Almost don't want to add data to it!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The key point is, as you can see, a **Figure** can contain many **Axes**.   Each Axes has a title (set via `set_title()`), an x-label (set via `set_xlabel()`), and a y-label set via `set_ylabel()`).  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before moving on let's look at a couple other useful things to do with axes.  One is that it is sometimes useful to give a title not to an individual axes but to the overall figure.  `fig.suptitle()` works well for this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_lst = plt.subplots(2, 2)  # a figure with a 2x2 grid of Axes\n",
    "fig.suptitle('Vertically stacked subplots')  # add a overall title\n",
    "ax_lst[0,0].set_title(\"Panel 1\")\n",
    "ax_lst[0,0].set_xlabel(\"x\")\n",
    "ax_lst[0,1].set_title(\"Panel 2\")\n",
    "ax_lst[0,1].set_xlabel(\"x\")\n",
    "ax_lst[1,0].set_title(\"Panel 3\")\n",
    "ax_lst[1,0].set_xlabel(\"x\")\n",
    "ax_lst[1,1].set_title(\"Panel 4\")\n",
    "ax_lst[1,1].set_xlabel(\"x\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sometimes it is nice to iterate over the figures in a single for loop. To do this you can access `ax_lst.flat` which \"flatten\" the 2-dimensional figure into a list of plots you can modify one by one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CiJhBOqa9OXC/pMslTS89OrMe4lwya6ylc0T5ccbbAVOAdYCngHmSzi4xNrOe41wyW1Mr54jOAp4k3RF+Fen5KR8DZgBHlxueWe9wLpk11krv25sBMyNiSXFgRLwg6dBywjLrSc4lswZa6WtudpNxt7Q3HLPe5Vwya2yo9xGZmZm1lQuRmZlVyoXIzMwq5UJkZmaVciEyM7NKuRCZmVmlXIjMzKxSLkRmZlYpFyIzM6uUC5GZmVXKhcjMzCrlQmRmZpVyITIzs0q5EJmZWaVciMzMrFIuRGZmVikXIjMzq1QrjwofNkmHAacC6wLnRcSFdeOnAhcDGwN3AcdFxCtlxmTWbZxH1utKaxFJ2hI4C3gbsCMwW9Jf1U12BXBCREwB+oBjyorHrBs5j2wsKLNFtDdwe0Q8AyDpauAg4Mz8fitg/Yi4L08/H/g0MK+4EEnjgfF1y94KYMWKFWXFbj2ssN+MqzKOFrUlj/K0ziVrq3blUpmFaCKwvPB+ObDLIOMnNVjOicAZjVYwa9asEYZoY9x2wONVBzGIduUROJesPCPKpTILUV+DYauGML7mfNKvvKJtgNuAGcAvhxNcm00C7gb2AH5VcSzgeAYzGbgT+HnVgbSgXXkEzqXhcDzNtSWXyixES0kbq2YLYFnd+AlNxgMQESuBlcVhkmovfxkRT7Qh1hEpxPMrx7OmDo7nD1XG0aK25BE4l4bD8TTXrlwq8/Lt7wF/J2kzSRsABwLfrY2MiF8AL0l6ax50OPCdEuMx60bOI+t5pRWiiFgKnAIsBBYDCyLifknfljQtTzYLOE/So8BrgS+WFY9ZN3Ie2VhQ6n1EEbEAWFA3bGbh9RJWP/FqZnWcR9brurVnhZWkS1RXDjbhKHE8zTmeztVp28LxNNeT8fT19/e3JxwzM7Nh6NYWkZmZ9QgXIjMzq1SpFysM13A7eZQ0mdTv1uZAALMi4vlRiOddpOOkfcB/A++PiGclHQ6cDfxPnvRbEXHKKMRzOnAU8GwedHFEXFhW55jN4snrnF+YfDPg2YjYvqztk9e7EbAI2K/+fovR3n+q4jxqS0xjOpdGK486rkU0wk4eLwIuiog3AT8ETis7nvyPmgfsGxE7Ag8Cc/Po6cBHI2Jq/mvHjtHK9pkOHFJYb21nbnvnmIPFExGLa3EAu5MS+rhCnG3dPjmmXYF7gCkDTDJq+09VnEcjj6mw7jGZS6OZRx1XiCh08hgRLwC1Th6BATt5/CdJ6wB75un/OLzseIB1gA/l+z0gJdDk/Ho6cLikJZKukPS6UYgHYBpwsqQHJV0gab2BttsoxVPzSeDOiLgnvy9j+0BKiA/ToIeBCvafqjiPRh4TjO1cGrU86sRCNFgnjgON3xR4rtA8btb5Y9viiYjfRMT1AJLWBz4BXF+Ydi4wFXgSuKDseCRtCDwAzAF2IvW2fNpg85UVTyGu8cBs0qGX4rRzae/2ISKOjoi7hxhvWftPVZxHI4xprOfSaOZRJ54jGm4nj0Pp/LGd8QAgaWNS4iyJiMsAIuKAwvhzaE8nm03jycdi/3izo6RzgUuBbzWbr6x4CmYB10fEU7UBJW2fwYz2/lMV59EIY3IuNdXW/acTW0SDdeI40PingY0kjRtgvrLiQdIWpB5xlwBH52EbS/qXwmR9wMtlxyNpsqQPNFhvy51jtjOegv2BrxfiLGv7DGa095+qOI9GGJNzqam27j+dWIiG1cljRLxM2okPLg4vO568wW8CvhERJ0ZE7Q7h54GT8gk/gOOB68qOB3gROEfS1pL6SMd4rxtou41CPOQ4dgbuLQwua/s0VcH+UxXn0Qhjwrk0oHbvPx1XiGJknTx+iHSlySOkrvNPHYV43gm8BThI0uL8d0lEvAq8B5iX49wZOKnseCLiaeBY4EbSpZN9wLl59rZ3jtni/2sz4A8R8VJhvlK2z0Cq2n+q4jwaeUzOpTWVtf+4ix8zM6tUx7WIzMxsbHEhMjOzSrkQmZlZpVyIzMysUi5EZmZWKReiLiVpL0kPtTBdv6RNh7js+ZLmDD86s+7gPOoMLkRmZlapTuxrbsyTdARwBrAD0E/qSv1zEfHVAaafAlwIbEjqjHAxcHDhprezJE0n/fA4NSJuyvMdRbr5bC3gN8DxEfFYaR/MbBQ5j7qHW0QdKHf2eC9wDulu5bsHSp7sGOCyiNgN2BbYGti3MP7nEbET8F7gstyFyAzgCGCPiHhLXte17f80ZtVwHnUPt4g613Gkzh9fJHXZ0czJwNslnUR6iNVE0q+6mi8BRMRDuduN3UgP39oWWCSpNt0mkjZp2ycwq57zqAu4EHWuNwDrAa8BJko6ktQfF8ANwO2Fab9G+l9+g9RF/WRW74791cLrWs+844DLI+JkAElrkRLvWcx6h/OoC/jQXAdSesrh14DTSQ+/+hrwmcJjgE+vm2Uf4MyIuIp0LHxXUoLUHJmXuxOwHfB94Bbg0Nz1PqRfjreV84nMRp/zqHu4RdSZPgusiIhLACTtT3qW/UA96n4KuE7SM8DvgDtJhwtqtpH0ACm5DomIZ4CbJZ0N3CppFfAc8O6I6C8cYjDrZs6jLuHet83MrFI+NGdmZpVyITIzs0q5EJmZWaVciMzMrFIuRGZmVikXIjMzq5QLkZmZVcqFyMzMKuVCZGZmlXIhMjOzSrkQmZlZpVyIzMysUu59u0NIeiPwOPDjwuA+4AsRcWkJ6zsSOCgi9qsb3gd8Bnh3HvQD4IMR8bt2x2DWbp2SR3XT/DNwTERs3+719woXos7yYkRMrb2RtCXwkKQfRsSDoxTDAcDfA1NJD/76BvDPwOdGaf1mI9UJeVRb91tJT359ZjTX221ciDpYRCyV9FNgiqTHgXmkRxhvAvwWOCwiQtIdwL3AW0lPlbwbOCIiVknaHTgbeC2wCpgbETc1Wee1km6MiJclbQRsDvymvE9pVq4q8ghA0huAC4GPA58s5cP1CJ8j6mCSdiM9mOv7wD8CKyPiryNiCumQ2fGFyf8C2At4M/C3wAxJrwO+ArwvInYiPSJ5nqTJzdabi9DxwC+BTYHr2vrBzEZRFXkkaRywgFSElrb9Q/UYt4g6y/qSFufXawO/BmZFxJPAk5J+LukEUlLtRfr1VnNjRKwCfivpZ6Rfe7sBWwDXF54W2Q/sMFggEXGBpAtJ54uuBmaM9MOZjZJOyKPPAXdFxK2S9mrPx+pdLkSdZbVj20WSPgjMBi4g/dJ6Bti6OG/hdT/pBO044NGI2LWwnInA08CsAdazI7BWRDyQH3d8CekckVm3qDyPgPcBT0k6ANgQ2FLS4oHiGut8aK577APMj4j/BAJ4BylBmrkP2E7SngCSpgI/BSY2mWcH4CuSNsjvDwduH0ngZh1kVPIoIraIiB1z4TkaeNxFaGAuRN3j88Cx+ZDDbcCPSIcWBhQRTwMHAv8qaQlwOek49y+azHM58E3gh5IeBP4SOKo9H8GscqOSRzY0ff39/VXHYGZmY5hbRGZmVqlSL1bI96EsAvaLiCfqxk0FLgY2Bu4CjouIV8qMx6xbOZesl5XWIpK0K3AP6caxRq4ATsjX8vcBx5QVi1k3cy5ZryuzRXQM8GHSib3VSNoKWD8i7suD5gOfJt3xXD/teGB83eB1gW1IV6682r6QbYwYR7ov5AcR8fuqg2mBc8k6VVtyqbRCFBFHAxRuACuaCCwvvF8OTBpgUScCZ7Q1OLNkD1JLo6M5l6wLjCiXqrqhta/BsFUDTHs+6Vde0VbAHVdeeSUTJkxoZ1w2BqxYsYJZs2bB6l/g3cq5ZJVpVy5VVYiWAsW9fgtgWaMJI2IlsLI4rPbLcMKECUyaNNCPP7NB9cKhKOeSdYIR5VIll2/nG8Feyl2kQ7p7/ztVxGLWzZxL1gtGtRBJ+rakafntLOA8SY+Sulb/4mjGYtbNnEvWS0o/NBcRbyy8nll4vQTYpez1m/UK55L1KvesYGZmlXIhMjOzSrkQmZlZpVyIzMysUi5EZmZWKRciMzOrlAuRmZlVyoXIzMwq5UJkZmaVciEyM7NKuRCZmVmlXIjMzKxSLkRmZlYpFyIzM6uUC5GZmVXKhcjMzCrlQmRmZpVyITIzs0q5EJmZWaVciMzMrFJrDzRC0kebzRgR/9b+cMx6j3PJrLkBCxHw5ibj+tsdiFkPcy6ZNTFgIYqI9xffSxofESvLD8mstziXzJpr1iICQNIU4DpgvKTpwG3AARHxWNnBmfUS55JZY61crHABcCLwVEQsA/4d+HKpUZn1JueSWQOtFKLXR8SttTcRcRGwUXkhmfUs55JZA60Uon5J65FPqkqaAIwrNSqz3uRcMmuglUJ0EXAzsLmkzwH35WFmNjTOJbMGBr1YISIulfQzYF9gHWB2RNxSemRmPca5ZNbYoIUoe5h0LPtl4P7ywjHrec4lszqDHpqTtC8QwMeBU4FHJe1ZdmBmvca5ZNZYKy2izwAzIuJhAEk7kS45nTbYjJIOIyXcusB5EXFh3fjTgaOAZ/Ogi+unMeshw8ol55H1ulYKUX8tcQAi4keSWmlJbQmcBewM/B5YJGlhRDxSmGw6cEhE3DvEuM260ZBzyXlkY0GzTk83yS9/IGkO8CVgFXAkcHsLy94buD0insnLuxo4CDizMM004GRJ2wB3AXMi4qW6OMYD4+uWPamF9Zt1hBHmUlvyKM/rXLKO1KxF9GvS/Q59+f05hXH9wJxBlj0RWF54vxzYpfZG0obAA3k5TwDzgdOAU+qWcyJwxiDrMutkI8mlduUROJesQzXr9HSkzyrqazBsVWH5zwMza+8lnQtcypoJdD4puYomAXePMD6zUTHCXGpXHoFzyTpUK52erku672FDUlKMA7aNiEY7etFSYI/C+y2AZYXlTgb2johL86A+0iWtq8m9FK/WU7GkwcI26zjDzKW25BE4l6xztXKxwlXANqQEeADYFbijhfm+B8yVtBnwAnAgMLsw/kXgHEkLSYcUPkzqmdisVw0nl5xH1vNaOWQwlXTFzjdJx5h3Z80TnmuIiKWkwwMLgcXAgoi4X9K3JU2LiKeBY4EbSfdW9AHnDutTmHWHIeeS88jGglZaRMsi4hVJPwG2j4j/krRBKwuPiAXAgrphMwuvrwGuGUrAZl1sWLnkPLJe10qL6IV8Q90S4D2S3gy8vtywzHqSc8msgVYK0fGkQwq3kq7WuQv4fJlBmfUo55JZA630vv0T4KT89uBywzHrXc4ls8aa9azwY/IDvBqJiB1KicisxziXzJpr1iI6ftSiMOttziWzJpr1rHBn/TBJcyNibqkRmfUY55JZc0PteuSdpURhNvY4l8yyoRaiRv1emdnQOZfMslaeK3SNpL3z2xtKjsesZzmXzBprpUV0DXBavhv8t4Vnq5jZ0DiXzBoYtBBFxIKImEE6pr05cL+kyyVNLz06sx7iXDJrrKVzRPlxxtsBU4B1gKeAeZLOLjE2s57jXDJbUyvniM4CniTdEX4V6fkpHwNmAEeXG55Z73AumTXWSu/bmwEzI2JJcWBEvCDp0HLCMutJziWzBlrpa252k3G3tDccs97lXDJrbKj3EZmZmbWVC5GZmVXKhcjMzCrlQmRmZpVyITIzs0q5EJmZWaVciMzMrFIuRGZmVikXIjMzq5QLkZmZVcqFyMzMKuVCZGZmlXIhMjOzSrkQmZlZpVyIzMysUi5EZmZWqVae0Dpskg4DTgXWBc6LiAvrxk8FLgY2Bu4CjouIV8qMyazbOI+s15XWIpK0JXAW8DZgR2C2pL+qm+wK4ISImAL0AceUFY9ZN3Ie2VhQZotob+D2iHgGQNLVwEHAmfn9VsD6EXFfnn4+8GlgXnEhksYD4+uWvRXAihUryordelhhvxlXZRwtakse5WmdS9ZW7cqlMgvRRGB54f1yYJdBxk9qsJwTgTMarWDWrFkjDNHGuO2Ax6sOYhDtyiNwLll5RpRLZRaivgbDVg1hfM35pF95RdsAtwEzgF8OJ7g2mwTcDewB/KriWMDxDGYycCfw86oDaUG78gicS8PheJprSy6VWYiWkjZWzRbAsrrxE5qMByAiVgIri8Mk1V7+MiKeaEOsI1KI51eOZ00dHM8fqoyjRW3JI3AuDYfjaa5duVTm5dvfA/74UXdGAAAFpUlEQVRO0maSNgAOBL5bGxkRvwBekvTWPOhw4DslxmPWjZxH1vNKK0QRsRQ4BVgILAYWRMT9kr4taVqebBZwnqRHgdcCXywrHrNu5DyysaDU+4giYgGwoG7YzMLrJax+4tXM6jiPrNd1a88KK0mXqK4cbMJR4niaczydq9O2heNprifj6evv729POGZmZsPQrS0iMzPrES5EZmZWKRciMzOrVKlXzQ3XcHsbljSZ1AHk5kAAsyLi+VGI512kE3Z9wH8D74+IZyUdDpwN/E+e9FsRccooxHM6cBTwbB50cURcWFYvzc3iyeucX5h8M+DZiNi+rO2T17sRsAjYr/7Gv9Hef6riPGpLTGM6l0YrjzquRTTC3oYvAi6KiDcBPwROKzue/I+aB+wbETsCDwJz8+jpwEcjYmr+a8eO0cr2mQ4cUlhvbWduey/Ng8UTEYtrcQC7kxL6uEKcbd0+OaZdgXuAKQNMMmr7T1WcRyOPqbDuMZlLo5lHHVeIKPQ2HBEvALXehoEBexv+J0nrAHvm6f84vOx4gHWAD+UbDyEl0OT8ejpwuKQlkq6Q9LpRiAdgGnCypAclXSBpvYG22yjFU/NJ4M6IuCe/L2P7QEqID9Ogq5sK9p+qOI9GHhOM7VwatTzqxEI0WG/CA43fFHiu0Dxu1gtx2+KJiN9ExPUAktYHPgFcX5h2LjAVeBK4oOx4JG0IPADMAXYidft/2mDzlRVPIa7xwGzSoZfitHNp7/YhIo6OiLuHGG9Z+09VnEcjjGms59Jo5lEnniMabm/DQ+mFuJ3xACBpY1LiLImIywAi4oDC+HNoT2/PTePJx2L/eNe9pHOBS4FvNZuvrHgKZgHXR8RTtQElbZ/BjPb+UxXn0Qhjci411db9pxNbRIP1JjzQ+KeBjSSNG2C+suJB0hakrtmXAEfnYRtL+pfCZH3Ay2XHI2mypA80WG/LvTS3M56C/YGvF+Isa/sMZrT3n6o4j0YYk3OpqbbuP51YiIbV23BEvEzaiQ8uDi87nrzBbwK+EREnRkStq4rngZPyCT+A44Hryo4HeBE4R9LWkvpIx3ivG2i7jUI85Dh2Bu4tDC5r+zRVwf5TFefRCGPCuTSgdu8/HVeIYmS9DX+IdKXJI6RnuJw6CvG8E3gLcJCkxfnvkoh4FXgPMC/HuTNwUtnxRMTTwLHAjaRLJ/uAc/Psbe+lucX/12bAHyLipcJ8pWyfgVS1/1TFeTTymJxLaypr/3Ffc2ZmVqmOaxGZmdnY4kJkZmaVciEyM7NKuRCZmVmlXIjMzKxSLkRdStJekh5qYbp+SZsOcdnzJc0ZfnRm3cF51BlciMzMrFKd2NfcmCfpCOAMYAegn9SV+uci4qsDTD8FuBDYkNQZ4WLg4MJNb2dJmk764XFqRNyU5zuKdPPZWsBvgOMj4rHSPpjZKHIedQ+3iDpQ7uzxXuAc0t3Kdw+UPNkxwGURsRuwLbA1sG9h/M8jYifgvcBluQuRGcARwB4R8Za8rmvb/2nMquE86h5uEXWu40idP75I6rKjmZOBt0s6ifQQq4mkX3U1XwKIiIdytxu7kR6+tS2wSFJtuk0kbdK2T2BWPedRF3Ah6lxvANYDXgNMlHQkqT8ugBuA2wvTfo30v/wGqYv6yazeHfurhde1nnnHAZdHxMkAktYiJd6zmPUO51EX8KG5DqT0lMOvAaeTHn71NeAzhccAn143yz7AmRFxFelY+K6kBKk5Mi93J2A74PvALcChuet9SL8cbyvnE5mNPudR93CLqDN9FlgREZcASNqf9Cz7gXrU/RRwnaRngN8Bd5IOF9RsI+kBUnIdEhHPADdLOhu4VdIq4Dng3RHRXzjEYNbNnEddwr1vm5lZpXxozszMKuVCZGZmlXIhMjOzSrkQmZlZpVyIzMysUi5EZmZWKRciMzOr1P8H2gcOZYLx8M8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_lst = plt.subplots(2, 2)  # a figure with a 2x2 grid of Axes\n",
    "fig.suptitle('Vertically stacked subplots')  # add a overall title\n",
    "ax_lst[0,0].set_title(\"Panel 1\")\n",
    "ax_lst[0,1].set_title(\"Panel 2\")\n",
    "ax_lst[1,0].set_title(\"Panel 3\")\n",
    "ax_lst[1,1].set_title(\"Panel 4\")\n",
    "for ax in ax_lst.flat:\n",
    "    ax.set_xlabel('x-label')\n",
    "    ax.set_ylabel('y-label')\n",
    "    #ax.set(xlabel='x-label', ylabel='y-label')  # alternative way to do the same thing in 1 line\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Even more interesting is to only show the x and y labels on the \"outer\" axes, i.e., those on the left and bottom of the main figure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_lst = plt.subplots(2, 2)  # a figure with a 2x2 grid of Axes\n",
    "fig.suptitle('Vertically stacked subplots')  # add a overall title\n",
    "ax_lst[0,0].set_title(\"Panel 1\")\n",
    "ax_lst[0,1].set_title(\"Panel 2\")\n",
    "ax_lst[1,0].set_title(\"Panel 3\")\n",
    "ax_lst[1,1].set_title(\"Panel 4\")\n",
    "# add\n",
    "for ax in ax_lst.flat:\n",
    "    ax.set(xlabel='x-label', ylabel='y-label')\n",
    "    ax.label_outer()\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now things are looking really nice!  If you get really advanced you can make plots that have interesting tiled patterns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'gs[-1, -2]')"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig3 = plt.figure(constrained_layout=True)\n",
    "gs = fig3.add_gridspec(3, 3)\n",
    "f3_ax1 = fig3.add_subplot(gs[0, :])\n",
    "f3_ax1.set_title('gs[0, :]')\n",
    "f3_ax2 = fig3.add_subplot(gs[1, :-1])\n",
    "f3_ax2.set_title('gs[1, :-1]')\n",
    "f3_ax3 = fig3.add_subplot(gs[1:, -1])\n",
    "f3_ax3.set_title('gs[1:, -1]')\n",
    "f3_ax4 = fig3.add_subplot(gs[-1, 0])\n",
    "f3_ax4.set_title('gs[-1, 0]')\n",
    "f3_ax5 = fig3.add_subplot(gs[-1, -2])\n",
    "f3_ax5.set_title('gs[-1, -2]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want to learn more about subplots and more advanced plot layout like the one below check out the matplotlib tutorials on [gridspec](https://matplotlib.org/3.1.0/tutorials/intermediate/gridspec.html#sphx-glr-tutorials-intermediate-gridspec-py) and the [tight layout guide](https://matplotlib.org/3.1.0/tutorials/intermediate/tight_layout_guide.html#sphx-glr-tutorials-intermediate-tight-layout-guide-py)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Axis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Axes contains two or three Axis objects (be aware of the difference between **Axes** and **Axis**) which take care of things like the range of numbers that are displayed in the plot, the markings known as 'ticks' that appear along a axis the help you know the value of numbers, and the labels (the data limits can also be controlled via set via the `set_xlim()` and `set_ylim()` Axes methods).  To understand the axis it can be helpful to actually plot some data. \n",
    "\n",
    "Let's start with some interesting oscillatory patterns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "x1 = np.linspace(0.0, 5.0, 50)  # first use linspace to create the xvalues\n",
    "x2 = np.linspace(0.0, 2.0, 50) \n",
    "y1 = np.cos(2 * np.pi * x1) * np.exp(-x1) # next use the cosine function to create a dampened\n",
    "y2 = np.cos(2 * np.pi * x2) # and un-dampened oscillatory function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create two subplots sharing y axis\n",
    "fig, (ax1, ax2) = plt.subplots(2, sharey=True)\n",
    "\n",
    "ax1.plot(x1, y1, 'ko-')\n",
    "ax1.set(title='A tale of 2 subplots', ylabel='Damped oscillation')\n",
    "\n",
    "ax2.plot(x2, y2, 'r.-')\n",
    "ax2.set(xlabel='time (s)', ylabel='Undamped')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Very cool!  Ok now what if we repeat the above but adjust the x range (meaning the scale of where the x-axes goes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create two subplots sharing y axis\n",
    "fig, (ax1, ax2) = plt.subplots(2, sharey=True)\n",
    "\n",
    "ax1.plot(x1, y1, 'ko-')\n",
    "ax1.set(title='A tale of 2 subplots', ylabel='Damped oscillation')\n",
    "ax1.set_xlim(0,10)  # <---- THIS IS THE NEW LINE\n",
    "\n",
    "ax2.plot(x2, y2, 'r.-')\n",
    "ax2.set(xlabel='time (s)', ylabel='Undamped')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice how the plot axis for the first subplot now ranges from 0 to 10.  Since we intially generated x values that only go from 0 to 10 the data stops about 1/2 way into the plot.  Another thing you can do is adjust how many ticks appear on the figure.  For example, we might find the measumrents of time in the second panel down to the 0.25 second to be too many.  Let's space things out:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create two subplots sharing y axis\n",
    "fig, (ax1, ax2) = plt.subplots(2, sharey=True)\n",
    "\n",
    "ax1.plot(x1, y1, 'ko-')\n",
    "ax1.set(title='A tale of 2 subplots', ylabel='Damped oscillation')\n",
    "\n",
    "\n",
    "ax2.plot(x2, y2, 'r.-')\n",
    "ax2.set(xlabel='time (s)', ylabel='Undamped')\n",
    "ax2.set_xticks(np.arange(0,2.001, 0.5))  # <---- THIS IS THE NEW LINE\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice we now have tick marks only on each 0.5 second interval.  You can do the same thing by calling `set_yticks()` to change the tick frequency on the y-axis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are a few other details about matplotlib that are useful to know about such as legends, etc... but for now this should help get you oriented to the main things."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploring common plot types through seaborn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now have a general sense of how to control some basic aspects of a plot.  However, it feels like a lot of work.  We have to create axes, adjust axis, add tick marks, adjust the colors of plots, etc...  This seems like it would be a lot of hassle (and it is!).  However, luckily there are some pacakges for python that make common types of plots very easy to deal with.  One of the best libraries for this is [seaborn](https://seaborn.pydata.org).  From the seaborn website:\n",
    "\n",
    "> Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.\n",
    "\n",
    "\n",
    "```{figure} ./images/logo-wide-lightbg.svg\n",
    ":width: 350px\n",
    ":name: fig:seaborn\n",
    "\n",
    "The Seaborn Library logo.\n",
    "```\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before reading further I encourage you too check out the seaborn [gallery](https://seaborn.pydata.org/examples/index.html) which shows off some of the types of figures possible with seaborn.  The thing to note is the wide range of plots but also the nice, professional looking color schemes, etc...  Seaborn provides this for you so you don't have to do all this extra work.  If you click on an example in the seaborn gallery it shows you the code that was used to generate the plot.  In almost all cases even pretty complex plots take less than a 1/2 page of code.\n",
    "\n",
    "Seaborn itself has an extensive and very helpful [tutorial](https://seaborn.pydata.org/tutorial.html).  However, in this chapter we are also aiming to introduce students to the basic types of plots for different types of data and so we will step through some of the same material talking about the advantage of a particular plot type for visualizing a particular type of question."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to import seaborn we usually use the following command:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set(style=\"darkgrid\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you are following along with these examples you should make sure to perform this import first."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure-level and axes-level functions in seaborn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seaborn provides a number of high-level functions for creating plots.  For example here is a quick example of a scatterplot (described more below):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tips = sns.load_dataset(\"tips\")\n",
    "sns.relplot(x=\"total_bill\", y=\"tip\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This function (`relplot()`) is known as a **figure** level function because it creates a underlying matplotlib figure and the relevant axes and then shows the figure all in one step.\n",
    "\n",
    "Alternatively there are axes-level functions.  Sometimes these do roughly the same thing but instead will display a plot into an already created axes and figure.  For example, consider the following example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uXYzj2AA4js3SpYubuUbKkZzcaQTTB06LtBDSfKlMHzitUWYljRgxkmuvvYFf/vLnXH75VKZPn4brujz00BP07duf6dMv5tprryQuLp78/L0AjBx5Mq+99jJz5352zNdvSRwcCmuKapUXVhW3icCg9mNQjmjmzH+wYME8HMdG1w3GjZvAVVdd29zVanQtcYFba96X4Ifa2n4MhqGxqXITTy59IVKmazp/nfgHqPEe4cjYaxUL3JTWZfLkiyJPQJqmMWXK1GaukaI0P9t26ZfWh5tHXkWP1C4cl9WPB0+7mxRf60+HAWrwWalDamoaY8aMZ968zxkzZpwaeFaU/dygxvCMYRyfeRwCge548BpeINTcVTtmKjAodZo8+SLy8nar1oKi/IBtuYj9t1GHtrNOQwUGpU6pqWnce+/vm7saiqLEiBpjUBRFUaKowKAoiqJEUV1JiqLU2xdffMbMma/gOA5Supx77iSmT7+6uaulNDIVGBRFqZejSbuttE6qK0lR2piKZUvY/su72Xz9T9j+y7upWLakUc77/bTbcDDtds+evbn44smRVBmrV6/kttvC2ZNvu+1Gnn32L1x//Y+59NIL1cr5VkK1GBSlDalYtoR9r72CNE0A7JJi9r32CgDJo049pnMfLu12167djnicZdm8+OKrzJs3jxde+Ds5OaOPqR5K01MtBkVpQ4pmvRMJCgdI06Ro1juNcv5Dpd2eP3/uEY855ZQcAHr37kNlZcURX6u0DKrFoChtiF1S3KDyhjhc2u0PPngPIcKb1QCRpIsHeL3h3EHff43SsqkWg1KnsrJSHnnkQcrLG2ezF6XpGOkZDSpviMOl3e7XbwApKans2LEdgIUL5x/ztZTm1S4Dg7rRNYzawa31yJw6DeGNzu4pvF4yp0475nMfLu32NdfcwHXX3chf/vIE119/NYmJrS+RnNdr4PUaiBaYMVszQMTZBD1ViDgbzWj6Vle7TLs9c+Y/mDfvcyZMOKNNppBuTGVlpfzqVz/Hsiw8Hi+PPfZ0m0yk15bSblcsW0LRrHewS4ox0jPInDrtmAeej1VLTbut6QJbCj5b8R2243LWyT3w6eA6R3ePycpKorCwstHqpxuC3aHdPL7o74QcE6/u4e5Tb6J7fA9cq351PJrvdrsbY1BbVTbMoXZwU8G0ZUsedWqzB4LWwpaC25+cR00wPC4yZ+EO/nr3BLwCWsIjs2OY/G3By4Sc8IQC07F45suXeeTM34DlqePoo9fuupLUVpUNo3ZwU9oqr1dnwZq8SFAACFkOHy7egcfTMp6ZXelGbR8KUGlW48im3S613QUGdaNrmJyc0WiaDoCm6WoOutLiiJY4MNBINHR6pnaNKuuW0hm9iTt72l1gyMkZja6HP1RdN9SNrg6TJ1+ElOG+YSml2pMhxlrZEOBR0XARlolwbGjAk7DwOYQ81exz9iDibHSjYQHCNB3GndCFeP/Bm6zPozNxdC8syz7CkbGj2+ExhSEdBuLRPQzK6scvTr0Z3W7a7UNbRnsphiZPvohFi+bjOGqryvo6MP+8DT+YtUiG4aW6uoKEhOQ2+1SsuQ6BvDyk4yCRmF4Dn7fuvnPhc3hn0wd8vj3c4o8z/Dx4+j0k6Sk4DRg4NoTkr3dNiAw+n31KD7wauE3bU1NvjiMxpJ9bRvwYqbkIV0NYBo7btJsCtbvAoLaqbJg5c2ZHbkpCiJgPPi9evIBFiw49L/7AdOMj/Q3HjBnP6NHjmqRuTS0tLYvS0kKqqlr/tGpN03APcTNzKitxD6zUdiVuQQF9Ro7EqWPwNySDkaAAELCDvLLmLX464ifg6PWul+tINCTn5/QEwuk7WkpQOMB1JZg6oCMBSdO3IttdYAC1VWVDhMdkwv9SHMdh6dLFLWZWUnl5OXDkwNCa6bpBZmZ2c1ejURxqGqdfmmx76WUCO3ZGlbt9+yDSOhy2G00IQUWoqlZ5UXUxLi6C+geGA0yzZXQdtRTtMjCorSrrLydnNAsWzMNx7GYZkxk9etxhn/gfffSPAPzqV/fFskpKI3E9frJOn0D1S69EyjSvl/gePag6wlolKSVZ8RnEe+KosQKR8rE9TsEjvdgxeKJu69rd4LPSMJMnX4SmhbuS1JiM0phM2yVt9Bi6X3Ul/s7ZJB8/mOMffYiQVvfAqmZ5+OPp9zC043F0SszikkGTOLPXWOx6LvpSjqxdthiU+lNjMkpTqnYNks84i7SxY5GahqX7cJy6B1YdWxKvJXPz8KtxccMthYAKCo1FBQalTmpMRmlKpi1B84V/qEdQOODAoKxAV91HjUwFBqVOakxGUdoXNcagKIqiRGmWwDB37lymTp3Kueeey5/+9KfmqIKiKO2QYWj4dInHo56JjyTmn05ubi73338/zz77LHPmzGH9+vXMn6829lAUpWklajbBFUvJe/7v1CxeQKJmq9X8hxHzMYZPP/2UiRMn0qlTJwCeeuopfD5frKuhNEBZWSnPPfc3brnldjUrSWlxhADhkUjdQbpgON5aez/4NZfd//oXBZ9/AUDJsuWUr/uarjfcQFANtdYS8xbDrl27cByH6667jilTpvD666+TkpIS0zqoHdwaRu3gpsSargsMo34rmLU4hzc3vccdH9/PHxc+xe5QLsITPUtJdywKvojumShZ9iW6o1Y8H0rMQ6XjOKxcuZKZM2cSHx/PrbfeyuzZs5k6tX5TIRtjl6233prJli2b+PTTD7jllluO+XxtWUlJCYsXL0BKyeLFC7jmmqtJS0tr7moB4PGEbxxZWa1vK8lDae4d5Jpaff9OZZUhduwpJ7+4mhEDOpCa5MPnPfStynJs3vpmDl/sWAJAflUhDy18hmcm/ZHM1IPf01CJhWYYB/MyAULX0Q2NrIzG/f60he9jzANDZmYmOTk5pKenA3DGGWewbt26egeGY93as6yslM8++wwpJZ9++hlnnXW+6h45gpkzZ0YWHDmOy8svv9ZiciVZVjiHU2NspdgSt/ZsS+q95aWh88Q/V7F+ZwkAuiZ4+NbRdEzxH3Lhm/RarMhbF1XmuA65ZXsg4Il8nj7doPPFU9n9+huR13U6fyIhqVPRiFtxNvbWno3haL7bMe9KOu2001i0aBEVFRU4jsPChQsZPHhwzK6vdnBrGLWxkRIrQkBZVSgSFAAcV/Lqhxs4XCZtHYPuqV1qlWclZEYF2ZAjyDjjTI5/9GG6XXE5g2f8kY5TphCSDU+41x7EPDAMGzaM66+/nunTpzNx4kQ6d+7MtGnTYnZ9daNrGLWxkRIrQghCodo5r6sD1mFTTUtLY/qQC+mQkBk5x9TjzsNH7QktAWlgZ3Um+eyJONndqZFNt2dya9csw/EXX3wxF198cXNcutmzhbY2amMjpan5hIPHtXCDFr1T/Qzpk8HX24ojv79gXG88uoZ9iI0SpJR4rDjuH38Xpmvi0Q00x0Cah37mdV2J29I2XGiB2t08LXWjaxiVRE9pSn5hU/rpp+S++Ra4Lv5OHfndH+7n7VXpbN9TzrmjetK3azK2dfibueO44Bh499/ONF3gI4SwLYRuYOoeTFctaGuIegeG8vJydF0nMbF1z5xQN7qGU0n0lKaihQLkvvHvyM/B/H1899o/mXbDDQTpgQa11iQciRCCOCvAxhkPUbPrOzSvl57XX0PCiSer8YQGqDOMbt++nWnTppGTk8PJJ5/MlVdeyZ49e2JRtyYzefJF9Os3QN3o6ulAEj0VRJXGpGmCUEFhrfKanTuRpolruw0KCgA+bHa99ho1u74DwDVNtv/9fzHsUKPUub2oMzD8+te/5pJLLmHt2rWsWbOGc845h9/+9rexqFuTUTc6RWl+riuJ69IZYUR3XKSdNBLXc3TZEIRjU7V5a3ShlIQKiyJ7lyt1qzMwBAIBLrvsMjweD16vl6uuuoqioqJY1E1RlDYupPk47ve/w9+pE8IwyDp9Ap2mTOEQk5PqxTW8pAwdElUmdB1/x8PvIa3UVucYQ7du3Vi9ejUjRowAYPPmzXTt2rXJK6YoSttnSYHRvTcD//gHhBDYmkG1PPqBYlMKul5+KWZJCWWrv8KTmkqfn96CqXlRe/nUX52BYd++fVx11VUMGDAAwzBYv349WVlZTJ48GYA5c+Y0eSUVRWm7bNvFFvu7jho2pFCLlFAtfHS/9af0kg4SsDz+8C5xSr3VGRh++ctfxqIeiqIojUJKGc6YKvbf3lRQaLDDBoZt27bRp08fEhISDvn7WKaxUBRFaWqGoaFrAseVDZ4N1dYcNjA89thjPP/881xyySVkZ2dHDdwEAgGWLl0akwoqilI/mhZOVe26DZ/m2ZJ5PBqWMNExcK1wd9GRhCcfiQYNNicaDlVl5ZhCQwBJqQlUWe13UdxhA8Ojjz5KWVkZffr0YebMmUgpEUJgWRbTp0+PZR0VRamDX9jI4mJKli0joXcfEgYOoAZPnTfRlk6Lc1mSt5IluSvpltKZqcedh276DplpVQiIw8KtqMAJBPB17EBA8+EcLgPffnGGpKza5plPdvHN1iJ6d0nljguPIzPVT8Bun1NcDxsY7r77bhYvXowQgpycnEi5ruucddZZMamcoih18xga1au+Ytvf/idSlnLCMHredhsBWm+iON0r+HjbF7y78RMANhdv55t9G7l//F3g1L51xWOx/S9/pXzd1wB40lIZ8ujDVOtxRwyQlhQ8/e4G1u8IZ3XduruMB/+5hsd/eirtdSrTYQPDSy+9BIQXuD388MMxq1BjWLx4AYsWHX4f6QM7tx1pgduYMeMZPXpco9etpTrSZ6Y+r5bNYwXY8n9vRJWVr1mLZpngaTmBQdNEVCpsIQRCcNg9KBzN5PMd0dmP91UXEXCCxImkqK4iTROE8vIiQQHAKi0jb9ZsOl42HdONvvb36+IgIkHhgMKyACHbxXOUi+IOLKb7YXfWDz+D+p8vfM5Y7ddRZydaawsK9VFeXk55eXlzV6PVUJ9XyyftQ2UebRnjDF7hEiosgp1biDcriRMOCcLCU7wXPT+XRGGh69G3IsPQQECyr3ZuNkMzKKgIIQwdXQ/fgDVNENpXUOu1wb35IEPsNnMRcTbC0Ag6kp0F1UhdQ9M1QJCdET3JJs5n4DV0jiYuCEOnoCJEYWW4jpomELqGq2nsLKjCIvxzfcULC19lMSJ3O4nCxNCbvnurTWZXHT163BGfXh999I8A/OpX98WqSi3ekT4z9Xm1bLbHT+epF7LrH69EyhL79wefv9l7QgxDw96+hZV/ehjccKDqfuV0hGGw65XXAPB1yGLwQ3+iav8eCkKA7Qnyyldv8aPjz+cvS/+Buz/Ije0+ihVfF/PCrE1kZyTw0C2nAg627ZJy/GCEYSDtg/s4Z47OoTxYwYyFf+WKwT+icFsm7y3YHq6brjHj5lPpmhnHPVeM4P4XllEVsPB5dO760VCqvviUrPHjqGlAd1xpRZDfPb+UvMIqALp2SOShW05l465SHnl1BQce+K+fMpjRQ7KRhxgr+b54LL574UVKln0JgB4fz/GPPYwbn9qkrYc2GRgUpT0xbUna6DHEdetK8bwFJPTrS3pODjXCW/cUnibmtQKsf/a5SFAAyP2/f3P8Qw9Gfg4VFFLw2eeknnc+puWiewTvbZ7Lij1rSfYn8uDpd7OrbDddk7qxZ4/Ds29sAGBvcTXz1+Rx5ogumKaD8BgM/PUvyXtnNnZVFR1OPw0jMYncin0AHJc+kBdfXh65ru24/H3WOu675mSyU7w8feMIgg54pU3Ju7PJmz+PtMGD0LI61+sm7PHoLFy3JxIUAHYXVFFWZfLsO+v4/ile/XADOUM6c6RnfyHALS+PBAUAp6aG716dSdebbyFE02WLVYFBUdqAGmmg9+xPp2v74yKospxmDwoQ7hc3S0qjyqTj1HpSDu7Zg9jfvJG47KsO52P7fPtiFuxazjl9x1OwLYs3/rs56rg9hVWR/nwTg2BhEemjTkH3+yldvZrknp15P28eutAIWbWfzovLA+H/MU32PfMXKjdFn98sKUHv0IX6NL00TZBXUHXI35VXRWd3tWwX23GP2BYRQmCWldYqN4uKEK4DoukCQ/udqKsobYzjuIQsF+sIm9rEmi10MsecGlUW16XI0ZckAAAgAElEQVQLVkVFVFnHc87hwNIL4eqc1Xts5HeWY7Hku5WcOiS7Vp//2af0iLzfkNRJOulkUkeeiK9TR3pefy3/CW5gU9F2HOniaEHSk/1Rx48f0RVDA8fro8NZZ0b9TvN6Sezb55BTYw/FshzOOqV7rXKvR+fkQZ2iynp1Tq5zrMB1JfHde6DHRdc564zTcbz+wxzVOPQHHnjggSa9QiMLBMxjfhBavHgBEJ5Jo9StpX5ejVkvIQTx8d5jPs+xaIzvdkvjCo2s4UPCCfKqqkg94QT63v5ThKYRyM3Fm5pKzxuux9ujJ9b+XdZcV5IWn0Sv9G4U1hSTndSBG0+cTqo/meEDOrK3qJr0ZD+3ThtKl8wE5Pf6aGw0LN0HKenYuoceWV0prC7Co3vokdaRS8eOpKQ8CEJwXk5PLhjbB9d2cF1JYueOxHXqiFlUTHzPHvT/xV1YcUm4sn6DvR6PQUqSn0G90tlbXENmShy3XTyMzBQfIwd1wnFdaoI2I4/ryG0XD0OXss6/t9R1Oo09ldC+fWg+L10unkra6NEEnfoPQB/Nd1vIVpaLtri46pgHXdRgasO01M+rMeulaYKMjObdnbAxvtstVUaqn+qScqThwZTh2USGHUJIie2Nq9XKEUIQb7gECaEJDY/rocYW4cFsN9yx49VFna0jTRNIw8HFwSN9uI5EagLHkXgNgf2D7iWPR8Mwg0hNw9a99VpBbugQLwJUrf0cXJukEydS4fpwXYFHO7gDnW5oWI7E0AXScev9EKBpAq+0EK6D44nDbOCq9qP5bqsxBkVRmpzm8RDUfPuzp0psW2LjAQEc4uaeICy2/fkv4XUJQtDhjNPofPl0auzwLUsAhxgyqMV1JZgaAg37QOpWV4a3DLVq35kty8X2GbiaTWHNHjokZKDZBq51+Cf0BC1I3ot3I0M1AFQs/w+db3iKSpnI9yZI4dguGuA2MKmf634vKWCMUp2owBBDauGdotTNY2gUL1h0cLGalBR8NpeMcWPRu/WuM8XFsdA9krXF3/Lcin8ikWhC466cG+ib1BfnEIHE69WpXr8kEhQApGNRsfJDfKMuJ2S2nPGehlCDzy2IWkimKKDhUrl+Q63yqo2bai2Ea2yOYfOPr95E7p+F5EqX/131Oo5uNug8rT3DkmoxxJBaeKcodXOFTvqoU6Lm7wOkjhiOdZRdKR5DQ3NtXN3AOkIflOO6hOzoqaUVocrDvt40HVKOO5XyxW/j7m81CMNL0siJVLag2WENpQKDoigtimU5JA0dSvaUyez7+BOEx6Db5ZehpWU0eHBeCEgQNiVLllG+ajXJQ4eQMXYs1dI45OCvjk7P1K7sLNsdKTu+wwCE1A67kqHajaPz9U9S9fU8cCwShp5OgHhaSEaSo6ICg6IoLU61a5B54VQ6TTkfEFi6l8BRPID7cMh9bSaF88Jje6WrVlPxzbd0v/lmAoe4/WmWh3tG38zr695lc/F2Bnfoz2WDp0DIiHQv/ZDtSModP96h55OSEkdRUWWrn3asAoOiKC1SyBWE8CEEyKPsldFdm8IFC6PKSlespOcNNmi1b3+uK9GCPq4afAmOsNGlgQzWb9Mf0wxPQWrtQQHU4LOiKEdB17WjHggWIpxcr67MpYYuSMTEW1pAglODX9hHPuAwtB+kHheGEUmjcShSSlxTIEIeXFO0iRt9Q6nAoChKvem6IMVr4tm3Dm/xJpK9FprWgFW4XpeAUcna0nVU6xUI36GbAh6vhmsEKQgWU+2T5H76MUUfftjg4GDpXrr+6JKosuwLJmNpLWefipZIdSUpilIvQkCiFmDPP36JWxPOdWSkZdPxigepMOu+0eoe+HLfV7z81b8jZZcPuZBxXXJwzYPBRdME1VTy4BdPUxosRxcalw85j4EbytGtEBj1v22ZriB1/ARSThhKxTfrSRo4AD0zi4BUz8RHoj4dRVHqxePRqFj5YSQoANilewntXBveWOcHNF1D6jpS16gOWDi6xf99/W7Ua97+9gNcLboVIA2bF1e/QWkwvKbHkS7/2vQhiWNOwaqoOGwXlKYJMHQqTYcq04X9m+QEMbDSOpI44QzsrM4EpHoerov6hBRFqRcNiVtVVqvcqS6r1WcvDJ33Fm1nzsLtuBLOOLEbV5zXn5AdvVDMcm0kMmpBmCtcdpfviXqdRFJh1ZCW0QXzMH3+Utf440tfsmNPOHD16ZLC7649GdxwkjzXbb3rCmJNtRgURakX04akkROjCzWD+IE54Zu718HwCHRdsLuwitnztmE7EteVfLriO9ZtLebX437KoKx+kcOHdhyIJqP3FdClwYjs46PKfIaPrMzOhMShs4R6PDpffpsfCQoA2/LKWbWhAI+n6fYtaKtUi0FRlHpxXYmdkEWnKx6kfOkshOEldeylmF4/C3OXsGrv1wzI6M3kAWexdktRreNXbijg8j5dOavPOKYMPIvNRTs4q884ZMDg+xvhSEvwo8FTCDomK/PW0impAzefeAW69GMdZoGbpomooHDAzvwKcgZ3bLTPoL1otsDw6KOPUlpayiOPPNJcVVCUdsEwNLxWEIGLKzRM3V+vzWd0r8DRLBCgOTquKQjaOkZKL/zn3YXjQjWSqsoCVu/9mvFdx9IvvQ9VNS5nndyd4vIAX6zazekjuzFhRFcyUv3sKt1OVlI620u/Y2KvM7BDEp800aSDFBqhA3UL6lw9+BKuG3IJRshCSIFtO+Dx4CGEgYNEYIo4QqaDZTmcMbI7nyzbFfUeThvRtVE3LvJpLp793V+W5sV0W3tWpENrlsCwdOlSZs+ezYQJE5rj8orSbui6wCgrZNPjTxLIyyOhVy/6/eIuQnEpRwwOwuuwLH81//5mDqZjMqFnDpcMmowb1LGBp/9vDeu2FpGR4uf2C47j7qE/IT8g+Pcn21m4Jo84n8EV5wzk9JHd2J5XzqOvrSBoOowd3plLzk7mu9I8Tup0AnGhIFueeJKqrdvwZ2fT7547EekdsR2Jz3KpWrmCXa/NxAkEyRo/jh5XX0Hxx88Q3LEWPSmdzPNvw5/ei6AFmSk+7rniRN74dBNCCC47qz/pST7ceu7AVpcEzSZ/9rvkf/QxQtfpMu0i0s84s00OZsd8jKGsrIynnnqKm2++OdaXVpR2x++E2Pinhwjk5QFQvWMHmx97Ap8TPOwxQggqnApeWfMWATuII10+37GYFXvXonk0/jHnW9ZtDXcVFZcHmfH6WkwH1mwuZP7q3biupDpg8X//3UhKoo+XP1hPddDGcSXzVuWx/JsiBnXojz9ks+XJp6naug2A4N69bHzwT/icIEKAqK5i+9+fx6muAdel8It5FM6dizB8ADiVJRS8+TBeYYUr7rgM7Z3GA9efwgPXncLQXmm19pY+WoahUbVhPXvnfIC0bdxQiNzX38DO39ugdRytRcxD3e9//3vuvPNO9u7dG+tLKy3Q66+/Rm7urrpfeAjffRc+7kBW2obq1q0H06dffVTHthbSsjCLiqPKanbuQrjuYR8LDUNjQ/6WWuWr9qxjeMaJkaBwgGm71JiSrzYVRpV37ZDEN9tqjzV8tbGYWwb1xS0ppWpz9HWs8gqkaaLHx1G5cWOtY8vWfE32GYMIbFkefn+OhVNVivB1REqwLXf/25L12sinvnQNCr5cXqu8dNUq0i/sFUmH0VbENDC89dZbZGdnk5OTw6xZs47qHI2x/eKBWQpZWUnHfK7G1B7rlZ+/mx2bN5KpN3zmiM8N/8uv3Fb7JlaXIsfB49Fb1GfdFFuLmqU2RnIydsXBgVl/djaG10NW2uHfe3+nd62ywR36E+c36Nc1lVWbCiLluiaI82kM7JnG198LBPnF1fTvnlbrPMf3TsdZuZpAXBzxPbpTs+u7g+dKiMcT5ychLYGqfn1rHZvYvy922femsgoNIzGVzJSm/zsGhg2laMGiqLLUIceTkhIXVdaSvlNHK6aB4cMPP6SwsJALLriA8vJyampqeOihh/jNb35T73M0xr64BwajCgsPn2e9ObTHelmWQ6auc0HS4XetawrvVZZhWU7kPbXVPZ89usGAX93Dpkcex66sxJOWSv977qJKenCO8PdM86cxqd8ZfLT1C1zpMrTjQMZ0PxkzYHHz1CE88OKX5BVW4ffq3DSxP4YMDziv31HCt9uL0TXBmSd1Jz3Zz7TT+jJ7/jZcVzKkTwYTesWz495XiO/WlT4338imPz+FWVSMnpBA/1/cTY30UFlcRXxaOgN+/Su+m/kvArt3kzx4ENmTJlIwawYAwuMj/ZwbMaWX8hj8m0kePoL0USdTsmz5/u1GT8fbvUfUv4usrKQW9++3xe/5/PLLL0f+f9asWSxfvrxBQUFRlIaxHPB07s6Qp55AWhbC4yWk++qclSSDOuf3OYuJ/U/HlRJd6siAgZSSBK/OjBtPwXQkHl3gFw4hr+SttW9yztlDuSEphyRfPB5NwzYdzj+1J5PH9sa2HGrWfkXuH/+AtG2qd+zErKzi+EcfxjVNhMeDqXtBSvyBCnLfnoUTCND3Z7fiSU/HETohj5/MS36HcEyEbmDhI2DF5rOslgbdrr+BHtdeA0LgaAY1bXDgGdQ6BkVp8ywHLHzgCQ/aUs89k11TAzQ0DqwykMRrNuULF5L/0ccYiYn0uOYnhLpm8eiiZ9lZtptFuSsA6JXWnV+MvglMD9JxyUxPoKy4grhu2VR16YKRlEjHc88hrm9fqlwDPPsXrjmQ6AZYc+c9uGZ4lXTJl8sZ8vgjWOmdcEMOITyABxppDEEI8EsLzbHAlUiPl4Dw1kq1LSUE8MCBBHxtOOtqswWGqVOnMnXq1Oa6vKIoDeTx6FR9tYodL7wUKfv2t/fR59VnonY8A9hR+h2266BzMLme5Qr0zGx63nUnwnVxvHHU/GCrTp/PoGT+ikhQAEBK9r43h+zrrifUBLuixWOx84UXKN0/uJw06Dj67e9ua69USgxFUepFt0IUfv5FVJm0bTQXEr0JUeVJvkR0rfaEAsdxCeIhoPkwvxcUhADN75Af2ouM99U6zkhKRNa1gcNR0HWNmq1bI0EBoHL9BkqWLmvXqTRUYFAUpV6kbuDr+L30EkLgz+5EXAjuHn0jaf5UOiZm4dU83DTyCnx48fkOboojhMDj0dA0EZn7r2ki/Huvw8tr/819c59A9u+Br0OHyGX0+Hiyp0zGshu/70bXNaq21J7VVrVpE4ff5bnxff8zaQnUGIOiKBGaJvBrFrpwcKRO0PVEZkqZLnS5ZBqlq1YR37UrPW+4FisxjYJqi456Ko8PvgGztISEXj2wfR7KPvwvVmUFHc8+m1CJia+0BKusjPhuXXFqAhipyQR0B6RDnObn24LNxHvi+LZ8J2P+dD9OVTVWYRHx3brhxCcjzcbPjmrbDuknn0Te29HT5zPHjqnvUMwx0TRBnDQx9+YjbZv4rl0IaPVLWdKUVGBQFAUI36QStRpKPnqOYO4GfNl9yZh0K9V6Mo7jIiUEvQkMefIJCAQI6D7+9/31TBicQc0nb1O+cmX4PH4/g+77DQWffU4wP5/kAf3J//Rzyr9aA4AeF8dx9/2Gna+8StIN03l+42xuGjqN+3JuxLA1qt+cw9dfvow/uxN9br2JUEkJxKcA4cV34RTajXPXNgwN1zTp+ZOryZv9HtJx6HTeOXjT0nBj8AQfL002PPAggdxcALyZGRz/yMNUcegssrGiupIUpZ3SDQF+C+IshM8hTjcpmv0EgR1rkbZJMHc9BW89TJw4mD7DcSS20AlJjYoaizVbi+ka50aCAoAbDLL77Vl0OOM0PCnJaF5vJCgAOIEAe959n6T+/XE2bEMIwYxlL5AVl0HN7I8pWbAYNxSiZucu1t//IHHZnXCEje0LsLJ4Nfn2XjS/U+ee0fUhhKB46TKqtm6lz09vpt+dd2CWlFK0ZNkR94VuDIahUb5ubSQoAJhFxRR8+ileT/PemlWLQVHaIc0j2VXzHc+tmElpsJwTOg3i5pFXYJXui3qdVZyHJi343hOsKQy27asmzmMQ7/dEraqOvKakFCMpCT0hAau8vPbvS0tJGTIYs7iEpC4JbCneAaZNxcqvol7nBII4gSB5RiEPLfxbZArpyM7DuHbYZRA6tgFi03ToeM7ZrP353RQtWrL/w9E44a9PEWjiNBeaJjD3FdYqDxUU0NyjDarFoCjtkGvYPLb475HtM9fkr+eNb+YQd8r5Ua/T/AmgHXx+9Hh0PluRy39W7aNjVhJB00bvmI2eEB91XOa4MZR9tYZg/j7iu3VDj/NH/37sGEq/WkviKSeysWgbHs1AeDzEd+8WXVEhCCX7mbn2nah1BSv3rMWUoWP+HKSUOAkpDHn0YdJPHkn6KScz5PFHsOOTkE08xmBZDhljRoMWfRvueM45WLEY4DiCVttiaKnJ11S9GlYvJfaEEBTVlOD8YKvLdfs28qOxP0MseRdpBRGGl8zJt2Npcfi8AseVuFKydXc5UkLIkTx522jmrtrNmX/4I0VvvoFZXEyHM08nY9QpAPiyO2Il+Oj30B/If/0t7NJSssaPI65rF0SvLny0byUhx+TmE6+gets2ul1+KTW7d2OVloGm0ePqK3GFoNqqqfU+TMeiMVYamFJDz+xEl5tvBcBCb/TUJIciJdhxiQye8SC7X38D17LocvE0tKyOMbn+kbTawJCbu4tNW7ai+xueY8d1ws3Prbm1Mz/WxQnW3vP2h/XauXUjnRIb/tHG71/KGczf2uBj86uO3OzNzd3F5u2b0FMaPqjl6uEbyLbiHQ0+1ik3636RElNSStLj0hAI5PemZPZJ74luxNP5xr8gzQDCG4eUOuWrVlC+Zh1pJ40kaegQrpk8iCXr9vLWgl2cMrgTp43sjjQ0AudfTmlpNYsLQpxbo9HhnPOQHofiQCm2Xyfjpqsoqy4l3wnRP6MHmlfjzMokzu91Cu6mFSRkDyL/84X0//ntaH4/3vR0TM2DIz2c23cC/1o3O1LXDgmZJHoTkYH6v2+vV0dKDrlxj+NInEgHSuxuyqbU0Dt1p8cdPwcpsT0+gnbzzkiCVhwYAHR/KvE9zojpNWt2fV7nazolGlwzND0GtTno5XUldb5GT/GSMq5zDGpzUPmCPXW/SIk5zTW4ceR0Xv7qTUzHomtyNlcPm4ZrGlS4Oggffttmz6uvUrRgIQCh8jLkwEH89Y2v+XZH+Pv2xapcfjJpEDUhizc/O7geYPmGAp64YwxloUJKg+VUmzUszV3NxP6nsWjnOgZm9qTs/x7Gzt9B1f4bcSjhc7LOuI1vfvcg/i6dGXD//YSkDqbLmK6nkOpPYcGuZXRP7sykAWeghTw49ciL4dEkXitA0ccL0Hx+MkbnhKeENvNT+QGO4+JggABaQFCAVh4YFEU5OtLUOCFjKE+dOwjHddAx0C0vjnvwxmS4NkULw2mmk0ecgLhqMmVmMBIUDpg1byt3XDo8qqykIohpOSzLW82CXctJ9iXyo8Hn823BZi4bcgG6LTHzt0cd41SXofvDLdqs8eNwvH7Yv6hNhjSGdxpMmj+ZneW7WZ33NSd1GYYI6LXGAg4spJNIHFviCVay9ud3RxL1uaEgHU6fgIvA1jyEXDXU+kMqMChKO+VaAixPJJ/R95++vToIBwY/cB/Fy77EN2EU96+byS9OuqvWeTRNYOjR82iSE7zYmMzZ9BkA5cEKnlr6Ig+efjcCgSvBk9kVq+hgjiUtLhGkoOvll5J55plUf2+ls+Z1eHbFv1i995tI2caibVx1/DTs0MEbu+aBoKji3a3z0BCc1+80ar5cE8m9NODun1O6eg2rb74NhCB78iQ6TDq/zWZJPVrq01CaVXl5GSW2zXuVRx67aWxFto1bHttrthZxwqZi6TIKCvchEuNJ6NEd0bkjg4v7k5Sg8eyvxrB2QxHvLNhJUVmQy87qT/csLxNGdOHb7cWcPrI7Y4d3oczcy6S+Z7OrYhf9MnrRPaUz6Vo8fuEnJCDrwrvY9+ZDOBVFaHFJdJh6NyR1IvWcblT/YMjMEXZUUABYU7Ceq/SpaF6JV/MgnBAVWohffDID2w2fYO6OxTw+7hdor/qJ79YVq7KSff/9NHKOPbPeJWXoUPQefeu12tgwNFzNwdAMHNcGNFwrPG4jhMAxTXyaiy2MZl+9fCxUYFAUJULTBG5ZGXJYf+bmFlJsFnBWl570MXwM7XQc/1jzBt1TOnPeiacxdlg6VQEdCvPJ/8tfufKCKQRPH8Wbn23mnx9tYNLoXpyYNpoTuw7mP5s/o6i6mB59MxDbN5PQ/XjMhCwSLv4DOCZoHqzEFGzLxT1ETiSBQNf0yEyqfhm9+MnwS3hr/X8oqinl7F459DOS+e/eryJBAcIzlxbtW8uQ4SegJyRQsf4Q24WuWkVmn/513sg1n8PWiu1UWzUk+xL579YFJHkTuei4c4mX8XhrKtn+3DtY5RVkT5mMv0tXgq20JdI6a620GSkpqWhFhc2yg1tSSmyv2RoYhk4oycPvFz9NpVkNQIeEDLbW7GX2ho8B+HrfRtbt28g9OdeTqZusnhHeUS0ltQN3Pr0Aa/8A6pff5vP47WN4evkrFNeUhsvy1vDnsXdQ8vH/knDmjdz6t1UEQuEb+ekju3HFOQMROoBEkwdTX3hcjcm9J/Du1vDkj6tOmMYjC5+lMlQFwJr8b3lw7M/wiNrjBR7dQ8/rrqFo0WI8SYkUfjEv6vcpw4Zh1zHoaxga35Rs5N2NH3PJ4Ek8svDZyO++zPuKJ8+5j02/uBe7Klyf0pWrOO4P96N379MqWw4qMDSy8vIySqvses0Sakz5VTZpqmtEOUZSSnaHiiNBASCn+4k8sfj5qNfllu+hxjHxlxWQMngQUkqWbiyOBIXwueA/i3ZyQt8hfL5jARB+gt9cvpsBoyYS8Fg88vOR/HdJHjvzajh9ZDceeHEZufsqOa5nOndNH4FHA9eV2LaHif1O58SsQeyuzKcmVBMJCge8sfETbhlxKf/dsZiAHU7jkeCNZ3T3k6gKekk+/Sw8jknWhHEUzl8IQtDxrDPx9+pFTR03b1sz+XDL54zsPJR5O5ZG/S5oh/hm7wbSsjtRteXgVPO9771P95/ehkPrS9+tAoOiKBGO45Lgj94fOGSHiPfEUW1GLzLzaAYaOk4wCBKS/LVvgEkJHgLOwRXKKb4k+nTsz8NL/pe8inwMzeDigVM4e9Rw7n9uJWWV4ddu2FnCk6+v5hdXjADCLQdpeumc2IXuyV3ItYprXcuj62i7N/PYmNtYXrINIXRO6To8PNtKSkKmQwid7KuuptsV0wGBrRnUyLpv3AKNeE8cQTtEvDeu1u8TvfE4weiV2EZiIlLToPGTwjY5FRgaWUpKKr5AUbOsY/CrrhHlGLmuJCsuixM6DmbNvm8B+O/WBVw9bBpPLnkhsiDu1G4j8QsDb3IWFRvC/fYnXJdEh7Q4CkrDq84S4zxMHtub+xe9Hjn/5AFn8u9v/0NeRT4AtmvzxvpZjDr3BKpqojdv3rCzhO9nypNSEnTCN9p0fzr90nuxpSS86NLQDC7rewbB95/D33cEZ466mJCjYwUcnB8sWAtKA8T+W189lzJojsH0IRfxxOLnuOPU61iRt46QHQ4EXZI70SejFzu/NzFL8/noeuklBOXBjVFbExUYFEUBQNM1pKZRUlHD1UOu4LoTNDaUbmBQVl98QufJc+9j3b6NdE3OpnNSFglSQ/oMjn/oQWp27iIlzuCxW3LYtLuCkOUyuE8GHyzaxt0n3cHmkq34DT/HdezJf7ctrHXt4kAJWWlx7C062IXVvWMS0pWHTigXMrgr50a+q8ijJFDK0A4D8BTk4pv8M2RiJlVBaMxHdcdxSTFSeeC0u9hdvpfHz/4tGwq3kuhNoHdqd7A8DLz/9wR27MAsLydl6BCCur/ZU1scLRUYFEVB0wQh16EsWMSH2z8hYAc4s+dpHJ85CBkQ2Jog0fAztnMOUoJruziVpay//0FAEpedjZ6YSNKwExjSOx3bdqkybWbP2857C3bQt2sqplXF9v55DOs8iE+3LYhcWxcanRKzuOGCFB7/Z3gwOi3Jx937xxgONS4spUQGdHr4e9AzridOyEWmD6TGdXGtprkZS1ug2T56J/RGWpIT0oYiJTgBFxeXKjxknXQipaXVVNku9ViU3WKpwNBOlJeXYZeFYp6iwi4LUW6oQfGWTgpByA3w0JI/YzrhLp2v923kt+Nup7u/O7btYn4vDXW8sNn+P3/HLArnGzOLiqnYsJHhz/0PQcJ7Nvt9OnE+g0DIZvN34VlJ6cl+bj/jPEoDZaza8zWpccncdOKVCMugdycfz9wzAct28Ro6OrLO2UKOIznQVWPbsenMP1inQweguurcGqjAoCjthEeT+FwTNxRC+HyYuo8D+eQ0TfBt/sZIUDjgoy1zufGEq8D+QYeOdKneEZ1UUdo2VlU1epoPxwJ0k59fcTx/f2sDZZUhemYnc/mknggE1w6dzjXDXZBgOF5sy0XiIgCvAByn3h1B4WEIEZWWWzk2KjC0EykpqRTZpc2SRC9FDYo3O48ucXduZ+1jj+MEghiJiQz83W8wOnbBdiS6JuiQWPvvlOJLQhdarQFcR9NJHjqU0i+XR8r0uDhEfDyu4YClI4D1gaX8/JoR+PU4ioJFfFmwmPMTz0KaGge2g7H397n4hYPhWkjA0QxCGEfcE0HTBK6mUVoZwnZcslLj0KRslesGWhoVGBSlHfA6Jl//+SmcQHh+vzczA7e6lASRhun1YdoO/dK70y2lM7nl4e7GeE8ck7uNwRcKIb1xWKaDEIL/b+++w6Mq04ePf0+Zkt4IoSUhhEBApPdOECEgICCCrnFXbCjKqr9X2rL2FVwbCiprW/f3vqzYKMICAgLSXFCk95ZASCGkT5Ipp7x/BAaHAEoJKTyf6/Iyc+aU+wwz5z7lee7H36KhmAZXebgAACAASURBVBpNHn+Q4juHc/RvM7AEBdFg/GOcNp3YdQ0/SyCm28KdiQNZuH85R/JTaVvvFoY2G4BRVrETmr+kkfnll2SvWg2mSUT3bsQ+OA7HZXoOm4rMK59u5dip8sGG6kX4M+OxHpXw6V1/stXEUMpvzcm6iuGu6jHbfInEIAg3A03z9sr1bxxLsz8/RN7KuTh+MlDu+Cv6yRMguZjY5QFOFmVQ6nGSWCceW0EZ7uJcTHsASmg4AZKTvGXvU3b0F2R7AIF9/0Sr994lL7cYd4iNuds+YkLnFA7k7aRNnVvBqTK6+TAMVSsfLU03UBXV5z68osi4jqeS/d1K77TcTZsJbd8Oe8euFx0/QVVldhzN9SYFgKzcUlb/dJLkLtG43dW384Bs11l2ZA3Lj6zFxGRgfB+GJtyO4aw+VV6rTySCIFQaU7Fgi4oCIGbMCPJWzsWTewqlZRKqYZD92aeURAXx7Mq/8cWepaw6up5nV/6NX0qO48zK5MSc2Vg0J8VbFlN29BcADGcJRSvew3A5OKFk8crG1xnTdAAlRQX84+d5uHCWj2ssuZi95Z88tnQaMzfPocDMQ/5VnzJFkSncs6dCzIU7dyJLF7+XJMsSmTklFaan5zi4RAPXakFRZNKK0llyaBWaoaEbOssOr+FYYSqqWn0Ox9UnEkEQKo1LtdHir9MIbBqPrU44ntxTAJhWfwxHMfZ69dhfkApAtiOHtIJTmKbJjrzDFGVm4Dh0GBUPztRdFdZdlpVGYmgCL7S4nzo7T3Ag9ygAqQUnMVWdD37+X/aePgSUl9J4df1sTOv5Fk66rhParl2F9YZ17sylHhd4PAY92jT4df83AAZ2icXQq+/VgqrK/JK5u8L0bRm7UZTqcziuPpEIglBpdN3EFRBG/JTJWCProobVwxLREFt4PQIiQnFmZ5MQHF1huZZBMbgOHycgLg7NVLE1Sqwwj71uNHpeDqdmvE1I5460imnNpJ6P0TS8MaZseJPCOYWuYlz6+SFfdd3E2qAhje4ejWy1Iqkq9QYnE9iy5SWbfpqmSYBN4aWHu9E8JowmDUOYlNKR+uF+Z5uwVk+6btA6qkWF6a2jWlSrh+biGYMg3CR03aAMK25TImr0VHLKZP72zWHuuy2C6JQUnNkOhjbpy7Lj69FNgw71W9EpoAmnTi2n8bOT0Cx+hPQYhTs7Fdepg0iqlYCe96L4BxGgWGj5+gyWZPzI4oMrCbIF8mC7MTQNjyM6pAFnSvJoVqcJDncJ6YWZWBWLT2ylpkrYoMFEDrgNAE2xUPIbI6uZukFs3QAm3dcBoLwzXDXvQ6BpBvFhjekX1511qeXF+HrHdqF5RFO0suoTu0gMgnCT0XWTIiWMGfO3cCK7mA++PcCz99xK/Xp+JHmaMbBFfyQkLIaEpdRD4ssv4bH7I8sGDt0fd+8J1AtWQFY4fkYjdU8u/lGnySzNZtGB74DzI7a9M/hFJnd+GLOomKKt21DCm1Gnz5/QdQsXjMWDy5BwSeWd435vr2FNM7xPFKp5TvAyyhTubj6Mu1oOARMkQ7loS62qVGMTQ2FhAbqzgNK072/odnVnAYWFNfZjEwQAdBNOZBczpk8Mya380HbNp/SQP9a2SXyw71va1r+VHg26oAfJrDu+mdTCdJLiukNJBM/N/dlnXdFRQfw5pRkrjq31mW5ikl2cQ5zDwu7J0+DseNKFMdE0f/45TMWGjkSZW8NmVVAovwq4GRi/6sdRHW98iSOcINyEZAlaxYdze6KFws+nc+7wJO/ZwKMpL/DM+ll0i2nPzA3ve/s17Mraz1+6TKuwrrAgG8WeYhqHNuJ4/kmf92LtdTgx9wNvUgAoPXESd1YWngaxTH1vIzkFZUgSDO8dz7CecVzyibNww9TYxBASEkpOkYZ/bP8but3StO9FT16hxlOBp+5qhbH+Q359zmq4StFPHqBxWDRuzeNNCgBlmpMcVwZdb63Hf3eXl822WRQeHHYLhdIphjYfwLH8k6QVpKNIMiNbJqOaCobbzYUMt5tF646SU1Beots0YdEPR7m9cwx25cqam8qyhKLIaJp+2Z7Swu9XYxODIAgVSRLIsuxt4SLLEpKEt6WOosjlA9obBgE2CyUWe8WVqFb8LX7YVCu31k0kzC+Ek4WZ3FInkQi/CB4fWYc/JieSU1RK/YhAbLJMmNkYi6IwpfvjuE0NVVaQdBVDUmk4agQHXpnhXb0lLBR7TDS7Vu8kOMBKaJCNjLN9EgxJQwlQMAwDxVDRXBXD+/U++ksePFnZlKamEtz6Vgx7IC4UFEVGksrHl6ippa+rUpUkhjlz5rB8+XIA+vTpw6RJk6oiDEGoXRSZYqfGyexCEhqFEqAYaCeOY2oaQfFxyLKBK+sYpsUPS1h9XIqN4G4jKT3wX0yt/KxeDamLpWECDzRpg6fUwoTW4zCPH4JOd/H56sPMWnWQVvFnGNOnMQmKE1VTMWQFo6yU0tQ0AuLisNj90GQLfoaL0tTDWCIjuOVvL5G94jusdSOpNygZl8WPCWNb4KKE7JIcmoQlEuJnJ7ssm8OZZ4gNbcSpwizaRiaiuc7XTJJsOiW6g/SiLOLDYsjfvpe0t+Z4P4LEV19Ciq3PobxUImzBhCuBBMhWyrCKBHEFbnhi2Lx5Mxs3bmThwoVIksRDDz3EqlWrGDBgwI0ORagmzug6i4uvvDR36dn71v7ylbfoOKPrBF3xUtWXpMj8Z3MqX68tH3NYkeHVBzsRnnuaop17CIiOJGPedIyy8rIY1qg4rIP/D3k2laiHZuE8vAVsgVhjW7HhcCELvt/JhLva8OOuDEZ0bsSsz3ew91j5cJqnchycOu3g4aYeAm0KnsICUj/9lzeWJo89Slinjuz6n0l4Csr/XUM7tCdq/APk4cRp8UPHzfqs71lzfFN5vJLM//R4lMUHvuPgmWPYFCtTek8gMz+D2MCGlOgKstVg+fG1fHugvHSGhMRTbe8jpGN7Cn/+Bb/oRuQFy7yw4gU8Z6vEto+6hfuCOxMR0xQHvk1khUu74YkhMjKSKVOmYLVaAYiPjycj4+rGCLjaVknG2YHCZfUil9G/Y5tQ54qXqw70QvdVjcdgOMt7ksoXGdP392yTiEu/Hx0de8XrPCf/RBoAUTFXvo6ga9x2dWMAC9aVJwV/u8qMcW3wy/gJM2cPDQYPoHjbf7xJAcCdfRz59HE8DZtSKNnxxPZl9tc7ODjvR+/Z+T+X7iO5W2MKDZX008U+29tzLBfrbW2xuYs5+t4HPu+lffa/BDVL8CYFgIJtv+C3sz0rgrIY22I4pmx4kwKAbhp8vnsxdzTrz8Ezx3Dpbr49sJIBcT3B5USyBGIoOksOrvIuY2Ly2cFv+cvQURT+/Ashg5L4v4eXe5MCwC/Ze7m7cRIlR46gNr+l2vdzqC5ueGJISEjw/p2amsqyZcuYP3/+714+IqJ8oPLmzROwWK78QAVw7NgxAJo0ibqKpaNo0qQJkZEXP9+0WBRSHRr/3JV3xWt2uMu/tIHWKz8DznJoJFiUS8Z1XT6vek2ufOF6XPbz+vOfJ1xVTABTp04FYMaMGb8xZ81w7rt9NbJySzh3p+T+/rH4bf+csoP/BcBaNxa9uOL30SzJB1NCkiG32MmB1Hyf9wuKXQT6WShyuAgLslPoOP8Q2d+ugseNpFR8uKyXlXGxRph6fiEB4f7YbVYKXcUV3i90FhNg9fd5HWELQcstoE6LemQ7ciqMuVDkcqD6ly8jBQdSWFJxvQ5PKf7FxdQJC6jwXmW41He9Jqmyh8+HDx/m0UcfZfLkyTRu3Ph3L5eb68AwTO68c+xVb/u1114G4JlnKja9+71ycip+AQHq1Wt00WqQv8fps2fAdepd+Zls47PbvlRc1fXzuhbnPufrsW5Zlq7pwHw9nPtuXw1FkWlcP5jUzCLaNAmh7Mct3vfKju8gtOudlB7Z5p0mKRbsjVtT4CnhTJ6LiOBAIkLs5BY6vfP07xTN7qNnGNGlPkM71WfOkiJMs/zh74O3x1O0agXWdm0IubUVhbvPF8EL69ge2WrziU9SFAI7tae9zYPhlPFT7ET6h5NTej5h9YrtxI6svd7XfeO6EVDswVInkpycYhS7SkxIQ04UnvLO0ye2C7LDSWi7toQE12FAVC8+2/GV9/0gawCRShDBrS7927ieIiODbsh2rsTVfLerJDFs27aNiRMnMm3aNIYMGVIVIVSae++9/6qXPXcAnjz5r9crHOEmIZsmz43rwtdrD6PIEpJq8T5QdmcdR3PkE3XXZAq3LEGy+eHXfQwe/wDCMSkxylv4vPpYD+avOsSpHAe92jYgMTacAMWgeOkCWrZqw0dT+pOe46BBiBXnti1oqkJgQjxB7VpT5MhHNwykUidhdRuiGRItnp/OqW8WIlutRI0dhREaTLRcPq6DYlh5vu8zfLN/GScLM+gW3YFu0R2Yt3MBzSKacFuTHtwSEIO/R8ap2EA3kdwWJvd8nMUHvuNofhod67emX+MeKB6FmCfi0RQLXdTGWBULa1N/JNIexuimAwjSLHis/jV6DOYb7YYnhszMTCZMmMDbb79Nt27dbvTmBaFWMgwTSdIZk5SAKmnYuo+kYP35W7S6q5R0qRHBfR4nNNQfhwaax8RmsXDs1BlyC500igpkzG0JqIqEn00FzYNFVTDuugutuJj8ZQtpOXAgmp+dkG6dkXt2xaUq7M8/yofb5uFwl5BYpykTGz4ATgtKXDMaP/U0sqoQEBZcfkWklV8R6bqBbFgZ03w4OjqqacVwmtx3y2iQDeyajG6YOFUF42xTW8MwkZwWRibcgYaGxbSglZlnR5dTymtiaDId6rSnbd1bsZggaxJuq1KtC+tVRzc8MXzyySe4XC5mzpzpnTZ27FjuueeeGx2KINQqpgm6pqMj4d/qNuo3aYfz5H5sjRL5Od3gzQ9/wjDBqsr87fEeFDiLsPvpbNp1Gk03WLDuME/c3Q5DN9mflke7ZpEkNArFNC1YwyMJHzmSMkNH0k2cphU0MC1uZv33Ywyz/HT8wJkjfL57Mfe2HIXmNtBQQYMAqHCbzDRBd0uA6h3eE7cEKJQCIHHhs4ryZUBCRbtEMQnNYwAK5598iKRwpW54Ypg+fTrTp0+/0ZsVhJtKqaYi2+thvzWaRRuO8fmq8tLXXVpFMbh3A+wBHhqHB2J6LLRrZuLWDB4dcSs7DuUwf9VBGkQGsnlXBp1b1uMPA5tTQjEL9iynyOVgSEISDQMagkchpyTPmxTO2XfmMDoakmgeWmOJns+CUEsZhommGWhnz9T7dWpAx44K7+16l2J3CXFh0TzU+gEW/nCUvCIn36w9zPtPdaVrowQ8mYdRopqwN8tEN02mfj+TsrPNvHdk7WVqrydo7NeYOrZwJEnyaS3ULKIJCqq4pV+DicQgCLWQqsroJuiGycAusfxn03GG9G7ES5texWOUF7w+U5rP0aKDPJ1yC/OXpxJTx455ZDOONZ9519Oy611YqUeZ5iTCP4w+9TtgVyz8nLGLmGbRyLrKE53/xMfbPqdMc9IkLIb7Wo8Ej4KsAtepJIUsS0iqicHZUhmiP0KlEolBEGoRSZKw2VUyckv493cHCfK3cl9yIu8+2Z18qQC7xc4fWibTLKIJQbYA9p4+zOK0r0m6rStdwqPJ++xtn/WV/bSIsA796VKvDfc27EPBN0sxypx0HToIP02jRLfQMrQFb9z+VwzTQJFUzpwxmL9qF1aLwj0DmhPkd3X9Z85RVAmnXMJX+/5DkauY5Kb9aBwci+mqXmMY1CbikxWEWkKxKJh2D9tz9nBKO8Sjdzcjr8jJxDd/wFQt1LEH8myP8WzP3MO01a/xzIqXySk5Q/sGrfh4x7+QZA3Tc0ElVF1DwiSlyUBSp75E3ub/UrB9B0dfmoknIxNFkTE8gNOC6rGTm2fw7OwNbDtwmh93Z/LMO+vxXOPJvW5xM3X1TDad+Ind2Qf4+6YPOFZ4HFUVh6/KIj5ZQagFFFWhzCzjhXVvMmfrJ8z9+X/5y5oZjB+bgCTBjsNnsCh+7Mzax86s/QB4dA/f7FtObEhDAq0B7Mo7SkBiV5/1+sW1QZIsaLsPVOjhnLFkKap5vjOnrMjsPZbL/YNbMLh7YwLsKppusHl35tXvlyJzJC/V+3zjnOVH1qLLnkssJVwrkRgEoRaQFIkdmXvJKcn1TivxlLImdT1db61HgJ8Fj+5hX87hCsumFqQTFViHzVl7Ce19N6E978Ie24rQXmMIH/IEbmxYgoMrLGcJCS0f8ecsU5IwgZ/2ZePRDF58pDuN6gYSFmirsOzvZZomgdaKpSyCrIFI4vBVacQzBkGoBSQkHJ6SCtOL3Q4aRgZQP8IfmynTvVFHTpecIbf0fF2kuLBolh5YzUMth3J6wZv4J3YjYuhEnKaNIrcJGAS2aIFfdCPKTqYDoAQE0GDEcErPXjAoqsy3G47xzdnqrvtT89hzLJfHR7WmUeTVlxoxDJP6gVE0CYvhWP4JAGyqjdG33AGajOijUDlEYhCEWkDTdLo0bMe3h5Z5Wx1JSCQ3TSJUrYvkLqGktIBgeyAPth+LBHy6/UsGNe2Ln2Lj1duexZJzCsvAh5FD6lPssfg0QS3FSosXnqc0LQ29tJSgxEScspVzXRg0E1ZuSfOJKfNMCeHBdmTz2h4ySC6VZ7s/xqniTApdxSTWaYrssYjxFSqRSAyCUAuYukGIPYiX+01hyaHvcBtuhjW7nd37SvnP+g0893grpm94B+fZIdGaRcTxXN8/Y5VtSG4F0wNGaFPKDBPDU/GAaxgmDiwocQmoSDh0w7f2kAnBATaKS33v+1stinc0uatlGCaUKTS0RhNtl9DKjGvqI6GqMoasIyOje0wxHOhF1MrEsGnTejZu/OGS7584W8X0XNG6i+nZsw89evS+7rEJQmXRnAbhlnBSbr2bHYdyePdfxziR5eCu2+L4ct9Sb1IAOJR7nNT8dFLzTzIwNgntIsngYsprDlWc1yLDI3e24sWP/+st/z2gcwxXOHzzZV2PYTplm87RouOsOraBSP9whjW/HdVjE7WULlArE8NvCQkJqeoQBKFSeDwahcU6b/97l3dagJ/C0YuMf1DkdlCmOTEwkSTAqqNJHjBBxQJutcL4B5eiaQYxdQOZO6U/B1LzaVQ3kNBAK1zj1cL1pKoyu3P3MWfrZ95pW9K3M+O2qVB2Ux4KL6lWfho9evQWZ/vCTSsk0OoztsLPe/NJTu7NgTNHvPPYVRuxoY1oEBgFuoxk9/CPbf/POx5Cy8hmPNn5Acyyy3dOkyS8t2JM3UAF2jQJxzBMzGqUFAA8sptlh9f4TCt0FZNZnE0DayPxzOJXamViEISaTlEkdIsHw9SRJRlFs6Jr5w9cVhVsuJAw0FFwYUdT3BiSjlW28NqEnsxfdYj0nGJ6t21Iq7oRPN3tYVYcWUuwLYhhiQMwDZMoexSSAafLchmWOICRLQdxJC+VBftWsD1rDx3rtL/owFOKImPXnWgFBchWG5KfP2WSpbz6aTVLCOfIyPhZ/CpM97PYxXOGC4jEIAjVjKrKFEuFvLF+LlmOHCL8w/ifbo8QrtZB10xsioGcfZCsZe9hlDnwT+iIMvghXt/0IakF6QTbgpjYZRz3JzfDo5lYFBmtTKdFcCIJHZsgyzIYIOkKmtvA9NPZn3mYBfuW49LdtK/fimd7jmfd8R/pVLd9hfgkCfy0Mvb+ZTqu0zkAhHZoT9zjj1FSjSuqyrrKvbfeyXNr30A3ypNds4g4Qm2hmE6RGX5NJAahWrtcQ4La2ohAU9y8vfEjshzlB93c0nxe3zSXV5Img6Zilz2kL3wDzh7czMa38I+f/01qQXkfgyJXMX/f9D6zBr2A5LagnZ2v/Mxf4fz5v4EkQbGnmM93L/ZO/SVzD9EhDRgY38fnKuUciyKRsfBbb1IAKNj2C65Tp5AbxVXbWzK6Xv5w/u1BL7Arax+R/hFEhzQEp4roD+FLJIYbqDq3lqqJB+Da2ojAlAxOFWf5TMt3FqKZGhZJRXfke5MCgBQZw8Ft3/vM79Y9lHqc+P3GGXx5yYm0CtMP5R5jYHxf9LKKt4VkXcN56lSF6WUZGfjFxGMYVzfm+Y1geCQUj41OdTpimubZ/RNJ4UIiMVQj1fVAV5Vx3YwNCSRTpkFQFBnF2d5pofZgVEnBNEEJDANZOX/FkHOSZhFx7D590Du/RbHgb/HD1C6/LV03aBoeW2F6q7rNUXTLRUdJ01UrkUn9KNi+4/xEWSakTWtKteqbFH5NqyFxVhXJ/L3t0aqJ3FxHtb1UFWouWZaIiLj60g3Xw7nvtqrKFFPA65vmkl1yhgi/MJ7p/ggRch10vfwZg5S9n9xlH2A4Hfg17YAy+GFe3/wP0gpOEWQL5InOfyLGLxpD++2OBJJVZ1PGVr7auxS37qFd/VY82uE+9NJL1yLylzXyN20i+z/LUPz9iX3gj8gNYnCbF18mMjKInJyKTWZrm+q4n1fz3RaJQRCoXokBzrdK0k0d5RKtkuySC0wDHRUXtvJWSVy8FdNvkS1gqB5M00Q2ld/Vh8GqSihuJ0gSHov9soPnVMcDZmWojvt5Nd9tcStJEKohXTdBV1HO/kT1C27puDVw8+uqpQZoKvIl5v8thgfwWJA4d8f9t5d3aybIZ2MQI6rVKqJurSAIguBDJAZBEATBh0gMgiAIgg+RGARBEAQfIjEIgiAIPkRiEARBEHyIxCAIgiD4qHH9GGT5Og4JJQhnVYfvVXWIoTLV9v07p7rt59XEU+N6PguCIAiVS9xKEgRBEHyIxCAIgiD4EIlBEARB8CESgyAIguBDJAZBEATBh0gMgiAIgg+RGARBEAQfIjEIgiAIPkRiEARBEHzUuJIYl/Piiy/yyy+/4PF4OHHiBPHx8QAUFRUxcuRInnzyySqO0Fd6ejqDBg3yxnnO3LlzqV+/vvf1ww8/zCuvvEJUVFSlxrNixQo+/PBDNE3DNE2GDx/OQw89dMn5v/jiCwICArjjjjuqTUxC1ZszZw7Lly8HoE+fPkyaNInNmzczY8YMXC4XycnJPP3001Uc5fXz2muvkZ+fz8yZM9m/fz/Tp0/H4XDQsWNHXnzxRVS1Bh5mzVro5MmTZr9+/byv3333XfPdd9+twogu7sI4q1JWVpbZt29fMy8vzzRN03Q4HOaIESPM1atXX3KZyZMnm9988021ikmoWps2bTLHjBljulwu0+12m/fff7+5ZMkSs0+fPuaJEydMj8djjhs3zly3bl1Vh3pdbN682ezSpYs5efJk0zRNc8iQIeb27dtN0zTNqVOnmvPmzavK8K7aTXMradeuXYwdO5Z+/foxe/ZsABYsWMCUKVO886SkpLBlyxa2bNnCXXfdxciRI5k8efINj3XKlCmMHz+e5ORk1qxZQ1JSEunp6ZW6zfz8fDweD06nE4CAgABmzpxJ06ZNWb58OXfffTfDhg1j4MCB/PTTT2zevJk1a9bw7rvvsmHDhhse068/ky1btpCSkgKU/xv+/e9/Z8yYMQwYMIAffvihUmITLi4yMpIpU6ZgtVqxWCzEx8eTmppKbGws0dHRqKrK0KFDWbFiRVWHes0KCgp4++23GT9+PACnTp3C6XTStm1bAEaOHFlj97MGXuNcndzcXObPn4/D4SApKYkHHnjgsvOnpqaydu1agoKCKjWu06dPM3z4cO/roUOHAhAaGsrcuXMBeOWVVyo1BoDExET69+/PbbfdRosWLejSpQtDhw4lOjqa5557jrlz5xIeHs7XX3/NJ598wty5c0lKSqJz58706tXrhsYUGxt72eU8Hg9ffPEFa9as4Z133qFPnz6VEp9QUUJCgvfv1NRUli1bRkpKCpGRkd7pdevWJTs7uyrCu66ee+45nn76aTIzM4Hy3/Kv9zMyMrLG7udNc8XQq1cvrFYr4eHhhIWFUVhYeNn54+LiKj0pQPmPZPHixd7/zt0/b926daVv+0Ivvvgia9as4Z577iEjI4O7776b1atX895777Fx40beeecdFi5cSElJSZXGtHLlyssucy5RJSQkUFBQcCPCFC5w+PBhxo0bx+TJk4mJianwviRVr9LUV+qrr76ifv36dOvWzTvNvEih6pq6nzfNFcOvHwBJkoRpmt7/n+PxeLx/2+32GxrfhW709tetW0dpaSmDBw9m1KhRjBo1ii+//JJ58+bx5ptvMnz4cDp16kTz5s2ZN29elcb09ddfA+d/iJqm+Sxns9mAmvujrOm2bdvGxIkTmTZtGkOGDGHr1q2cOXPG+/7p06epW7duFUZ47ZYtW0ZOTg7Dhw+nsLCQ0tJSJEny2c+cnJwau583zRXDxYSFhXH06FFM0+TkyZMcPHiwqkOqMna7nTfffNN73940TY4cOYLVakWWZcaPH0/Xrl1Zv349uq4DoCiK9+8bGVOLFi0ICwvjyJEjAHz//feVFoNwZTIzM5kwYQJvvPEGQ4YMAaBNmzYcP36ctLQ0dF1n6dKl9O7du4ojvTb//Oc/Wbp0KYsXL2bixIkkJSUxY8YMbDYb27ZtA2DRokU1dj9vmiuGi+nevTvffPMNgwYNIi4ujg4dOlR1SFWma9euPPHEE4wfP9575dSrVy/ee+89pkyZQnJyMna7nU6dOpGRkQGUf35vvfUWQUFBDBo06IbFNGHCBNq3b8/LL7/MnDlz6Nmz53XftnB1PvnkE1wuFzNnzvROGzt2LDNnzuTJJ5/E5XLRp0+fSvm+VAdvvPEG06dPp6SkhJYtW3L//fdXdUhXRYzgJgiCIPi4qW8lCYIgCBWJxCAIgiD4EIlBEARB8CESgyAIguBDJAZBEATBh0gMtcSKFSu89YIEQRCuhUgMgiBUqnHjxpGXl3fN82zZsuV3lXhv3rz5Rdf1/fffe+uOpaSksGLFCtLT02nXrt1vrvNmc1N3cKvp3nnnHZYs4LWVaAAAA7BJREFUWUJoaKi3sNzx48d56aWXKC0t5fTp0yQmJjJr1iy+++47/v3vfzN//nwAb92hNWvWYLVaq3I3hFpu06ZN12Wea9W/f3/69+9f6dupDcQVQw21evVqVq5cyaJFi7xVYwG+/PJL7rzzTr744gtWrlxJeno669atY9CgQZw4ccJbRuKrr75ixIgRIikIlWrq1KkA/PGPf2Tr1q2kpKQwdOhQhg0bxqJFiyrMk5mZydq1axk7diwjR46kb9++zJo164q3O2vWLEaMGMHw4cNZu3YtUF5m/9FHH71Oe1a7icRQQ/34448MGDCAwMBAVFVl1KhRADz77LOEh4fz0Ucf8cILL3D69GlKS0uxWq2MHj2aL7/8El3XWbhwIWPGjKnivRBquxkzZgDwr3/9i2nTppGSksKSJUv46KOPeOutt9i+fbvPPPXq1ePTTz9l5syZLFiwgC+++IIPP/zwN28zXahRo0YsXLiQ119/nSlTplzx8jc7cSuphrqwMqyiKAA888wz6LpOcnIyffv2JTMz0zvfmDFjGD16NJ07dyYhIYFGjRpVSezCzefo0aO4XC5uv/12AKKiorj99tvZsGGDzz1+SZKYO3cu69atY+nSpd4il2VlZVe0vXvuuQeAZs2aER8fz/bt26/fztwExBVDDdWrVy9WrFhBUVERhmGwePFiADZu3MiECRMYPHgwkiSxc+dObwXUBg0a0LZtW1599VXvD0cQboSLlUA3TbNCyfTS0lJGjBjB3r17admyJZMmTUJV1YuOdXA5snz+0GaaZs0cd7kKicRQQ/Xp08c7RsHo0aO9gwo9/fTTTJgwgZEjR/L888/TqVMnTpw44V1u5MiRGIYhRjUTbhhFUWjYsCEWi8U7yFJ2djbfffcd3bt3986jaRppaWk4HA6eeuopkpKS2Lp1K263G8MwrmibCxcuBGDv3r2kpaXRpk2b67tTtZxIozXYI488wiOPPFJh+h/+8IeLzm8YBhs2bODee+/13noShMo2YMAAUlJSeP/993nllVeYPXs2uq4zYcIEunbt6p3n3nvvZc6cOfTt25fk5GSCg4OJiYmhadOmpKWlXVFDiZMnT3LnnXciSRJvvfUWoaGhlbV7tZIou32TcDgc9OvXj9atWzN79mz8/f2rOiRBEKopkRgEQahRPv74Y5YsWXLR9x588EGGDRt2gyOqfURiEARBEHyIh8+CIAiCD5EYBEEQBB8iMQiCIAg+RGIQBEEQfIjEIAiCIPj4/3B8KrBV2YIcAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, axes = plt.subplots(1, 2, sharey=True, figsize=(6, 4))\n",
    "sns.boxplot(x=\"day\", y=\"tip\", data=tips, ax=axes[0])\n",
    "sns.scatterplot(x=\"total_bill\", y=\"tip\", hue=\"day\", data=tips, ax=axes[1]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, `boxplot()` and `scatterplot()` are known as axes-level function.  The main cue is that they include an argument which is which axes they should be drawn to (here we create a 1x2 arrange of axes and then the `boxplot` is drawn into the first axes and `scatterplot` is drawn into the second axes.\n",
    "\n",
    "When you look at the [API reference](https://seaborn.pydata.org/api.html) for seaborn that is an important cue to pay attention to.  Figure-level thing are described that way and mean they created their own figure can axes whereas axes level functions need to be drawn into an existing matplotlib figure.  The is a good overview of the differences between figure-level and axes-level functions [here](https://seaborn.pydata.org/tutorial/function_overview.html) in the seaborn tutorial docs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seaborn is particularly uses in Python when combined with Pandas dataframes that we learned about in a previous chapter.  In particular, seaborn makes it very easy to map columns of a data frame to visual attributes of a plot.  If you remember from the intro to this chapter, creating visuals is about mapping between elements of data and some visual feature or representations.   The structure of Pandas+Seaborn makes this very clear.  Let's go through several examples of common types of plots that you would use in an analysis, discuss the types of data they are best suited for, each time paying attention to how we specify to seaborn the mapping between columns of our data and visual attributes of a plot."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scatterplots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Scatterplots are a simple but effective tool for visualising data. We’ve already seen scatterplots in this chapter, when using the plot() function to draw the Fibonacci variable above. However, for the purposes of this section I have a slightly different notion in mind. Instead of just plotting one variable, what I want to do with my scatterplot is display the relationship between two variables. It’s this latter application that we usually have in mind when we use the term “scatterplot”. \n",
    "\n",
    "In this kind of plot, each observation corresponds to one dot: the horizontal location of the dot plots the value of the observation on one variable, and the vertical location displays its value on the other variable. In many situations you don’t really have a clear opinions about what the causal relationship is (e.g., does A cause B, or does B cause A, or does some other variable C control both A and B). If that’s the case, it doesn’t really matter which variable you plot on the x-axis and which one you plot on the y-axis. However, in many situations you do have a pretty strong idea which variable you think is most likely to be causal, or at least you have some suspicions in that direction. If so, then it’s conventional to plot the cause variable on the x-axis, and the effect variable on the y-axis. With that in mind, let’s look at how to draw scatterplots in seaborn."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First let's use seaborn to load some example data.  Seaborn includes a few built-in dataset including one called 'tips' which looks at how much people tip as a function of a number of variables such as the total bill, if the person was a smoker, the day of the week, etc..  The seaborn `sns.load_dataset()` function loads a pandas dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tips = sns.load_dataset(\"tips\")\n",
    "tips.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that this dataset is \"tidy\" in the sense that distinct variables appear in their own column and the rows reflect individual measurements."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can then make a scatter plot of the total bill versus the tip amount using ONE LINE!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x=\"total_bill\", y=\"tip\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I think that's pretty impressive and it looks pretty interesting!  The key thing is that we used the `sns.relplot()` command which is a figure level command for plotting the relationship between multiple vairables.  Lets unpack the code.  The last argument is critical: `data=tips`.  This tells seaborn we want to plot something from the tips dataframe we created earlier.  Next we also tell Seaborn the mapping between elements of the dataframe and our plot.  For instance when we say `x=\"total bill\"` we are telling Seaborn to map the x-value of each dot in the scatter plot to the `total_bill` column.  We also write `y=\"tip\"` which tells seaborn that the `tip` column should be used for the y-position.  \n",
    "\n",
    "```{note}\n",
    "This example highlights one very important part of seaborn which is that it deeply integrates to pandas dataframes.  Often the way you are able to specify complex plots in seaborn is that you have a dataframe and seaborn helps you see the different patterns between the columns of that dataframe.  This is kind of why we went to such trouble in this class to teach you pandas and python.  Because once you get use to dealing with a dataframe like pandas then many other aspects of data analysis and visualization become much simpler!\n",
    "```\n",
    "\n",
    "The `relplot()` command can also plot a third variable or relationship by using color.  In seaborn this is called \"hue semantic\" because the color starts to show a meaning:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 435.725x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x=\"total_bill\", y=\"tip\", hue=\"smoker\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, the right way to read this is that we are telling Seaborn to do a scatterplot with the data in the Pandas dataframe we called `tips`.  We tell it to map the x value of each dot to the `total_bill` column, the y value of each dot to the `tip` column, and the color (hue) to the discrete yes/no `smoker` column.  Mapping data to visual elements of the picture.\n",
    "\n",
    "I guess it looks a bit like smokers might be a stingier.  Notice that a legend was automatically added to the figure.  Colors were also automatically chosen to be clearly distinguishable but also pleasing.\n",
    "\n",
    "The amazing thing about seaborn is that we can quickly look at a different relationship if we want.  For example, the 'size' column of the data frame is the number of people in the party (i.e., seated at the same table).  So instead of using 'smoker' as the grouping factor we can use the party size:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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169YNaHup+jyxjOQxK5VZEyBfhc6dtg7e/emLfV93HW1kyZ98EKP89O2LwRyvtzD3g1XJtDK0ZY2b3xP5nb74fQ2Gr2pK1pgNAMrAVzVlWPpzMUb8NlpZWRkrV66kpKQEr9fLjTfeyK5du0a6G2ISUUrjScXQx4+iG47jtRN9wTNcLMugZceBnPamt/ZhDfGemqekkNWf/RCWJ3NlFCwLcf19H0JbUqxd9M9TXEpg6oy+KxnD5SYwdcawj9ds2LCBqVOnDmqbEf+tXbNmDd/4xjfo6ekhEAjw+uuvc+ONN450N8Qk4k7EaH51Y1+JZmUaVKxeRcIavnVvtAbLk3urwvK4hz6Ybyiqls3lI9+tIRlN4CsKgHv0b4eIsc1TXDrqkwH6M+JXNsuWLeP+++/nnnvu4dZbb6WmpoY777xzpLshJgnTNAgfqs1aC0DbDvGGRgxj+K5ubNuhfNlclHH6T0oZisrl87Ft5zxbnp/WYBb48VUUS9CIcW1Ursfvuusu7rrrrtF4azHJKDROMnfA1EmlsIb3ThoUhlj6p2vpPHQMNBTPmw6hiT2hRYiBkpu/YkJL25rg3NnEW9qy2n1Tp5C0h3eigNZAKEjJlZcATNiJLEIMhYSNmPCcYCHlK99Hz/6DKNMktGAetjcAecoCCRkhcknYiHHPUOBKxbGjUQyPB8frI61Pj53YWmEHiwlddRWgSdrkLWiEEP2TsBHjmmEozK52mrds72sLzp2NZ84c0jp7UCY1zLfNhspQmUkKmGbenvkRYqyRsBHjmstJ0fr2zqy28KFafFNrwO0fpV71TylF08ETvPPcFjob2lmweilTL5+H4fWMdteEGLAf//jH/Pa3vwVg9erVfP3rXx/QdhI2YnyzbZxkKqdZJ5NjLmySXT08/72fk05k+rvl5y9zaVcvi269SgprimHTc+QY7Tv2kI7GsPw+Si+7hNCs6cOy702bNvHGG2/wzDPPoJTi/vvvZ/369dx0000X3HbAz9l0d3cTiUQuqqNCDDftcuMuCmU3GgrDP7aCBqC7ob0vaE7Z8/u3cKLxUeqRmGh6jhyjZevbpKMxANLRGC1b36bnyLFh2X95eTnf/OY3cbvduFwu5syZQ0NDw4C2vWDY1NbWcuedd7Jy5UpWrFjBJz7xiQHvXIh8SzqKkiuX4y4uAsD0eam49iqS5th7ANJ0mTltLo8LNYwPl4rJrX3HHrRtZ7Vp26Z9x55h2f+8efO47LLLADh69CgvvPDCgJeHuWDYfOtb3+Luu+9m586d7Nixgw9+8IP8xV/8xcX1WIhhFDfcFF71Pio/cAOl119Lyh8ak7elCmvKCJUXZbWt+OPVGL7hK5sjJrdTVzQDbR+qgwcP8pnPfIZvfOMbzJw5c0DbXHDMJhaL8bGPfazv609+8pM8+eSTQ+6kEPmQchQY7jE9pdnw+7jtWx/l2K4jhFu6qF48ndDUCnkuRwwby+/rN1gsv2/Y3uOtt97igQce4MEHH2Tt2rUD79uFXjBt2jTefvttli9fDsCBAwcGXe1TCJFRXFOK7XajlJKQEcOu9LJLaNn6dtatNGWalF52ybDsv7GxkT/7sz/j0UcfZeXKlYPa9oJh09zczCc/+UkWLFiAZVns3buX8vJybr/9dgCef/75ofVaiElK6/ytqSMmt1OzzvI1G+3xxx8nkUjwyCOP9LV97GMf4+Mf//gFt1X6Ar/127ZtO+8OVqxYMcBuDg9ZPG1imWzHLMc78Y3m4mlj2TmvbA4fPsycOXMIBAL9/vuSJUvy1ikhhBATyznD5gc/+AH/+q//yt133011dXXWZX8sFmPz5s0j0kEhhBDj3znD5vvf/z5dXV3MmTOHJ554Aq01SilSqRT33HPPSPZRCCHEOHfOsPnqV7/Kxo0bUUplzTowTXNApQmEEKNHKbAjUXqaOjBcFsHKElQ/y1YLMVLOGTaPP/44kHmo82//9m9HrEPjkWEoTKWxtUxnHY8UkOqJoB2NO1SAngBP9Cc7eqjfeTjzhVKEmzqoXjoLwzd8z1sIMRgXnPosQXN+HtIkTjQSOX4CT0kJgdkziBtSxXe80Ikk7/3hLfb8/i20o5l91UKWr1uFMUwPwSkF3S0dNNQ2YJgGqUXTcQXyu1S0AXQ3trNn/dvEeqIA+AoDvL+6hMA0CRsxOqTq80WwDIi8u5/e4yeATFXfaEMTZddfS4LcOlhi7GmvbWD3i6fXwqnduo+ymZXMvn7ZsFyldjS08OhXfkwilgAgEArw5b//IqHykove97koHJoP1PcFDUCsu5djO4+wdFYN6bSTt/cWE98//MM/8Lvf/Q6lFHfddRef/vSnB7TdgKs+i1xmOtkXNKfY8ThOr1THHg9M0+DEu3U57bVb94G++BOyYShef35TX9AA9Pb0smvjbow83qozXBY9Ld057V2N7Xl7TzE5bNu2jS1btvDcc8/xq1/9iieeeILa2toBbStXNhdDqcx/Zz0XqwzJ8PHAcRzKZlay/9Xs9qr5U0EZOT/XwVJAy/GWnPaW+hYMI3/je6mUw5xrFnF895Gs9rnXLJarmkmgacdBDq/fRqIrgqeogDk3raDqsnnDsu8VK1bwn//5n1iWRXNzM7Zt4x/gch5yVrwIadNF4YK5WW3ukiLw9/8grDi3dCJBR2MLvV3dqHN86LcM8NgJPHYC6yJ+cw1D4SGNKxljyuJplM2q6vu3gtIg86+/tC8ItGPT0thE44kT2OnkoN7HdjTXfOiqnPZ5i2aS6Dp99asUmOkUhMOYqVS/x28pjcdJDvjYy+dN48o7V2G5LSy3xZV3rqKwuhQnGkOd6xs8QgxDEesO09HQQip24bV8lHZIdvaQ6g6jRrDSqlLQ09XJ8aN1RHp6zvl7OZY07TjIvl+/1vf7leiKsO/Xr9G04+CwvYfL5eKxxx5j7dq1rFy5ksrKygFtd8FyNWPNWCtX48KGcA/xljZcRSFcJaUk1NAuGCdraY/D7x7l8e/9hKa6ZtxeNx/90p0sWbkUZZ4e93JjE91/gEjdcQAKZk7HP38eyUGOjRkKzJ5O2re/g5NKYwX8FF2xnM7WMNpxCFYWo7yZkv+94TA/ffwX/PLnz+M4DmtuWsUXv/45iooHPt4SbmjhnTd28crzmzAtkw/ccR3Jxi6u/KNV+CpLUAqc9k4OPP0KyUgMl9/L/D9ajVlR2ndh5cYmeugQkdrMLb/AtCkEFi0geYEbE4ZSpKMx7FiczT/fQNP+E7j9Hlbf/yFK5k1Fk/+z59m/01o7HHxrHz/7u/8mHo1TXlPGZ/7yXkpqKvrd3o7GeOdXr1O7bT8oWPz+y1lyy/tQeV5KWynYs2M3D/35I3R2dFNaXsLDf/8XzF+84IIXvKNZrmbjD3+W9UHmFE9RAdf++Z8MS59OicVifP7zn+fWW2/lox/96AVfL1c2FymFSSpYjGvefHRZ5ZCDZrKKRmL84rFf0lTXDEAynuSJH/4XHY1tfa9RCtJtrX1BAxA5egy7o33QnzZd6QStW7bjpNIApHujdL31NqXTywnNqO4LGoDdO97lyZ8+i+Nkbj29vP4NXvn9a4Mab/EV+Inub+COO9ew9vZVNG89SHd9G97CzNWvkUyy76kNJCOZsvCpaJx9T72EET89zmN3dvQFDUDv8ROkW1oveIXiaI1hGqx/7Fma9p+cxBJN8NI/PUeye3TGFbtbOvj/Hv5P4idXJ21taOMnj/yUdCKR81qlFPXvHMoEDYCGvS+9Q9vh/C/e2N7ayje++Fd0dnSf/LqDr3/xu3R1dOb9vS9Gf0FzvvbBOnz4MO+99x4APp+Pm2++mf379w9oWwmbYeI4ekwu2DXW9XT2cHh37gBj2xlhY1kmsfrcE0ysoQnTHNyvsBOL5YzFpHujqFT2LTLTNNi2cTtn+8NvX8VOpwf8fq5QASv/5EaObN3PgZd3YVoGN37xwxi+zCfzdCRKOpZ9orWTaVLhXgAsyyDW2Jyz3+iJBkzzwqEX74kSae/JanNsh96z2kZKR3MH+qw7E011zfT2E36G0hx5M/dEVr/7yKB/7oPV0tRK7KxbfD3dYdpax/YkC09R/9Pqz9U+WPX19Xz7298mmUySTCZ56aWXuOKKKwa0rXwMF6PKX+CncmoFzfXZA+mFJaG+/7dtB095GbGWtqzXeMpKsO3BJbzy5N5+MTxutOXKanMch8WXLuTZX76Y1b78fcswLWvAt3I1UDRnKrd/5xMke+OUVBYRc07nnenzYFgmTvqM9UcMAyvgxQFsW+MpLSF6Vth6yksH1Ae334Mn4CXRm33i9IVGZ1wxVBzqpy2IL5D7/I9GUb1gOi2HG7Pay+fU9F1t5ktxSRGmaWKfsS6Mx+OmqCi3/2PJnJtWsO/Xr/VduUNmduKcm4anOv/q1avZuXMnd9xxB6ZpcvPNNw94ATW5shGjKlQc5J6vfhS35/TJfs266ymbdnrQ0XE0nppqXKHTn85chUHclZWDXhfGdnspumTh6QZDUXbl5aTOuv2pNVx59XIuuWxRX9uUadXcfuctgx4z1Fpj+Lx4y4oIlASzLqy0z8vc21bRdz9QwewPXY0++aS/1hp3RTnuM05yrmAB3ilTBtQPM+Dn+vtuwTjjSmDFR1fjKRmdk2ZJdRlr772l72vLZfGpb9yDpyB3RpPjaOZcuzhrKe2yWVVUL56e97sIFdWVfP2hL/bdqjQMgwf/91corSjP7xtfpKrL5rHwjuv7rmQ8RQUsvOP6YZuNBvDAAw/wwgsv8Pzzz/OlL31pwNvJBIExZLJOEGhtDdPb0U17Uzv+oJ+SqjIMV+5Ft1vZ6Gg0cwLw+UnqoX1WMpXGSiVwEgkMn4+k6T7nySvaG6G+rp502mbazKkEQ4VDes9T+vsZKzSqN0oyEsVV4EcF/DhnDd67lQOxaCa4/H4SejATIzSp7gi97T34QoFM0IzQ9Pz+jtex03Q2tRPpilBSVUKwtAjOM1lBxxOEWzoxDIOCiiJwj0yNN8dO09TQRFtLOxVVZVTWVKHUhb/vsp5N/yRsxpDJHDaThRzvxCdh0z+5jSaEyCvrYh6KEhOGTBAQk45S4MQTpKIJ3AU+cLkuvJEYFKUg0d7NGy9upbuxg7mrLqF4VhXKku/1ZCVhIyYVpaDnWDOv/tv/EO3qJVhRyJr/5zZ8lSWTauq6hUYDdp4e7Ex2hfmfR35BKpaZUn707UNc9+kPUnPFgkFP6hATg1zfikklHe5l/T88Q7Qr8xxLuKWbP/zjr3FiuQ8VTkSGdrCbWjj45HoO/tfvSNU3YuRhGnHn8da+oDnlrV9vRCcnx/dZ5JKwEZNKb3sP6UQqqy3a1Uusu3eUejSy0u1d7P3FH4g0tNHb3MG+X75MsrntwhsOB61Bj4MCYyIvJGzEpOIJ+nNm2VpuC7d/4i94Z5oGbbsP57Q3bX9v2Afxi6eV4/JlT1Fefse1sjT1BPH973+fb37zm4PaRsZsxKTiKQ6y4o9Xs+2/T64roODaP70ZVzAwgvWER4fWGiuQG6qugLefV18cd1GQW7/xMY5s2UtXUwfzr1tK8ewaGa8ZAQfe2MPmX7xCpL2HgtIQKz92A/NXXTJs+9+8eTPPPPMMN9xww6C2k7ARk4symHnNJVQtmEa0K0KgNIS3ODThgwYyT+SXLp5N45v7+sqZKNOg6opFw77OjdbgKS3kuj+9mc7OXllHZ4QceGMPL//bC6STmZ9vpK2Hl//tBYBhCZyuri4effRRPv/5z7Nv375BbSthIyYfw8BbXoy3vBhgTAWNHe6l/WgziWicsllV+CqKOd/T9YMWDLL0T9fSU9eIdjShGVUQCub1myBBM3I2/+KVvqA5JZ1Ms/kXrwxL2HznO9/hK1/5Co2NjRd+8VkkbIQYI+xwLy/+3VP0tp98+lzBLV+9i9CM6mF7D601OhAguGTuya8ZW2krLsrZFb4v1D4YTz31FNXV1axcuZKnn3560NvLBAEhxoj2uubTQQOgYftTr6Ec+9wbDZHWF73qtRiDCkr7L7B6rvbBeOGFF9i4cSMf+chHeOyxx9iwYQN/8zd/M+Dt5cpGiDEiGc1dIjnaE0XbDhiDW5FUTE4rP3ZD1pgNZGZbrvzYDRe97//4j//667TDAAAgAElEQVTo+/+nn36abdu28eCDDw54ewkbMekpNTY+5ZfOrEIplTVj65KbrsDwuCds8VkxvE6Ny+RzNtpQSdXnMUQq5I4cpSDZGab1cAN2Kk35nBp85cV5H7443/EqND3HWtj+y9eIdvey5KblTL9yAYZ3/D4DJL/TF7+viUKubMQ5mUpjJuPoZPKC677kg1LgdtI40V6UZaG9PlJDXMPmTIahMGJRmvfWsvsPOwm3dmOYBmu/+TF8VaXD0POh0SiC0yt5/5fvRNu2XNGICUXCRvTLUprU0SO07z8EZJYqrlh1FUlfcMQCx5OK0/L6ZpxUprxMYGoN/sWLSDH08QsXNqlj9XTuP0hQGaz52NXse6uOA5v2sfvFN7n607cw2ud3bRhgGBI0YkKR2WiiX0Y8SvfJoAHQjkP79h24GJlnJiwDunbv7QsagN76BlQ0MuR9KgVOZwdde/ejbQedThM/epT5V87CMA2iXRFkHrAQ+SFXNqJfTiK3Om86GkPZaTAurr6VZWSqD6fVuT/rGNom0dnVbx/wD21pZtNQRI4ey2lX0QglU8tYctNynGEuFKkUdHd20tLcRqgwSFGRb1j3L8R4IWEj+mX6/Tlt7uJCtOViqBc3SoEnHad7z36SHV34p9aQdM3r97W2MvHXVNF7rD6r3SooINnvFhemUbgKC4m3tme1G14/S29dQdm8qUPc87kdOVTLn3/hO3S0d2G5LP7823/GmlvWYJrypycmF7mNJvqVcnkoW7EcZWVOiq5gASXLLyPpDP2Tv9tJ0/L6ZmINzdjxBOFDR2h5cwcuI/fWle1AcME8PCWZkjLKMCi+dAmOLzcEB8q2HQIzp2G4T68WaXq9FM6dQcWSWahhXrEzHo3yV9/4AR3tmSu0dCrN3z70D5w4K0CFmAzk45Xol6MVuriMivdfj06lwO0hfpEzwZxoL04yey2ZWFMLoVQSzNzpvXHlIrTiSlQygTJNUqab9EUOmidMD+WrV2FHIijAKAgSV1Zehmq6u7o5djQ3WJobW5k+a+bwv6EQI+BTn/oU7e3tWCc/iP71X/81y5Ytu+B2EjbinLSGBBa4zn0yzkxPTmGHw5mTdzBIQvV/haCs3Flk6uTMK5fSmDjYPT1ox8EMBkmaHlIOYJ0sgT8Ms7O0JtO/YPFF7+tCQkVBpk6rpv54dtHCiqqyvL+3EPmgtaa2tpZXXnmlL2wGSsJGXBRPOkHL65v6rlgMj5vy664h0d8kAq8fb1UF8aaWvqbiJQtINDTSW3ccb1kJrlCQjt17UaZJ5fXXEreGf62VkeLzF/CdR/6cr/6/3yHcE8EwDB74+meZMm34x4aEOGXz77bx9L88R3tLB6UVJaz7/IdZ+cEVw7Lv2tpalFJ89rOfpb29nT/+4z/mE5/4xIC2HbWw+f73v09nZyePPPLIaHVh1BkGuLSNVmpYHla8EKXApRyU1qSUyUCXns/008FQGo0ijUHayTwcGT1afzpo3C4Kpk1Bx3pxFXrQ8SQYBumTdb2S2iB06VKCs3pI90ZxFwaJNjQSb+/CLKsglUqSrG8gNGsGPbV1hA8dxrv4EuzzXNEoBaZtg+OgXS7sQV78GIbCSKbQSqNd/T9EaRgKI53EBByXi9Qg6mLOXTif//vLf6K5sYXCohALFs2muyd3pt94YKJR6TTaMrFluHdM2vy7bfzkkZ+TTGSm0bQ3d/CTR34OMCyB09PTw8qVK/nud79LPB7nU5/6FLNmzeLaa6+94LajEjZDXeltIvGQJnr4KJ2Hj2L6vJQsuwSneOiD3xdiGGD1dNGxcw92LE7B7Jn4Z8/M3CY7Dzc2yeMnaNl/EMOyKJw3G8e28U6ZQtrwkurJlOXwlBRTMK2GrgOH0cqiY/thmncdwhMKMPtDK3FVlOEASUwIFqNCxeh4L0nb5FBthINbthMsK+SqdVcTKAwAkApH8KM517ldoUk3tXHgxS0kenqpunw+lSuWYLsHVt7FsNP07D3K8dd2gFLMuGE5BfOm45xZ9DKVQkfC9Bw6RLKrC295GUVLlxDvZ4ypP1pDUUkpRSWZygRujxsYf2FjRqMcfelNumobCE0tZ9YHr0YHC8ZETTlx2tP/8lxf0JySTCR5+l+eG5awufzyy7n88ssB8Pv93HXXXbz66qsDCpsR/3hy5kpvk5VhKGJ1xwgfrEU7DuneKC2btpHoyH2uZLi4Epn3SPdG0Y5D+FAtsaN1GMa5Z5cppUi3ttD17j502saOJ+jY/R6my0XXzj3g2ARmTAOgYPoU2ne+i+n10H6khaZ3DqBth3hnmL3/tR4dzq4VpTUoy2Lf9iPs37gXx3bobu5k/b+8SDyV6VPBzBmkz3cyC0fY+4v1xDvDaNuhcfs+mt/ciznACXPxEy0c+f020vEk6ViCw7/dTKKxNes1Tk+Y7l27SHZ2gYZ4SxttW7fj7mcG3URlOWn2/3IDXYdPgNb0HG9h789/j5Ec6iR0kS/tLR2Dah+s7du3s3nz5r6vtdYDHrsZ8bA5tdJbKHTx6yuMVy6dJnKkLqc90dmdt/dM9+QWBowcOYZLn/uekGXofvuZ7AmT7u3FTCdRhcWUXLYUO5Ypj+8pK6Pl3SPZG2hNvD332BJJzaEt+896qaarqZOixQvwlJVgdXdgdbfjcZKos0Ik1tadM3Gh+Z0DqFT2jLd+j80yaN5xIKe97d1aLCvzZ2GZBvGuHpyzPimmI72oRO5yABNVOhwl1pG9+FYqGifVPfRqDiI/SitKBtU+WOFwmB/84AckEgkikQjPPPMMN91004C2HdHbaBe70htAaWnBMPdq5NnJJJ1+P8lk9gnY9LgpylOV13As92RvBfwEQj5C7v4rAmjbIRosINmVfaIxPR7QGl/Ai6sggC4L0XP4KABOIoknFCDemR1ungJfTgXbaJdBoKSASHv2a30lhYRmV3PiD69hxzO3nJRlMvXG6/GWn/6jaWnNnTzgKQoQCPlwBy78pH5LRTFdtQ1ZbYHyIoqLA31fx7zu3IdIlcLj9xAqGtrParxV8o04KZRhoM8a5PMFfYQGcCzj7XiHw2gd87rPfzhrzAYyt27Xff7Dw7L/NWvWsHPnTu644w4cx+Gee+7pu612ISO6xMCnP/1pWltbMU2T7u5uotEod9xxx6AW4JkoSwx44hGaX9/ct5CKuzBE9Q3X0B3LT+0xN2m6tm0/HRxKUXndShLe84e3Jx2j5dVNaDtzBWT6vBTOnYXyetGlFX0/C49O0bHlTdKxOP5Zc9j33Ka+YwtOKWfOHauxXdmhphT0HG3kt3/3y74rlKoFU7nu/lsxutro3PVu1usLZkzDs3gx9slZAGY6xaGnXyHS0Nq3wyX33IxRPrDKzUZvL+8+8VvS8cwfpuXzsOSTH8I5s3pCpJfY0SMkGk6HUtGShRjTpg94gsWZxmPJfUNpunYepG7D9r62mqsWU3H1pdjnKTkE4/N4L9ZoLzGQz9loF2PU1rM5tdLbYGejTZSwUQrcqXjm4ULLQhUEKSwvyusfphsbHQmj02nMggKSLu8FB3iVUrjtOM6p52i8XrQySHt82GfVEfOQxjk5NuNog2hHGNPrxlNalBM0p5QU+2k4cIKepg7cfi+FU8qwAl6S+/cTrj2avf+SIkJXXUXqjClnZjpJorULO5HEW1qEChYMuJqOUmDE4sRaO1EKvOXF2B5vzmtUNArxKDqZwgoG0IEC0kOcPTheT76G42B3dZPojuAOBnCVFGIPYPXQ8Xq8F2O0w2askudsRonWkLC8UDRyz5EkMaGgCIA0DOipea01CcMDhWfNvupn2wRW1sOSnlCmYOb5Zgqblom3vBhv+entbFvjq6nMCZvArJk5FQRsy41VXYF1skuD+RiiNdheL+5p1efsp9agfX44WSYnxSDfZIJwDANVUoz3ZPmgQcz+FgIYxbBZt24d69atG623F8NMKYUrGSXVlRkbMguC2D4/mqHVUnMCIUqvvIyu3e+hbZvQonmYZWWkLvJErxNJYl1hXD4P7lDBZMwNIUaFXNmIc1IKDNtGaY1tWee95eZO9NLy+ubTYzteD0VXXI4dGNqsw7RWqNJKym7IlHZJYlx00CQ7uvnDY78m0t6DYRpc9fEbmHblIjDlAUUh8k3CRvTLQJNsbOXo77eRiiWYcvUSipfMwbZy656ZhiJ88HBf0ADY8QSxhma8cwLZD0kOgtaaxDDNzle2zcaf/J5Ie2aChGM7bP7pBspmVuGrHL2loPNFKXCicVAK0++dEOOcYnyTsBH9sru6ee8Xf+j7uu7ltzEsk9DS+TknLkOBHY3m7MNJJjPFM8fAhUM6lqC1timnPdLeM+HCxoknOPTqTnb/bjumy+J9d19PzWXz+i2EKsRIGQOnATHWKAWR+tac9sY338NIp3Pa047GP2N6TrunrBTtGhufZyyvm+IpuaHiLxr/z22dSSlFw67D7PjNVuyUTTKaYONP1tNT3zzaXROTnISNyKE1uAL9PDBZGMgUWevn9VZFOYWLF2C4XJg+L6FLFmMVF41K7SylwIzHSBw7QaKuHjq72fHrN1j2oRW4/adn1V12+9UEKvK/1MBIUo7D/ld357TX7z5y3tJEQgzUhg0bWLduHbfccgvf+973Brzd2PjYKcacQE05nqICEl2ZkiTKMJh+wxWkzzG7LIWFOX0m5VOmoB1N2uXCzs/zqRekeqPs+c8X+h7WNN0WU1YuY+N/vcySD1xOYVUJhTVleEqCcIGHEscdU1E8tYz2Yy1ZzYWVJYzSI3VihP3Pr9fz2A/+naaGFqpqKnjg659l7R0DKylzIcePH+ehhx7iqaeeorS0lHvvvZdXX32V1atXX3BbCRvRL9vjZdHHP0i8pQM7lcJXXgLBwHmnCjuOJqEsMrX4c/9dKTBNA9t28nbFYxiKjn1H+oIGwE6mSbZ24C8q4J3ntuAJePnwX9078YIGcBxYetNy6t4+ROrk9yBYVkj1oulSoXkS+J9fr+evvvlD4rFMmafGE8381Td/CDAsgbN+/XpuvfVWqqqqAHj00UfxeAZWAV3CZgKzTIWGvvIug2V7PLimVeMi8xyjaadJdfZguhRevxsnmULbNqqggDQW6a4wqWgMT1EQCgJZz9h4dJpUSyvR1la8VZW4SktJnvXrZyYTJFo70Y6DtzhINJYm0tGDLxTAX14EloWpwK2TmfdGYZ9VyUApRbwj++ltw2XhLfRTObeGzhNtWB4XaoLeUjIMhSsR5oOf/QCRnjiGoQgELPxeYxwubDB0hnZwesIkw1E8oQJUqABniM98jSeP/eDf+4LmlHgswWM/+PdhCZu6ujpcLhf33Xcfra2trFmzhi9/+csD2lbCZgKylIPq6SZ8+AiW10tgziySbt9FfbI10ymOrd+Ky+OiYmE1XXUdxE6uuOmprCDaq2nY9l7mxQoW3rkG97QatNa4lEPX2ztItGXKnEdPNBGYWoPvkktO7z8W5d2f/o5UbwwAb1EB/vkz2fhfrwJw2W1XsfDmK3DFeumprcNJpfBXV6BcLszSir7AsW2HsiWzad1TC0DZohkEq8voOHyCsqCXD3z2FvB6UG7XhPyk79I2rQcP4yRTnCoQlGiDdFkhlF64OOlEYKDp2n2Qug1v9bXNWXsNBfNnDsfK4mNaU0PLoNoHy7Zttm/fzhNPPIHf7+cLX/gCzzzzzIAe0J949xEmOaWAjnZaN79JvKWNyLF6Wl7diDt1cSXxkx3ddOw/RsnMCgzD6AsaAFew8HTQAGg49JuNGImTFZvjsb6gOaW3vgEjmemTaSpadx3sCxqAeFcEl2PjC2XKxOz4zVbirZ00bdxK74lGYi1ttO/ci5NIYqWz6zK7K0uZ9+FVBKpKCFQUc2TDW3TXNdH+3lEaX3+HsimlAwoadfaaBuOAoxSWN3dyh3GOyt4Tke6NUvfyW1lttS9ugVjsHFtMHFU1FYNqH6yysjJWrlxJSUkJXq+XG2+8kV27dg1oWwmbcUQpcCsbt+Gc80ToUprufQez2rTjkOroHPL7mgq8XosFa6/CXeDNKTWfTvYzHTqexBnAujIACoicaMtpT/ZECBSfnpoc64xw9kfTyLF6lM7uj2OY+ObMYOHd76fxnew1a5xUmmhz+3n7YyYTxI/U0/3OezhtHRh6lGY6DEHKURQtu4Qz7xi5QkGMgolT0PFC0rFETv06bTvY8Ym/2NsDX/8sXl/2GIrX5+GBr392WPa/Zs0a3njjDXp6erBtm9dff50lS5YMaFu5jTZOuLBJNTTQtu8gyjQpWroYSspyKi9rzvGJfIhjFKbS6KZGWnfuAcC3bAnKzH440OV1oUwDfcb0s0BlCabflyn46fXhLiok2XV6TR1fdSX65PLNtqOpuHQu3ceynwXxVZTS+YfMNF7TZVFQUkD47LXcDCPzqf2sPNBa4ygTo5+p2qqftr7jTSU58MsNRFtOh/O821fhnzdj3DyFn/YHqVxzPXZPGOWyMILBCy7/PZG4gwFMjws7kTqjzY9V4J/wBURPjcvkazbasmXLuP/++7nnnntIpVJce+213HnnnQPadtSWGBiqibLEQH/OVZpcKVBtzXS8tTOrvWLV1ST9ubXHXOFOWje/eXp7y6Ji9bUkzIHNGjmTJx2necNrp/cdClK0cC5OIknnewdxkkn806bgKq3gwPMbSYajBGvKmH3bqqx1YTw6TaKpkXhTC76aatwVFSSURXl5kI76NpLtnXQeOkHTjoOgYMpVS2jvivH281spKA1y/X0fonRKMS0vv55VFqdi5ftIhfqf1qsUJI6eYP8zr/a1WV43S+5di+Prf/wi3dSSVTnh1DZL7/8I6X5K9QzWZCu5PxrHq5RCd3Ry8LnXiXeG8ZcXMffD10EoOCLjdLLEQP8kbMaQc/2SukxFz5atJDq7stqDc2fhmptbPsZSGiMWIXrsBKbfi6+6moTlGdIfmivSReumbVltpsdN5eprAY3WkDLd2BqMVAqdSqO8nn4X1TIMhWEobFv3hUOhz2LnEy8Srm+hoLqU0gXT8YQChGZPIWlrkr1xXF43yuMGFJ50jHhDI+l4goJpU0j7C0g7mas2Q4Hr1BpBLhcqUEBaK9KtHbTtPYKnsIDiBTPQAf85vxfJ+kb2//LlrDZlGCz7/DrsYRj3kLAZOaadRidTKI97QGvvDBcJm/5NnmvrcczRYBUEcsLGCgT6/USf1gq8QTyLFqO1Ju7oIa/BYvh8mfv/Z2yvTJO0YZJ0DCxDYybjGLYNXh8plyvz0n7ez3F0TjBG27oI12cmG0Qa24k0ZsZTLr3/w+iCAlyhzJiNPrnTuOnFmDEbj1IkHAd0pnNKgRXppnnj1r59e8pKKFx+OU5FGdXVFZlbaxf4XnhLCzFcFk7q9DhU1RULweOelOvYjGe2aYFPTnFjhfwkxgHb0QTnzSba0JRVwt9dXkbiPCdA+zyP8BuGwqUz+0pinPOTfsrloeLaq4m3tBNvbcGOxSm96goSjoELm9iBg0SOHMP0uCleugiVSuM4Gk9Z6cCmWw/hBK61xpVOkGprx0mn8JSVgc9H+zvZs2ISbR3o3ggECs/7vcjatz/AJZ/8EPVv7CDa2kXlZfMoXjybIT6qJIQ4ScJmnEi4/FSsWYUdjqCUygz6qqGNIVjKwWlpoXXPe2hHU7RoPq7qalJk32pQaFKNbez/7WYS4SiVy+YxZeVVJN3eTEhEwkSOHAOgePEC2t/Zc3o8RSkqb7iWhMvPubiUxuU1WLJuFclYkro39pAMRylZMB0jcO7BXLedpPW1jTjJ0wPAVdevJB3PfWxRD3BGXN/rtYZQkOlrrwPbRlsW9gS9bSvESJKwGSfOuTzzEKhIDx1vn74K6Ny9lzKvB1VSjtaZ514MNOmuCHt/sb7v6qPp7f0oQ1F53XIcpUh1Z9aGsQJ+kt09WQP3aE3k8FG8S5ZkVTCwlMaIR1GOQ++xelrrjmf6ZBgs+vBKIp0xgjOr+x3zgcygf6qtPStoALreO0DJJYvo2PXuGS8Gs6CA3InZF2ZrwDBzplqPBA9pnEgErTVmQTBTAkiIcU5+iycZ0zSInWjMaY8cqSNYUYEZjxHZf4RUOIxRXJlzm6t5x0Gqrl6Ktly4CjMz4QzLzBrjOMVJJLIKhFhKkzpWR8/BWkqXX0Zau/BOn43LZ9Fbe4TwwUMUr1pJ0jnf418KJ517teIkknhrqijoCROpO47l91Fy+aWkXN4hj7W4DI1KJlBKYbs8pEfgcRuPk6Rt4xbs2MkHXj1uyq67hoQxeR7KFBOThM0k4zgaqyB3DRdXKIiZTND86ib0yTVrfIW56794QoHTyygXBCmYOZ3I0WMEZ88gcvxE1msL5swidcZVjZlK0PbeAYILF7L7v1/OPHxH5oS68Lar6HnvPZTjcL5njbXWmTGaswTnzyWmTTwLFxFYMA+NIqmNIQeNhzTdb+8i3pJ52LRg5nT8C+aR1Pmb1WQYisSJpr6gAbATSWLH67FmzQE0rnQSnUyivF6S6vxLdQsxlkjYTBKmqdA6EzaeqkrMg7XYJ8vJGJZFYNYM0j3hvqABMLRNsLqU8MkZYijFnFuuBsdBWSYpbeJdsIDQvFk4qRSV17yPrn2H0I5NaOF8dDCUdbJ3Uiksv4+eE+19QQOZE2rHkWaKZk3HNqx+K0afKeXxU3n9NXS/tx8nkSQ4fy5GaSm2BltrbC4uEAxDEa873hc0AJGjx/CUlUJJ+dB2mk7Tc6KVA7/bRrC8iIr5UzELssezDEMR7+7O2TTV2YV3DqQbGmje+S5ojeF2UX7NChLuwND6I8QIk7CZ4AwFrmSUaG0DSoFv6hSSbh9l11+DEw5nxgWCQRKmG8vIrh3Ve/Qo066cA4HLSceTWB4XRzZsJ94RZtr1yyhaNBvT0LRue5tUdxhlGgRnz6Rg9iyi2sy5qjC8PqwCPz2NkZx+xjojTF9zOdEBPOLtaEh4CwheeQVoTVqrYZ0tZhkQacxd2TLa3EpBZSWp1ODupxmG4viOQ2z8yfq+tsLqEm76yp0YvtN1zNJpB/+UGqL12bc5/dOnoWJROnbs6Wtzkinat71NyXXXZq7ghBjj5Ld0gnMleml+5Q0S7e3YsRhtW97EnYziKDPz4KMyMtOgTYWrsJDCBXMIzpmJb0o1/poqPCWFWNWVGJbJ3v9+iXhHD0Wzquk6dIJURzdOuKdvEF3bDj0Ha4k3NeEyFZaZ2e+p6jmOy0Xp8kupWDIrq4/BKeVMWXUpMcc82RfwuNQFV5bUqLysSeOgsAqLctoNry/rOSGlFDg2Z1YHOtV/0zzdaEfjvPnka2fuiu7GDrobcuvBqaJiipYsRJkGyjAoXDQfo6QEO55bSDUdjUE/41f5YqhMReVTx6tUppS/MYCCpYYBLrPfhV7FJCFXNhOYZRn07j9G2WVLibe1kwxHKJg+Bae3l2R3IzqVxvB4SPdGcAcLiHZ0EWtuxRUK4a2sItYVpaclTGGomBN7aildOINQTRlt++qYds0SVLSb7toWvOWlBGdNp2P3XtCQ7OomEAwSrj2KHYtnKh2EgnTv2U9PPEHBjKlc8tH3c/gPb1F2+QIOvVNL7X+sZ+ENy6ieUULkSC3uwhCBqTXgD+RM8VYK3Mko4XcPYUcz+1fFpaSG6bNTOu3gmzqFRFsbdm8UAFdxMUZhYd/MukRvlD2bdrPpt1uZMqeG99+5morqUpINDUSO1eMuLqZgzkzihgftOKST/UxqSOdexqW0gTFtBhVTajJfGy5SjsbTTyVnK+AHy5X3h00VEG1uZ/dv3yTS3sPiDyynfFYVh7e8x7F3DjN16UzmXbcUM9j/LT2vThE7Wk+ksRlfVQXe6dOGPG1fjF9SrmYMGe7SHqZpYLQ10b4rU4r/lOCMaRheD9q2SXR2UTC1mmhTK7Hm1tPb+n2YJZXEOnsxPC68RQWke+McffltqpfPx++xSZ4xvuAuDOItLaGnto7Ka1fQvPnNrGnDxYvn03O4rm+cqPiShSRNH8//8FekzyiYuPy2FVQVpEj3RjG9HgoXzMWqqs66VeRJx2l+5fWs/ZdcvhRdUTN8Sx/bNnZXD7H2DrQDVqgAb0UpyrJQSvP7n/6OPzx5uqyNL+Dlq397H/b+fae/hx43ZatXkVIWe57fxJ7fnS577/K6uf0v/wQrlDtZoz8mGt3WTMeO3eBoDI+b8pUrSLjP/RzTcEm0d/H8//4ZzskHY+ddu5jupi5aDjf0vaZkajkf+F/rwJU9a6446ObEhjdInlH9wl1USNFV75uwt/+kXE3/JuZPWwCZCgLKNLOCBiB87Di+smLCR+rwV1eiHZ0VNAB2NIbLY+EO+mnY8i6FUytp2Z1ZkCxYXZwVNADJ7jBWwE9g+hRS4dylAMJ19finVPV9HTl6nK7GjqygAdi9/h2s8szaG3Y8kVnnOBbNek2quztn/z37DuFSZ1wppFL0NrTSc7QRZyjrmJgmVlkxwTkzCM6dgX9KJcrK3AiIdkd4+ens22Kx3jiNx7MXqLITSZxIBEfDwhuXs+KjqymqKWX2+xZw6zf+GFfhwIIGwEZBeRWV719NxeprKV99HUlP/oMGoP1oc1/QABRVlWQFDUBHfSu9rf1MbgiHs4IGMle+xCf+2jIim9xGm+j6qVSsDAOtdWapAMcB89yzt5RSGJaJtiwM98lfl3NcPLiCBcRa27Mf7jy1H9PMaleWiWHm3uu3PK5Mn85kGCilcJFG2TbK78vcSzvjKkZZJqcWcXFicbb+9CWO78qEoy/k55av3Y2rOLdC9vloDZjW6f/v646By21hn3UbzOzv+3hykMLweZl9/TIu/eAVRHpTOGftcyAcTeZ5G8/Jq4cRusA3XWcd1znGaIx+jv9cyzmcb5kHMTHJT3yi8wdwhbIvxQsXLcDw+SicP4fI8QaUaVIwa3rWa9wlxSTjaSJN7XrgEPkAACAASURBVMx4/xXYbjfTb1gOQPuhBryV2Sv/+asqiByrJ9bUguF2YbizQy40ewa9ZzxMGpw5ncLyEP6S7E/3V9y+glRzZiaYuzCUCUSfD6ung/ZXXqf5D6/Q+e5+ypZfmrVAWNEli0idXNuno665L2gAYj1Rdv7PVtQwnZ29wf+/vTsPjuO6D33/Pb3OhsEAIBZuIEUSIkWJpERt1EpRtuhY1GLZTiLrWko9xblOlSuq+B9ZdlxJvZTzrDiuyHGcVKpuXI794nd97RfbuXJk2X6O5NikRJkSJUoUKe4gQYDYB5i11/P+GGDA4Qy4AiQwOp9/WOjp7ukzM+xf9+lzfr84Dz65rWJZ2+JWFi9fWLHMbGxAi089xwhDiR2LnGtk95zTsrwDOzFVkqHvvROsuu2ainWWbVxJdEGNchfJBuJLF1csiy9ZSGBXP4NS6pt6ZjOHzFY6dlv6eMNDeOMZIm2t0JDER8MWITKbwc8XMOMx/EIRZ3gUPR5Di8YopAsYMRurtZlA09GkJBgdY/TgCZqWt2NaAmckjd2SwozFyPX0YkSj6PEYwjTwRscIXJdoRzvCtnD7B/ALBSItzWAY6NEo+XSOnn09ZIbHWbruKpoWxHFPncJIxLFSjYSRGML3KmrqQCmjc7JrBc7wKJGOdoJonEAKhBAcfukNdv3bbyrWT7Q0cP+f/TcwZ+bBtO+6nDx4gnd37aN9STurN15NqrkBMuMUBwYxkw2YLS1VD8Lna4kBL52hd+8x8qNZll6/glhzI8PH+ug/cJLWlQtpXbW4Yhj3pNbWBsYG04TpUZzhUeyWJrRUCreOO1XUM5vaVLCZQ2bzRCREqUus1menaaLUrSZEuXdq8u/p1y+to2lT65SGKkuEKHXTSVl638nXJ/cPYAYuwzt24ufyaJaJbts0b1yPYyfKQ54ntzPGRxh6dVfVcbTftwVPt6qOcexoLz/723+rWHbdh27k2gdvn/EZ95OfXWU3W/WySfM12MDU93f6533691/L6e0917r1QgWb2lQ3Wp0RAiwRYuNjnPbtTmYPqCUMZfn1IJAVf0+3vqYJdF2rWKdUr6Y0MKG0j8r6NZN/h6EkSI/hTwwrDl0PL5Ml/c5+DK267o1Wo2iZHo0gNb3mMSaXtLLxI7ejTaTVWbS2k9X3XD8rqV0mP6tzLasHZ36fMP1vpJb3Q6BRple/97LvQ5oAI5Mmc+QYkQXNGNEo0ZYmCuHMfc0aEKbH6NtzECGhdUMXIpUsTbA8T0JA6FaXAwjyBTRZnRtNRmLlHGyTO2i58fpp59UI0+TqD25k+c2rCf0AuzGBPMsgCEVRZp8KNnXE9IoUTvVjRGxG974HQHJFJ9FVq3BmKIFkmB7j7W//x1TZgTcPsP6J+6Gpesb9dKQEO9VYtTyxfEkpKPiVV8AeGtHVq4ktW0rouuixGK5hnfXuIZSiPIdFXU8rypWnutHqSJDLoUcjZI6dmHzwUppIOTI8I/vXdY2BNw9Unr1lqc6NYVxYMAv9gJbrr8NMxNEsk8auqwg9H22a9CueFLh2HL+hCUe3kfL876QURbnyVLCpI0YiTnFopGp57kQvhjEzX7WsUV45DAIM35lu+kXt/QjByDv7S6lulneS6xsolb2ehVxniqJceep/9hziZfOY+XGsQgZLnEf64zNIy8ZqrJ7rEGlpnpGHs0EQ0r5+JWc+nmm7ppPe7Xtg/AJG4MTiRFpbyBw9ztiBw/i5HM0bN8xYfjNFUeYW9cxmjoiELj2/2FnK5EtpMlzzrTddUMJCJxDEli0l19Nb3o8Rj6HbFpr0cS+xzguA3ZJk7SN3MfDucUDSek0nuqlzas8RQgTtd99IUOPu50weOon162haswo3X0SPx/HMyIyN4tI0gS4kfihmLl9aDUKARQC+jzTMus33pSiXSgWbOUDTBIXunnKAAPDGM3iDg4j2Rec8AZsagMSXGqHUSHQuQTNLX23oeQztfpvWO26F2IWla6nF1S0SS9oxbI3QcZHAiZ37CRwXN5u/oK40T2qkFnWQH8zgl5owIyKhS+7IcXIjI8SWLsFqb5uVSYRCgFXIMPTaboJiESMeY8EtG3GsWF0OfVaUS6GCzRygaZCv8azFGRklsnAJMgwxfQfpeRXlgDUBZjFHvuckdrIBM2JjNCTIe1452HjZHEiJCENsJ4smBFI38A0L/xwP2U0h0d0CBAGabeNqZqlQmabh+4Lu3+wnN5guJ/lqv/5qnLEshXSOSEMUM5m47CPBbHwGf/Nquf6LM5ImsbyTyJo1+DOcJ8YKPQa2v1bO+ebn8gy+souWu++YkbtI5dw0GSKzeUI/wGyM42vqlDZXqW9mDggCiC1dRHG4MuBEO9qRYQD9fWeUA74Vx4phegUyBw5hxKIM7X4bgJYN1+KMpMkcPjaxjzZSa1bhZzOM7NkHlPKU6bEo1qLF054ULXwyb71D4VQpk7HdnKLx6pUYySZkJoPb38uim1bT+/oBAJbcsgYjFuWH/+f/jVdw0XSNu/6PrbSvXzVt4sYzTU4SvZRurzCXqyo0lj12nHjXSvwZrqESFotVSUeDYhFcBy5D6v/3O8336Pv1bgbeOgRArDXF1R/bQhCJnmNL5UpQHcxzgJQSo62dhslkmEKQ7FqBSDWhu8VSOeCJE3Doegz/9g0sEeKNjBJta2F8IrAY8RheNleR0r1wagAjFiO9/3B52fiRbjRdI0yP1jweISAYHi4HGijdITgjoxjFLKHr4gyN4Jw4ypJ1i1m8bjHOyW6Ov3UIr1AqZxAGIf/1zZ/hps89aEB6HiMHT/D6//wlx36zBz+Tu6DPr/LYawS2c1T8vFi1MhsIvVQBVZl9Tv9wOdAA5AfT9O/ar6qBzlHqzmaOcNFpu+UGYitXgBD4uoUXSoxa5YBzeYTvoek6QXFqXorVmMQZSVetXxwcQo/YhO5UXZswCPFHRjGbW6tGqum6VlXfBkoBx0qlMJtKEzJlEJDvLWVybli1gle//9uK9aWU5NNZrLOk9pdScnznfnb+r5fLyxp+8QYfevr30GIXfoUq4qUs195pI+Mar16Fp5vMdLpl37BpWr+W0T3vlpc1b1yPq81+9cz3O00T5E5Vzx8bPdxDx+0bCFXEmXNUsJlDNMMo1SuBcnEwfZpywNIwMZtSyKGp/3Du2DixjjacM4pVWU0pcr39le+la9gtzfg1hkQHQUikvZVcT2WBLLs5hQwDpGHRdvstjLz1DkGhSGLFcqKdSymM/6pifSEEsdTZC4RlBsd448fbK5cNjzPWO0zTqiVn3bYWR+o033oT3tAQ7ugY0Y42SDbizUJe/0CCvnAx7S0tBMUieiyGd47MBsrMCENJvKOlannTqiWEhjbjFxbKpVPhf47zrQjNN6wrP/fQLIuWmzfiSg3HiGC3NNG4elVp3VweMxHHbmkqbx9bvJBIeyu6PdXlk1yxjDCQaI21U8xICXpzC7GF7eVldksTVqoREHjoeA0pmu+6g7YP3oNoW0h6MMOWT9+PFbVLx2no3P2p38FqOnvWWillzaHS8swCahfAESaybSH2NWvxks14s/iwPpACx4yWMxuEKrPBZRNpb6H9+q7y37H2JtpvXFNVe0+ZG1SJgTlkutTkmiil5BeBjxAC33HRolFcvRRAIgTgOsggQEbjpR4cp4gQgsCO4IcCWwRQLKBpGhgGnm6dc3RWRARQyEEoEYZOfmCYyOJFU3N/goCjO95h1w9+jZSSxo4mtnx6G34QEo9Z+HkHIxZBNMQJp0nU2dIcZ8f/85+89R+vlZfZ8QgPfPEx9ES85jbz2XwuMXAxZru9upSE2Vwpi0UyQaBd+VGAqsRAbaobbR4IJfi6STgwMPV8QBO0bboZr6GJgtTBjIHJ1LOCydFQEwHFkTrYp3VpncfVXyAFfnqc9LulpJ6ptasJxdR/5sJQmt9+f6qo2dipUXb8639y92N38863XyCcKJu87J6NpNZfXbMfXdM1uu65nobWFAd+/TYLlrdz9eYNGA1x1R2lnFMgBDQkEMCF59xQLicVbOYJwy3Sf9qDaELJ0K7dtN5zFw4GQoAxUbTrUueTmBqIICAcG614+D26510WxGKQbAYgN1J99bZ4zWIO/u/flAMNQPfLb5BcsQiStQcKaBGbpbesZsXGFUgZEhj2jM+JURTlylLBZp44fSQZAEIQWdCCJkNMXSJHhhk/eAQtYpFc3YVrn/3OQNMEhgyQmoY3ERd0IdFzGdxMgVN7jtDUVj04Id99gtgNC/D9kHhLdfBItTZyav+RquVetoA5TbAxCXGPdTO8/xBISXRhO8l11+Kon6ei1A01QGCe0KLR8iABIxZlwcZ1hK7L4Pad+MeP442mcUbTFPoG6P/VDiy3MO2+LALCE92M/Ho7mdffIOKV0szohSzZ7hMc/v9eJ9M7hFZjcpzZmCw/M4suSLHpv91brogZbYyzoGsp0QVn1KoRYDeeZVRadpyxfQfLc4kKff0Uj58463wJIUAvFgmGRtAKBfVDVpQ5Tl06zhOebtG66SaGd71JY9dVpYwBEyf90XffI7lyOWZDAi+TBSlxh0cQCxdX3d1omqB4tJvx90qT4fx8gf6hHbTfexfZ7hNodpT84MTQaTOCZluETumuSrMtIksW4UwO0NA0lm1ay8JrOnHzDrGmBrSoTdfDd3Pg316imM6i2yartt2BjE8/o94dqZ5cmu/pJbVsec2BBZomcHv7ee//fYnQDxCaRteDdxC9aqka8aooc5QKNvNEKIHGZlq33EU4OloONJMyx07QePUK0vsOAqWZ7LUG7ZnSZ/RgZTeXDEP8TBZhmsjAx0pEcbMFDr74Glfdcz1WzCSSakBrbKzKQi0RmI0NmI2lUTNSAg0NrHn8foJ8Ad22kJHIWUcQmsnqETd2SzOh0KjVFyiKRQ786Ffl50IyDDn4/G9Y/6mHIabSxCjKXKR6H+aRMJSl5xhG9TWCbluEbimbgGYamC3NNfchhUCzqtOpaEIQX9ZJvreXFR/YiNA1Atfn0M93kRnKETQ2X1C5g0A3oKGBwLLPOVRdS6WwWxdMtSVik+haSTDNdn6+SOBUVvSUocTLTt91qCjKlaXubOYhraEBIxHHz07lEGtetxY3kyG1fi12W2tpDk6Nc7UnNZo2XMfQztfLy8xEHDc9hlYs0nbX7TiDQ6z/5H34XogemZgnM4sVNF0MkhuvRxTyyDBEi8UpnmUiphGPYkRt/IJTXiZ0DbMhVrMbTYjZrWmjExJm88ggxEjG8cWVn+uhKHONCjYzSAiBEEx7Ja9pAik564lP1wVCiPI+Tt+XrguCoHR303LbrQTpNIFTxGpqIozGiLY0EyIQhoFwg/IDdilL7x0EYSlRZVMLi+7bTO74yVIpgjCkMDRCrKMN6RSJtrfi5XJomsSIGYSmRiBL7z2d82nbmZ+TlBI/n8fSQjypIyNnT20zKbRs1nxsC8f+cxeF4XGQIV0P342MVo6ei2gh/ugofjaH1dKEjDVcdNqa6dqn+R5929+if3cp+3Vi4QJWfeRuArt6JN/pOUJ1XUxkuL6441GU+eaKBJtvfOMb/PSnPwVg8+bNPP3001fiMGaMEGAHLs7AIF6hQHRhO0E0QTCRukQXEj2fpdDXjxGLYre1TuVAAwwRouWy9O88iB6xsRIJNCkJfJ9oYxJMEz89RnFwCKulGb2piUAz0GNRvGwGAg/n0EH8aASCkKDolHKCAflTA0Sam5AyxLJthK7hjmXIZHNE2xYQFIoURtKY8RgjE3NqNMukbdNNZIcypPccx04lkLZNgCC1vANxWrZjXUj0QpZCb6ltkbZWilp1NuTJz8kdGadnz1GKmTyd1y0lO3SKMJ8nte4aaF5Q/szOxpABRDQ6Ny7HTDZgtTThGKdV+fR9xk8M8PYbB0i2NNC2qJGxfTtJXrMGL5bEbkqed55MXUiMYo5CXz+abZfuGg27/F5O/3A50ABk+4YY2P0erbdtqHhmphUKjB85ydBYltiSVt7ddxwjYtG1oYtY6tKL2inKXHfZ09Xs2LGDr3/963znO99BCMGnPvUpPvnJT3Lfffed1/ZzMV2NHboM/teOirkwrZtuwm8sPTfR08MV3Va6bbHg7jtwhIkQAm24n+Fdb069HomQXLkMgPEjx2nZsJaBV6e2jy3qING5hIFXd2E3N2HGYxjxGNkTJ/Fz+fJ6qTWryJ7oxc/lSa5YhpVqZPTd9wiKU91PLRuuRbNMBn879f4AVqqRbFbSv6c0mCDS1IDW0YY0DLo+eCNSloKHMTbC4Ku7yttplkXr3bdXBNNJXnqc//i/vod7WvfXB//7h9AHjiODkLY7N+Geo5qoJiA80V3OagBgNjbQtOkWXKmjaYITr+1j+7d/UX493tzAvY/djtd3klGStK+9ikhb7WdaZ7JyYwxs3zn1/qZB6+Y7cTQLTRMMvbqHkzvertgm2pJk9SfvJ5joetScIu9+5wW83FQG7wW3r+N//P2PSLU28sdf+u9YF5Hhej54v6XnAZWuZjqXfYBAa2srzzzzDJZlYZomK1eupLe399wbzmHB2FjVpMv03v2YQmISEhbytN68ngU3XIsRjxE4LsH4OFCa85J++93K/RWLCE1j7OBREp2LyJ/swzrt6lfTddL7S1fTsYVtZHt60UyjItAAjB06SqKzlDl5/OhxjFikItAApN87XPPZjpseI9E+dUIujmZINid48/lX8TOl9zGFJP3OvortQneqbWcaONRbEWgA3vzZbqzWVgAKp/rR9XNUDw09xvYfrFjmjWWQudLzq6Dg8Nsf/FfF67mRDNl8QOj5GLbBoVfeRdfP/dM3NUjvPaN9no83UipyF4aSxMLqzMOpFYuRp00SKg6MVgQagMw7R7j9vhs5ebiXgRP9Z+5CUerOZe9G6+qaytJ67NgxXnjhBb73ve+d9/YtLefXr385pdPVtV9C3ycetwg9l7zhExbzIDRab7yW4T3voYnSVYuXyxMGtbM6ySBAaDphECD0qYfOQteQE8N+g6KDEa1+PgClIcFisnCYlDWDigx8jBpX1XZzE2Mna7QrDLFMnebWBvxCkeEaxy6QNa/Iemqs67k+TCRPtBsSNDWf/ft1xsZrZoQ2dEGqtYHxwTECr/p9ZBASWbiQN3+xj9SiFpqbz53kM3Bc0jUyUmtIWibaV7QW03rtCgb3lu4AY60plt52HYkFU+3vO1F9MRV4PvbE3KPJ30K9que2Tef92OZzuWIDBA4ePMinP/1pPve5z7F8+fLz3m5OdqMlGhCaVnESbFzTRcHx8fu6kd7EXY8McUcHSK1ZiYgnGBzMIAQ0ru4ivXd/eVuh66VqnSs6yfX00rh6JUOvv1V+3c1kSa5czvBbe8ke76Hp2jVI30czTUJvakhww7Kl5E6eAkpdb6HvI3S9opRxcuVynPFxUqtXkT5wGKTEiMdIrLiKQ9unuqKMqE2x4HH1HdcR2tbEsQsa13QxsnuqG0loGlpDsmY3woKVi0oVQk87ga+7dx3e0CB6xEZvaTln94OhCRLLl5I9dqK8TLdtQjs6cUwa6z58E2/+71fLr5sRi8aOJvoO9jJw5BQ3ffzu8+rmEAKSq1dVdHEiBHoqVbH94g/eQset1yL9ALMxQUEzKJz2utXSiGboFfniGtcu59+/8wuSTQ00dyyo264m1Y126fuqF1ekxMDrr7/OU089xRe+8AW2bdt2QdvOxWAjBFhugczBQwT5Ag0rr0I0tWCaAuf4gar1ows7yYlYeWSTLQKC4SEyh7sx4jHii9rxXRcZBGiGgRAa7niG4tAI0fZWzHiMQv8gdnOK3MlTWM2NJJYsAinJdPfgjY2T6FyCZpmMHTxKbGEbumUhDAMjYpM53oOfzZPoXIwejTDw6utYjQ0kOpeUBiCYBvmhUTK9owzuP050QYroolbG03kWb1hZUUHTJESODpM5fBQ9FqOhayWuFZ1mlJUkf2qYd366i/xYluvu20hHZzNChmgNDec9j8ciwDt1ityJHuymJuIrllcMSpCOQ+/bR3nvV3toWryAtVs2sO/X75AbGmPdh28m2dkO5zmU2yCEsVEyB4+gRyOl9tmxCxpFJoSA8XH6Xt1LcXSc1NrlvHugh9HRLHc9dAfJ1uquuHqhgs2l76teXPZg09fXxyOPPMJzzz3HbbfddsHbz8VgM0nXBRqlrMtSQsQU+L2HkX7lBMRIZxc5r3SyE0IQ1xyKfcfRI3G0aBTdjuIbEQjDUq0Ox0FPxJGWjS81zMDF6e3Dz4yT7FpJ4PvIIESLJ5CWhUFIICkXkRKahpABfigQlM6zmgQCj9Hf7sYZGcWIRWm58XrcWANSgmlqGMjSiCop8QIJmlbzsy9lnIaQsw+PnlTq2ZOEUlz0f0xNE+hIAsS0xyRCCZpg4p9SGvqL/OmYeilbgn+xOwB0TdCYtBnLOASejzZNlod6ooLNpe+rXlz2brRvfvObOI7Ds88+W1726KOP8olPfOJyH8qMCwJZUVPD8SXxhUsp9BwDWTrzWws6cMOpq+qIAcWTJ5BBgJ8bh1zp4Xpk6Spyvg6RBFY0hnQchO+DbuEIE23pMhq8An2/2l5+fmM2Jmm65SZy4syvdfKoZOWfGCRvuQnN95C6gYtWvmL3vJDKECmqUuRM0gQIKZHTFEg7U2k3l1bRMgzlxATO2sckZSlbwuTLl3pSLz0GurSdBKFEN02CoAha/QcaRTmdqtQ5yzQBERPwXYRu4IR6xdVx3AjwR0dKEzkDhyCfBcBetJy8tIkERYZe3YWfyyM0jabrr0O0tiOEIL9nD/neUxXv13LzDQRNrZetfZHAIXPgEM7IKPGli4l0Lr2g0gDvtytf1d76p+5salMZBGZZKCHvAlgT1TGnAk1Eegxs34U3VvphxpcsJLG0DT+bRjcMzEAy8ts95SHNMgwZeWMP7VvuRNpR3PHqH7Sfy6M1l9Kz6LqGlHLWgrONz+BvXiGYyAo9tv8g7vg48fUbVPEzRVEqqEScV4gmIHf0WDnQAOR6+gh9sNsWk+3px/Rd3NF01bZBvoCPRmLZ0qrX7JZmNEKsQgZn/7sEx48RCZyKVCkzJczlyoFmUqG3H91zptlCUZT3K3Vnc4XoSDKnBqqWO6MZ3ntxN8XRcW54chtmIo53WsJNzTQxE3ECt4C+ZBGh6zJ+6CiaoZNat5YwlkAbTzPwym/L24wfOEzb5jtwdLv2sQiJ4RQICgW0SIQwEsM/j7Qxp8/9KS/TNM5a9UxRlPclFWyukEBoRDra8Q5V1pYR0RhLN61BFxJnJE3rphs59fIOQt9Hty1aNq5nYPtOgqKDHo2w4JYbia24Cgl4wkAQMjYxZ0cYpSSb0vfxRkdhQUfVcWgCZH8f/W++U17WuKYLY9nyc+Ypk9EY9oIWnKHhqW2vuRpPMy/1WbqiKHVGBZsrJAwlsauW4QwN4aZLI9DinUswLIOxd94pn6zzPY10bLkLr1DAjFjlwAMQFIoMvvIarffcVXooLyWGBnosSsuKZQRFB6FrpXke05z8zdCjf8/eimVj+w/SvmghgVE7M8EkT2o0btxAmE7jZbLYk5mVVaBRFOUMKthcQY4wabn1ZoKxNEGhCLrO+IFDFYHBTY/h5XJ4iRSimC0Hmkmh6yGLRZhIz+9JQXLlcvq3v1ZeR49EaLvjFmqVFpOeV3tcsOfCOYINlGrRkFqA1tSKO78GNiqKchmpYDOLNE1ghj7IkEA3q0ZoaZqg2NvH6ERq/9SaLvx8dUiQnocduujRCM3XrSEMArLdPfj5AkLT0C0TW3r4uoUmZLk09KSgWMQdy0BzdfDQIhGMWLS0L10j0bkEMxFHt2qXCZjOdCPodQ2MoDRjx9NNaqQ1m1NO/85C3bzo+jeKolRSwWaW6ALEyCCDb75N6HpE2ltpXreWom6XbyQMQkYOHytvkz/VT2LZEjJHuokvWYQ9kelZaALv1CnGh0YonBpAMwwaV6+kMDBEfHEHQ6+9gZfJ0rByOYlVKwic6tFgoedOFCyrXB6g0XzdGsaPdJNYtpSxA4fJHD2OEe+m5eYbcO3ERVe5tAgoHjnG8MEjIKCxayXWsmV4Z6nCeSUZQiKHBhh88x1C3ye6qJ3ktWsvqBy2oii1qWFDM0QIiBAQDYpEnCy2XyS9dz+hW7qqL/YPkt67H8vNI0Qpp5jmFtFPy9jspseJL2qnbdONBI7DyDv7Gdn7Hu7oGGgahYnRa6HvM7r3PVJrVpE5dgJvPFPKi3boKO7wMMlVK6qOz2purpnPKwCc8SwNy5cyuvc9vExpUqmfyzO4fSdW6FVvdJ6fRzAyzPhEck9Cydh7h5Dp0Yva3+WgFfMM73qz3FVZ6O0nd/gI51GNQFGUc1D/jWaAEGDlxvGHB+n/9Suc+tUO+l7eTnLVVZgNUynz86f68UZGsEWAc+wop176DQ3LlpTrBesRm2J6nEL/IMXBiRFeUjJ24PBUqYDTuOlxvPFsxbLskW6shR00b7gOIxbFakrRdtcmPKt2ca4whMjSJYR+QFCsrLkSej5hsdaTnnMzDJ388Z6q5fmeXgxjbv7s/Ez1JNn8iZMYUvWlKcqlUt1oM8AKPZyhYTJHj5fvZGQQMLLnXZqvW8PI26UCXGZDA+5YBru1tXTFD6T3H6Jlw1pCP8BqSCBMk6Ej3VXv4ecLaLZFeNokSt22q2q7WM1NuOiwcDHNHR1IoeGGnHUosiNMoq0LqsokQKny5sUIQ0ls6SKKwyPI00oKWE2pOZtuSI9UP9Myk0nCs4zmUxTl/MzNS8x5RjoOwtCrn5VIWX7eITSNxq6rCKQkPK0/y8/lGX5zL6N792Mk4ohoDKupseo9rMbGipN2pKUZzTIwElNFwPSITXzZ0lKSylDiSu28H3A7mkXz9esqlqWuuwbfqD0R9Gz0YoHR3fvo+e1hrMXLiS1eoZVq/gAADodJREFUBIARi2Iv7JizwUYkGoi0TeWVE7pO0/q1eOEspF9QlPcZdWczA4Rtl2rPWGb5zqb0QikoNK9fC1JSGBkjuboLKTSMWJRYR1spWIQhmmVixGOM5QMar1mNMzRaDl7RjjaMeIyOe26fGDVmoFsmXr5A26ab8ItFZCjREgmKF/mVhhL0BW20b7mLoFhEmyhI5l9gXNA9l33f+wVOutS9N7S/m867NtB29+2ISBRnjg4OAHDRabhhA8l8rjSJNpHA0azqURWKolwwFWxmgKuZmKkUzdeuYXjPu6VKmELQcuMG3GgCIxIrFQjTDIoTXVptd97KyO63GT+ty8xMJBDRBgqazYLNdxDm86WUMJEoBTlxE5o4raunIYIPELvwu49aAgSBGQVz4vnORZxjneGxcqCZdGLH2zSvW0UwhwPNJE9qEC1l2vVBBRpFmSEq2MwAKcFPprASPh2bbyP0fIQdwdUtNCTCdUpXytEYgdCRErx8oTwIQI/YJFddhZMeI2KaSCEIHBctFsMVxvw63013sPOpDYqizDgVbGaIlKI0H8Mwy5+qKUMKBw+RPXIMKD3Qb71zE0XdRnql4bWaadK0djXDb+0t3REBjatX4gyP4o5laLtzE0Wz9kiyuchuSWE1xHAz+fKyRbeuhYitAo6ivI+pAQKzSOSz5UADEDgO6bf3lvKXxeMgoOGqpYzuO1AONABj7x0mvriD0PMYeeMtLG3+nKUDy+Kax7ay5I71pJYvpOvBO2ndeM1Fl2NWKhm6wNDVgAVl/lF3NrMoKFTPUXGGR2mUAZ4Zoe2OTfiZTCkv2hnCiVLP7tg4IgyYT19VGI3Rcus6WjVBEIQq0MwAXUj07DjjBw+jGToNXavwInFVWlqZN9SdzSzSY7GqZdGONgJRqj/vxZPYCzsqhi9P0ozSw3S7pYlQO/9Ao9WY/HklhKHE98P59bxpDtOz4wxs30lxYIh8bz/9v9qO6ebPvaGizBEq2MyiMBonde2acoYAM9lAcu3qckJOKaEQ6iy4eWN5QqHQdZrXXUPmWA9GPEbTDevPa66MIUrVOYPuo+gjA9jy4tLMKHOPoQvGDx6uWl442TdnLi4U5VzmT9/MPOSjoS/tpH1hB9IPwLYpyur47lhRFmy+E1P6eFKAEKRaWsCO1Fz/TJomkAODDLzxVnmZmUzQtOnWUjYBZd6rWRXVUN+tMn+oO5tZFoSl2fmuFcWdJnBICY7UiLa24AgTBwPXik27/pnM0Gf07XcrlnnjWWQuO80WF0/TBKYuSgXZlMvCDyTJrpUVy4SmEemYu9kYFOVMdX1nYxtgSA8CHwwLV+p4wbm3m6QLiV7MlyZX2jbEEnhnxGdDB1sE4Lug6/jCwvGn2eEsEEKg+R6p1StBCGQQkN5/CBmGFSPcZkIkdMkd6SY7PEJ86WKsjo5S8TRl1nnRBO333EG+pw/N0Iks6sA1I2o4uTJv1O2ZwjIEjPdTHJtKaW+3LyY0GgjO42pQExD29TJ8WsnkxFXLiFx9Nb4U5XUsP0fx1FR2Y6MhhZVqx71MAcdy85z6r+3lvGl6NELT2qsZ3X8QPZFgpg7DJmDwN6+WM0O7o2PEx8aJXrO2qiicMvNCCY4Vx1zVBYATShVolHmlbrvRTHz8scraKc5AL7Zxfv9DzcBl9J3Krqns0W40Z2o4s22C099bsY6fSWPO2Cn+7AwNMgcOViTonBxG3b75Tlz94jI21xLmc1UlCHLdPei+O80WymyYTLKqKPNN3QYbGdboQpISzrM2iQwCak1ikP5UIBHT7O/MNP2zRQB+Nle1PPADXDMyo8OOaz6jEaI80k5RFOVs6jbYYFigVTZPi0TPOxmktCNYjcnK7S0T7bS5M77U0KJnzJHRtNJ7Xwa+FCSuWl613G5dMPNXv7E4Vqry82i8eiW+rkomK4pybnX7zKbgQXzJSpzBk4SFAkZDEqO5g5x7fidhLxQ037yRsb37KJwawG5O0bThOhxhlPvKXV8Sb1uCP9KPnxlDi0Sw2xaT8wSXo0NdSonZ1kbq2jWMvXcIzTBoWr+WIJaY8bd3pUbTzTfiDQ/jpseItrdBQ/K86+UoivL+VrfBRkrIehrWgk4sDfyA8w40k4qaRXzDBpLrA0KhUQyrKzbmXDBTHVjNHQQhZD3J5Xxy66KjLe2kbckSpCilyJ+tWfuOMBGtHdjtC/FUDhpFUS5A3QabSe6FVv86gx+Cj37W+OH5kis5Xz8MwUG7LDFOSghUoFEU5QLV7zMbRVEUZc5QwUZRFEWZdSrYKIqiKLNOBRtFURRl1qlgoyiKosw6FWwURVGUWaeCjaIoijLrVLBRFEVRZt28m9RZ72Vw6719tbzf2qzaW//ej20+FyHlbCU3URRFUZQS1Y2mKIqizDoVbBRFUZRZp4KNoiiKMutUsFEURVFmnQo2iqIoyqxTwUZRFEWZdSrYKIqiKLNOBRtFURRl1qlgoyiKosw6FWyuoGw2ywMPPEBPTw8AO3bs4MEHH2Tr1q0899xzV/joZt43vvENtm3bxrZt2/jKV74C1Heb/+7v/o7777+fbdu28a1vfQuo7/ZO+uu//mueeeYZAPbt28fHPvYxPvShD/Fnf/Zn+L5/hY9uZj3xxBNs27aNhx9+mIcffpi33nqL559/nvvvv5/77ruP7373u1f6EOcOqVwRb775pnzggQfktddeK0+cOCELhYLcvHmzPH78uPQ8Tz755JPy5ZdfvtKHOWO2b98uf//3f186jiNd15VPPPGEfP755+u2zTt37pSPPvqo9DxPFgoFuWXLFrlv3766be+kHTt2yFtvvVV+7nOfk1JKuW3bNrl7924ppZSf//zn5Xe/+90reXgzKgxDeccdd0jP88rLTp06Jbds2SJHR0dlLpeTDz74oDx48OAVPMq5Q93ZXCHf//73+Yu/+Ava2toA2LNnD8uWLWPp0qUYhsGDDz7Iiy++eIWPcua0trbyzDPPYFkWpmmycuVKjh07VrdtvuWWW/jOd76DYRgMDw8TBAHj4+N1216AdDrNc889xx//8R8DcPLkSYrFItdffz0AH/3oR+uqvUeOHEEIwR/90R/x0EMP8a//+q/s2LGDTZs2kUqliMVifOhDH6qrNl8KFWyukL/6q7/ipptuKv89MDBAa2tr+e+2tjb6+/uvxKHNiq6urvJJ59ixY7zwwgsIIeq6zaZp8vWvf51t27Zx22231f13/Od//ud89rOfJZlMAtW/6dbW1rpq7/j4OLfddhv/8A//wL/8y7/wve99j97e3rr+ji+FCjZzhKyRfFuI+ktTfvDgQZ588kk+97nP0dnZWfV6vbX5qaee4pVXXqGvr49jx45VvV4v7f3BD37AwoULue2228rL6v03fcMNN/CVr3yFWCxGc3MzH//4x/n6179etV49tflSzLt6NvWqvb2doaGh8t8DAwPlLrZ68frrr/PUU0/xhS98gW3btvHaa6/VbZsPHz6M67pcc801RKNRtm7dyosvvoiu6+V16qm9L7zwAoODgzz88MOMjY2Rz+cRQlR8v4ODg3XTXoBdu3bheV45wEopWbx4cd3+pi+VurOZIzZs2MDRo0fp7u4mCAJ+8pOfcPfdd1/pw5oxfX19fOYzn+GrX/0q27ZtA+q7zT09PXzxi1/EdV1c1+WXv/wljz76aN2291vf+hY/+clP+Pd//3eeeuop7r33Xr785S9j2zavv/46AD/+8Y/rpr0AmUyGr3zlKziOQzab5Uc/+hF/8zd/wyuvvMLIyAiFQoGf//znddXmS6HubOYI27Z59tln+ZM/+RMcx2Hz5s38zu/8zpU+rBnzzW9+E8dxePbZZ8vLHn300bpt8+bNm3nrrbf4yEc+gq7rbN26lW3bttHc3FyX7Z3OV7/6Vb74xS+Sy+VYu3YtTzzxxJU+pBmzZcuW8ncchiGPPfYYN954I5/97Gd54okn8DyPj3/846xfv/5KH+qcoCp1KoqiKLNOdaMpiqIos04FG0VRFGXWqWCjKIqizDoVbBRFUZRZp4KNoiiKMutUsFEURVFmnQo2St158sknGRkZueR1du7cyQMPPHDO91u9enXNff3yl7/kS1/6EgCPP/44L774Ij09Pdxwww3n3Kei1Bs1qVOpO9u3b5+RdS7VBz7wAT7wgQ/M+vsoynyg7myUuvL5z38egD/4gz/gtdde4/HHH+fBBx/koYce4sc//nHVOn19fbz00ks8+uijfPSjH+Wee+7ha1/72gW/79e+9jUeeeQRHn74YV566SUAfvjDH/LpT396hlqmKPOburNR6sqXv/xlfvjDH/Ltb3+b3/u93+Ppp59m69at9Pf387u/+7ssW7asYp2mpiaefvppnn32WZYvX05/fz9btmy54LQqS5Ys4S//8i85cOAAjz/+OD/96U9nqYWKMj+pYKPUpcOHD+M4Dlu3bgVKWbW3bt3Kr3/964pnJkII/umf/omXX36Zn/zkJxw+fBgpJYVC4YLe7xOf+AQAV199NStXrmT37t0z1xhFqQOqG02pS7VqiEgp8X2/Ylk+n+eRRx5h7969rF27lqeffhrDMGrWYjkbTZv6rySlxDDUdZyinE4FG6Xu6LrO4sWLMU2Tn//85wD09/fzs5/9jNtvv728ju/7dHd3k81m+dM//VPuvfdeXnvtNVzXJQzDC3rPH/3oRwDs3buX7u5uNmzYMLONUpR5Tl1+KXXnvvvu4/HHH+cf//Ef+dKXvsTf//3fEwQBn/nMZ9i0aVN5nccee4xvfOMb3HPPPXz4wx8mmUzS2dnJqlWr6O7uxrKs837PEydO8JGPfAQhBH/7t39LKpWareYpyrykSgwoiqIos07d2SjKOfzzP/8zzz//fM3X/vAP/5CHHnroMh+Rosw/6s5GURRFmXVqgICiKIoy61SwURRFUWadCjaKoijKrFPBRlEURZl1KtgoiqIos+7/B0AJuv/htAiBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 405.85x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x=\"total_bill\", y=\"tip\", hue=\"size\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, we knew that hue should be set to the name of a column in the pandas dataframe.  Interestingly seaborn automatically adjusted the colors to be a nice pink-purple scale instead of orange/blue because there were more categories of size and the are not a nominal factor.  Again, this highlights how useful seaborn is for exploring datasets.  Two lines, two very different views on the same data.\n",
    "\n",
    "You can also change the symbol used in the scatter plot by assigning the 'style' of the marker to one of the columns.  For example, going back to the smoker example we can make the differences even more obvious by setting the color and size to reflect the smoker status:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 435.725x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x=\"total_bill\", y=\"tip\", hue=\"smoker\", style=\"smoker\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can go overboard and put lots of data relationships in the same plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 435.725x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x=\"total_bill\", y=\"tip\", hue=\"smoker\", style=\"time\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So now we have color showing smoking, style/marker type showing if it is lunch or dinner and otherwise the plot relates the total tip to the total bill.\n",
    "\n",
    "```{note}\n",
    "Another reason this data is so easy to plot is because it is organized in a pandas dataframe as a **tidy** dataset.  We discussed tidy data formatting in a previous chapter.  However, this is where that discussion begins to pay off.  Because each piece of data is a column and there are descriptors of each data point in the other columns we can easily use different columns to group or color the data in a myriad of ways.  The main point is that adopting dataframes+tidy data organization makes all the other stuff you do very simple (as short as one line often!).  It's like being organized - it can make your life better!\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Going back to the example of using the size of the party to determine the color of the points.  Imagine instead we want the size of the dot to relect the size of the party:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 419.1x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x=\"total_bill\", y=\"tip\", size=\"size\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now everything is the same color but the bigger dots relect bigger tables which kind of has a nice congruency to it.  You can also change the range of sizes used in the display:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 419.1x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x=\"total_bill\", y=\"tip\", size=\"size\", sizes=(15, 200), data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I hope that you are at least a little impressed by seaborn at this point.  Usually in a single line you were able to look at this multi-variate dataset a number of different ways which give you some insight into the relationships.  The ease of doing this is critical to the sensemaking process described at the beginning of this chapter.  By making small changes to the mapping between dataframes and visual elements of a plot we get different depictions of the data.  \n",
    "\n",
    "The key to effective use of seaborn is to let it help you do these types of things while relaxing about some of the details.  For instance these dots all have a nice blue color.  While it is really not that big of deal to change the color using seaborn, why bother?  You have a nice color pallete selected in advance and you can focus on other things.  The key is relaxing and letting other people figure out the detailed stuff so you can focus on your science/data analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lineplots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Scatterplots are a very, very important tool for getting insight into the relationship between two continuous variables.  However, some types of data individual data points are linked to one another.  For example, data that occurs in time might be better visualized as a line.  Let's create some example data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(dict(time=np.arange(500),\n",
    "                       value=np.random.randn(500).cumsum()))\n",
    "g = sns.relplot(x=\"time\", y=\"value\", kind=\"line\", data=df)\n",
    "g.fig.autofmt_xdate()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice this is a very different looking plot however it uses the same `replot()` function we used for the scatterplot.  The main difference is that the `kind='line'` option was set.  If we plot the same data without the kind option set we get a scatterplot again:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(dict(time=np.arange(500),\n",
    "                       value=np.random.randn(500).cumsum()))\n",
    "g = sns.relplot(x=\"time\", y=\"value\", data=df)\n",
    "g.fig.autofmt_xdate()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because seaborn's `relplot()` assumes that you are most often trying to draw y as a function of x, the default behavior is to sort the data by the x values before plotting. However, this can be disabled by setting (`sort=False`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.randn(500, 2).cumsum(axis=0), columns=[\"x\", \"y\"])\n",
    "sns.relplot(x=\"x\", y=\"y\", sort=False, kind=\"line\", data=df);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Categorical scatterplots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the previous section we talked about visualizing the relationship between two continuous variables, possibly using color or the size of dots to display additional information about this relationship.  When we have a categorical or nominal indepdendent variable but a continuous dependent variable (E.g., reaction time as a function of different conditions in an experiment) a different plot might make more sense.  \n",
    "\n",
    "One nice plot is known as the categorical scatterplot.  Here is an example for the `tips` dataset we have explored earlier:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tips = sns.load_dataset(\"tips\")\n",
    "sns.catplot(x=\"day\", y=\"total_bill\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's unpack what is going on here.  First we have our categorical variable (day of the week or the column `day` in our dataset).  Then within each level of this variable we have plotted the total bill (`total_bill` column of the dataframe).  Notice that dots are randomly jittered a bit so they don't all plot on top of one another.  This gives a nice visual summary of what types of values are outlier (e.g., the 40 dollar bill on Friday) as well as what seems typical (usually bills are about $20.  We can also see that perhaps people spend a little more money on Saturday and Sunday on their total bill."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can get rid of the jitter like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"day\", y=\"total_bill\", jitter=False, data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But of course this does not illustrate the data as clearly since everything is on top of one another.  Related to jitter is a thing called a \"swarmplot\" which prevents the dots explicitly from overlapping visually:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"day\", y=\"total_bill\", kind=\"swarm\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The seaborn categorical plotting function can do the same color grouping for an additional factor.  For example we can color the observations by if they were male or female waiters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 436.35x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"day\", y=\"total_bill\", hue=\"sex\", kind=\"swarm\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Boxplots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Categorical scatterplots are nice in that they let you see more of the overall distribution of the individual scores.  However, there are also times where it is useful to plot more schematic or summary data (particularly when the number of data points gets really large).  For this, a very common and traditional type of plot is the box plot or box-and-whisker plot.  In fact, boxplots are simply a special type of seaborn categorical plot (`kind=\"box\"`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"day\", y=\"total_bill\", kind=\"box\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Box plots show a lot of information at once about each categorical factor.  Usually they show the median (middle line) and the 75th and 25th percentile (edges of the box), then whiskers extend beyond.  Here is a useful chart which shows a typical box and whisker type plot but this is **not** what seaborn plots.\n",
    "\n",
    "<div style=\"text-align: center\">\n",
    "    <img src=\"./images/boxplot1_annotated.png\" width=\"350\">\n",
    "</div>\n",
    "\n",
    "Instead the whiskers in seaborn by default extend to points that lie within 1.5 inter-quartile range (IRQs) of the lower and upper quartile and then an points that go beyond this are plotted one by one (helping you see possible outliers).\n",
    "\n",
    "You can add another dimension to the graph using the 'hue' option we saw earlier:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 418.459x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"day\", y=\"total_bill\", hue=\"smoker\", kind=\"box\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here the different levels of smoker (yes/no) are put side by side due to a behavior called 'dodge' which can be turned off with generally poor results given the similarity of the data in these conditions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 418.459x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"day\", y=\"total_bill\", hue=\"smoker\", kind=\"box\", dodge=False,data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Raincloud plots and violin plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The purpose of boxplots and categorical plots is to summarize the distribution of responses with different conditions.  There is a balance between showing the data directly (like the categorical scatterplot) and showing the summary of the data (like the boxplot).  Recent some new types of figures have been proposed which aim to accomplish both things.\n",
    "\n",
    "One example is the violin plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"day\", y=\"total_bill\", kind=\"violin\", split=True, data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The violin plot shows a small box plot in the center with a smoothed \"kernel density estimator\" (a type of smoothed histogram) showing where the data actually fall.  You can also use the 'hue' option with this type of plot with kind of an interesting a compact comparison between the second factor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 436.35x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"day\", y=\"total_bill\", hue=\"sex\", kind=\"violin\", split=True, data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "People have taken these types of plots to the extreme and there are even really nice plots call \"Raincloud\" plots which plot the kernel-density smoothed histogram (like a violin plot), a categorical scatter plot (jittered data points), and a box plot with whiskers all on the same figure.  When oriented horizontally these plots look like a rain cloud with little rain droplets beneath, hence the name.  There is a nice library called [ptitprince](https://github.com/pog87/PtitPrince) which simplifies the seaborn commands required to make such a plot making it only a single line."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12a3b08d0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import ptitprince as pt\n",
    "#same thing with a single command: now x **must** be the categorical value\n",
    "f, ax = plt.subplots(figsize=(8, 7))\n",
    "pt.RainCloud(x = 'day', y = 'total_bill',  bw = 0.2,\n",
    "                 width_viol = .6, ax = ax, orient = \"h\", data = tips)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is the vertical version:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12abe9898>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import ptitprince as pt\n",
    "#same thing with a single command: now x **must** be the categorical value\n",
    "f, ax = plt.subplots(figsize=(8, 7))\n",
    "pt.RainCloud(x = 'day', y = 'total_bill',  bw = 0.2,\n",
    "                 width_viol = .6, ax = ax, orient = \"v\", data = tips)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The \"bw\" option here controls the \"smoothness\" of the kernel denisity estimator.\n",
    "\n",
    "Overall these are about the most ultra-categorical plot you can get!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Barplots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Perhaps the most common plot of all time besides the scatter plot is the bar plot.  This draws a set of bars reflecting some categorical variable and the height of the bar usually reflects the mean value of the dependent measure.  To illustrate this we will load in another pandas data frame example from seaborn for the passengers on the titantic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>survived</th>\n",
       "      <th>pclass</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "      <th>embarked</th>\n",
       "      <th>class</th>\n",
       "      <th>who</th>\n",
       "      <th>adult_male</th>\n",
       "      <th>deck</th>\n",
       "      <th>embark_town</th>\n",
       "      <th>alive</th>\n",
       "      <th>alone</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Cherbourg</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   survived  pclass     sex   age  sibsp  parch     fare embarked  class  \\\n",
       "0         0       3    male  22.0      1      0   7.2500        S  Third   \n",
       "1         1       1  female  38.0      1      0  71.2833        C  First   \n",
       "2         1       3  female  26.0      0      0   7.9250        S  Third   \n",
       "3         1       1  female  35.0      1      0  53.1000        S  First   \n",
       "4         0       3    male  35.0      0      0   8.0500        S  Third   \n",
       "\n",
       "     who  adult_male deck  embark_town alive  alone  \n",
       "0    man        True  NaN  Southampton    no  False  \n",
       "1  woman       False    C    Cherbourg   yes  False  \n",
       "2  woman       False  NaN  Southampton   yes   True  \n",
       "3  woman       False    C  Southampton   yes  False  \n",
       "4    man        True  NaN  Southampton    no   True  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic = sns.load_dataset(\"titanic\")\n",
    "titanic.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A bar plot is nice for showing the trends across different factors (typical of a factorial experiment).  For example, we can plot probability of surviving the titanic as a function of the ticket class of the passenger and the gender:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 436.975x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"sex\", y=\"survived\", hue=\"class\", kind=\"bar\", data=titanic);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Generally this shows that women survived at a higher rate than men, but it is pretty depressing that nearly 100% of the first class women passengers survivied while about 50% of the third class ticket holders did.\n",
    "\n",
    "The error bars here are the 95% confidence intervals.\n",
    "\n",
    "A related plot doesn't compute the mean within each categorical variable but just counts the number of observations within a group.  For instance this is the number of people on each deck:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"deck\", kind=\"count\", palette=\"ch:.25\", data=titanic);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or men versus women:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"sex\", kind=\"count\", palette=\"ch:.25\", data=titanic);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Interesting to learn there were about twice as many men as women on the titanic!\n",
    "\n",
    "These count plots are like a histogram but with a categorical variable.  These examples also show how to adjust the colors of a plot (known as the palette).  There is more information about this [here](https://seaborn.pydata.org/tutorial/color_palettes.html). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Point plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Point plots are very much related to bar plots however instead of a bar, you just plot a point with an error bar around it.  In addition, these types of plots often include a line connecting the observations.  These are useful because they draw the eye to patterns of change across conditions.  They also make things like interactions more obvious.\n",
    "\n",
    "Here is the same barplot from above on the titanic data this time as a line and point plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 436.975x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"sex\", y=\"survived\", hue=\"class\", kind=\"point\", data=titanic);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When you plot a figure like this one in black and white it might not be easy to map the colors of the legend to the lines.  For this reason, it is usually better to modify the line type and marker symbols. Here's one example of that type of customization in seaborn:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432.85x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"class\", y=\"survived\", hue=\"sex\",\n",
    "            palette={\"male\": \"g\", \"female\": \"m\"},\n",
    "            markers=[\"^\", \"o\"], linestyles=[\"-\", \"--\"],\n",
    "            kind=\"point\", data=titanic);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that the linestyles used here are the same codes we described earlier for raw matplotlib.  That is because seaborn is deeply tied to matplotlib and thus learning a little matplotlib can help you understand why certain things in seaborn exist.\n",
    "\n",
    "By now you should be getting the sense that while plotting in raw matplotlib usually requires many lines of code, plotting in seaborn usually takes just one line and a few options.  This is because seaborn tries to do most reasonable thing for you including nice colors, etc...  This lets you get nice and informative plots with little effort.  Then you can often go back and adjust things with addition options to seaborn functions (such as the example above).  In addition, since seaborn really is just a matplotlib figure you can use many matplotlib routines to adjust and customize your figures."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Histograms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Histograms are another major type of plot which is important for exploring your datasets.  They make most sense when you have a univariate (i.e., single type of data) on an interval or ratio scale.  Most of you probably know how histograms work, since they’re so widely used, but for the sake of completeness I’ll describe them. All you do is divide up the possible values into bins, and then count the number of observations that fall within each bin. This count is referred to as the frequency of the bin, and is displayed as the height of a bar.\n",
    "\n",
    "Histograms help reveal which values are common or typical in your data, what the shape of the overall distribution is (sometimes useful for checking the assumptions of certain statistical tests), and can help detect outliers and other anomolies in your data.  Histograms in seaborn are most often accessed view the figure-level function `sns.displot()`.\n",
    "\n",
    "This function can take as input any arbitrary python list or array, or a data frame and column:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1250ee5f8>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "penguins = sns.load_dataset(\"penguins\")\n",
    "sns.displot(data=penguins, x=\"flipper_length_mm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x126209860>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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fUy09EXv2O+TamTnE+jxs0BWTVZjTAhxBqlq6GDSGkjCd+3e0kuJ8XDUtm437aglMJ6JUeNICHEGON3bh8wiF6fG2owTdDfPyOdnSzd6TbbajKHXetABHCGMMxxu7KM5MxOeJ/P/WlbPz8AjaDKHCWuS/U6NES3c/rd39lGRGdvvvkMykWC6ZnKkFWIU1LcARItK7n53JDXPzKa/r4HB9h+0oSp0XLcAR4nhjJ+kJMaQnxtqOEjKr5uYD2gyhwteoCrCIXDGabcqOgUE/Vc3dUXX2C1CUnsCCCWls2KdrxanwNNoz4J+Ocpuy4GRLNwP+yO9+diY3zM1nV2ULNa09tqMoNWYjzgcsIpcBlwM5InLvsLtSgfBc5zwCHW/swusRJmQk2I4ScjfMzeMHGw6ycX8Nn7xsku04So3Juc6AY4FkAoU6ZdilDfhIcKOp0Tre2EVRegIxkTD7mXgQkVFfpuel0t9YydcfenRM+4kIxRNLbP9rVZQb8QzYGPMK8IqI/MYYczxEmdQYtHX309TVx9yiVNtRxofx8+DGg2Pa5Y2KBrafaOa7z+8nIWb0H8zuXTVzrOmUGlejPWWKE5GHRWSjiLw8dAlqMjUqQ93PJkVh+++QqbnJGANHGzptR1FqTEa7JtwTwC+A/wR0KQIXOd7USUq8j4zEyJ397FzyUuJIjvNxuK6DOQUR8klARYXRFuABY8zPg5pEjdmg31DZ1M2M/MhafHOsRISpOUnsPdVG/6A/MtrCVVQY7W/qcyLyjyJSICKZQ5egJlPnVN0aWHwzmpsfhkzNSWbQbzjWqM0QKnyM9gx4rfPz68O2GWDK+MZRY3G8sQuPEJXdz05XlJ5AvM/D4fpOpuem2I6j1KiMqgAbYyYHO4gau2ONnRSkJRDn0y7ZHo8wOSeJw/WdDPoNXo/7mmSKJ5ZQVXkiJMfy+mIYHOgPybEAJhRPpPKEdpQaq1EVYBH55Jm2G2N+O75x1Gh19A7Q0NHHFVOzbEdxjWk5yZRVt1PV3OXKUYFVlSfG3MXufN27ambIjjV0PDV2o22CuHjY9XhgBbAD0AJsyYm/zH7mvkJjy8TMRGK8wuH6Tn1dVFgYbRPEF4ffFpF04PGgJFKjcryxk8RYL9nJ0TP72bn4vB5KMpM4XN/BdTNzorpniAoP59tfpxPQdmFbxMPxpi5KshK1yJxmam4SXX2DVOvkPCoMjLYN+DkCvR4gMAnPbOAPo9zXC5QCJ40xN4nIZAJnz1nAduBuY0zfWINHs9iCGfQOaPezM5mcnYRH4HB9B4Xp2jtEudto24B/OOz6AHDcGFM1yn2/DJQRmEEN4HvAj40xj4vIL4DPADrIYwwSplyEEGjzVH8tzuelOCORw/WdXDktWz8hKFcbVROEMynPAQIzoWUAozpjFZEJwAcIDGFGAu+G5cCTzkPWAbeOLbJKmLyE/LR44scw8Uw0mZqTTGt3P42d+sFKudtoV8S4A3gHuB24A9gmIqOZjvI/gH8C/M7tLKDFGDPg3K4Cis5yzHtEpFRESuvr60cTMyo0dvQSWzA9ahbfPB9TcgJNMxV1ulaccrfRfgn3z8DFxpi1xphPApcA/zrSDiJyE1BnjNl+PsGMMQ8bY5YaY5bm5OScz1NEpNcrGhDxUJKt7b9nkxTnoyAtXhfrVK432gLsMcbUDbvdOIp9rwBuFpFjBL50Ww48BKSLyFDb8wTg5OjjqlcO1jPY1UpeSpztKK42LSeZho4+WrtDNxpMqbEa7Zdw60VkA/CYc/ujwAsj7WCM+SbwTQARuRb4mjHmLhF5gsBqGo8TmGPimfPIHZX8fsOr5fX0HH0PkaW247ja1NxkXqto4HB9BxdNzLAdx4r2nn5OtfTQ0t1Hb78fEUiM9ZGdHEtBWgKxPp01zrZzrQk3DcgzxnxdRD4EXOnc9Rbw6Hke8xvA4yLyHeA94JHzfJ6os7+6jYaOPrqPbgc+ZzuOq6UlxJCdHEt5bXQV4IFBP/ur28j/5IP86o1jf9ke4xWMgQF/oDep1yNMykpk4YR0JmQkaG8RS851BvwfOGexxpingKcARGS+c98HR3MQY8xWYKtz/QiBNmQ1RlsPBlqBuo/usJwkPMzIS+HNw420dveTlhDZE9YbYyirbufNww109g0iHi9XTsumOCOBzKRYfF4Pxhh6B/zUtvVwrLGLgzXtHK4/SWFaPFfPyCEvNd72PyPqnOszSJ4xZs/pG51tk4KSSJ3VK4fqmV+Uhr+r1XaUsDAzLzAt5aHadstJgqutp5+ndpxkU1ktqQkxfPiiIqp/82WWlGSQmxqPz5mgXkSIj/FSkpXENTNy+PQVk7huZg7NXf38/t1K3qhoYNBvznE0NZ7OVYDTR7hPhxmFUGt3PztOtHDNDO0RMlqpCTEUpMVHdAE+3tjJ77adoLa9hxWzcrl9yQQmZIyui6LP62HBhHTWXl7C7IJUSo8388cdVXT0Dpx7ZzUuzlWAS0XkbxobReSzBIYRqxB50zk7uWamFuCxmJGXQkNHH40dvbajjLs9J1t5ZucpkuN9fPySicwrSjuvttw4n5fr5+SxZl4+9e29/KG0kuYuHcQSCucqwF8B/k5EtorIj5zLKwSGD385+PHUkK0H60mJ97G4eKQPJep003OTEeBQbWT1Cd5xopmXD9RRkpXIHUuKSU+88FnxZuSlcPuSCfQP+nlyexUNEfhHy21GLMDGmFpjzOXA/cAx53K/MeYyY0xN8OMpCHzB8sqheq6anv2X9jw1OklxPiZkJnCwth1jIqN9852jTbxW3sC03GRuWlA4rt3JclPj+chFExDgj9urqGvXWeWCabRzQWwxxvzUubwc7FDqrx2q7aCmrUfbf8/TjLwUWrv7qW0P/zO6HSeaeetII7PyU1gzNz8oSy9lJcdx+9JiYnwentl5ijYdzBI0ejoVBl45FOh+drUW4PMyPScZr0c4UN1mO8oFKa9tD5z55iRz/Zw8PEFc9y4tIYZbFhYy4Dc8s/MUPf2DQTtWNNMCHAa2HqxnVn4KBWna8eR8xMV4mZqdxMGadgb8/nPv4EInm7vZsL+WgrR4bpibhycEAyeykuP44IICWrr7eH53tXZRCwItwC7X2TvAu8eatPnhAs0uTKVnwM/Rhk7bUcastbufP+8+RWq8jw8uLAzp9wATMhK5fk4eVS3dvF7eELLjRgstwC731uFG+geNNj9coImZiSTFeSmrDq8+wQODfp7fXY0fuHlhIQkW5oCelZ/KouJ0dla1UF4XXq+f22kBdrktB+tIivVy8aRM21HCmkeE2fmpHGvspDNMBhoYY3j5YB31Hb2snps/Ll3NzteV07LJS43jpf11tGgf4XGjBdjFjDFsPVjPFdOydeaqcTCnIBVj4EBNeJzF7TnZSll1O5dOzmSy5fmfvR7hxnkFiMALe2q0PXic6LvaxSrqOjjZ0s21M3NtR4kIGUmxFKTFs7+6zfV9ghs6enm1vIGSrEQuneyOTz+pCTFcPyeP+o5eth1ttB0nImgBdrGtBwNLMV2rw4/HzZyCVJo6+1y9bP3AoJ/1e2uI83lYNSfPVVNFTs1JZnZBCqXHm6lpc+9rGC60ALvYloN1zMxL0eXVx9GMvBRivR52V7l3Rrk3Khpp7Ozj+jl5JMaOds2E0Llmeg5JsT427atlYDA8u/W5hRZgl+pwup9dO0vPfsdTrM/DnMJUyuva8SS5b16Now2d7KxqYVFxOpOy3LnuX1yMl5Wzc2nq6uPtI02244Q1LcAu9UZFA/2DhmtnaPvveFswIQ2/gZSFq21H+SudvQNs2l9LdnIsV0zNsh1nRCVZScwrTGVHZTP1ETDE2xYtwC619WA9yXE+lk6KnuV0QiUjMZaSrESSF62h3yUfoY0xbCqrpW/Qz+q5+WEx6dIV07KJ93nZfKAWxP153UhfNRcKdD+r48pp2cSEwRsxHC2ckI4vJYsN+9wxqd+uqlaON3Zx1fRsspLDY8Xr+BgvV8/Ipratl+RF7vo0ES703e1Ch2o7qG7t4Tpt/w2akqxE+pur+c2whSttqW/v5fWKBiZnJ7GgKM12nDGZmZdCcWYCGdespU57RYyZFmAX2uIsvnmNtv8GjUeE9u3PUnq8mW1H7PVpHRj0s35foMvZytm5rupyNhoiwnUzcxFvDP/2QpntOGFHC7ALbT1Yx+yCVPLTdJXaYOrYtZHs5Dh++nKFtQyvlTfQ1NnHKpd2ORuNjMRY2t55mj/tPMWOE82244QVLcAu097TT+mxZh18EQJmoJe/v3oKr1c0sP146LtTVdR1sPtkK4snplPi0i5no9X69hPkpsRx/3P78esw5VHTAuwyb1Q0MOA3XKfDj0PirmUTyUqK5SebQ3sW3NbTz0tlteSmxHHF1OyQHjsYTH8P/7R6FrsqW/jTzpO244QNLcAus+VAYPHNiya6b5BAJEqM9fG5q6fwyqF6dla2hOSYfr9h/d4ajIE184KzrJANH1pcxMIJaTzw4oGwmXHONi3ALmKMYeuhOq6enhMW/UAjxd3LSshIjOFHGw+GZJKebUebqG7tYfmsXKtTTI43j0f41gfnUtfey8+3HrYdJyzou9xFyqrbqW3r5Rpt/w2ppDgfX1w+ndfKG/7SAyVYKpu6eOdYE3MKUpmZnxLUY9mwpCSDWxcV8vBrR6hs6rIdx/WCVoBFJF5E3hGRXSKyT0Tud7ZPFpFtIlIhIr8Xkcg5BbhAW53FN6/V1S9C7u7LSpiSncR3/lxG70BwFqD0puTw4t4aMhJjIvpL1m+smYVXhO+tP2A7iusF8wy4F1hujFkILAJWi8gy4HvAj40x04Bm4DNBzBBWth6oZ25hKrmp2v0s1GK8Hv71g3M40tAZlI/PXX0D5H74Xxg0hg8uKIzoEY4FaQl87qrJ/Hl3NbtC1K4eroL2W2ACOpybMc7FAMuBJ53t64Bbg5UhnDR39lF6vInls7T3gy3Xzczl5oWF/GxLBYdqx2/VDGMMX3tiFzE5k1gzN5+MpMj/0HfPNVPJSorlgRcPuH7ye5uC+mdYRLwishOoAzYBh4EWY8zQV6RVQNFZ9r1HREpFpLS+vj6YMV1h66E6/AZWzs6zHSWqfeuDc0iNj+FLj71HT/+FN0UYY3hg/QFe2FND89bfMMny0kKhkhzn40srpvPWkUa2Hor89+/5CmoBNsYMGmMWAROAS4BZY9j3YWPMUmPM0pycyG0vG/JSWR05KXHMD7O5ACJNdnIcP7xjIQdq2rn/uf0XfPb245fK+eUrR/jEsom0v/v0OKUMDx+7ZCIlWYl878UDuobcWYSkIcoY0wJsAS4D0kVkaMzlBCDqe233Dfh55WA9K2bl4omQPqHh7LqZufy3a6fy2Dsn+NUFTNbzsy0V/GRzOXcsncD/vHne+AUME7E+D19bNZMDNe08/V7Uv83PKJi9IHJEJN25ngBcD5QRKMQfcR62FngmWBnCxTtHm+joHdDmBxf5+qqZrJ6bz3ee38/v3z0xpn39fsO/v1DGDzYc5LbFRfz7hxZE7R/WD8wvYMGENB7ceHBcmnQiTTDPgAuALSKyG3gX2GSM+TPwDeBeEakAsoBHgpghLLxUVkucz8MV08J/SGqk8HiE/7hzEVdPz+Ebf9zDz7ZUjGqOg7r2Hj71m3f55atH+ORlJfzgIwsiZqTb+fB4hPvWzOJUaw/r3jxmO47rBG36JWPMbmDxGbYfIdAerAh8SfNSWS1XTssmIdZrO44aJj7Gy8OfXMLXn9jNDzYc5M3DDXzrprlnHEDR0z/IY++c4KHN5XT3DfLd2+Zx16UlFlK7z+VTs7l2Zg4/21LBRy8ujqjRfxcqPOe/iyCHajuoau7m89dNsx1FnUGcz8tDdy7i0imZPPDiAVY/9CqXTs7kiqnZ5KfF09k7wJ6TbWzaX0NbzwBXTsvm2zfPYVpu5I1yuxDfWD2LG3/yGv9n62H+x42zbcdxDS3Alr1UVgvACu3/61oiwl2XlnDjvAJ++9Zxntt9ih9tOvSX+zOTYrl2Zi4fu2Qiy6Zkht2k6qEwuyCVDy2ewG/ePMbayydRlJ5gO5IraAG2bHNZLQsmpOnotzCQkRTLl1dO58srp9PVN0BDex8JsV6yk2PNtfuvAAAWOElEQVS16IrnnK+BNyWHont+ycK7vknjCw+d96EmFE+k8sTx897fTbQAW9TQ0ct7lS18deUM21HUGCXG+piYpW+fvzB+Htx48JwPe628nh2+6/n7z36G7PNcfPTeVTPPaz83itwB6WHg5QN1GAMrZmvzg4oOF0/KJNbn4c3D9tbhcxMtwBZtLqulMC2eOQWptqMoFRLxMV4uLsngaEMnJ5u7bcexTguwJT39g7xW3sDyMFwJV6kLsag4neQ4H69XNET9RD1agC15rbyBrr5BVs8tsB1FqZDyeT1cOiWTmrYeDtd32o5jlRZgS9bvrSEtIYZLp2TajqJUyM3JTyUzMZY3DzdE9SrKWoAt6B/081JZLStn50X0xNxKnY3HI1w+LYvmrn72V7fZjmONvvst2HakidbuflbPy7cdRSlrpmQnUZAWz9tHGukf9NuOY4UWYAvW76smMdbLVdN18h0VvUSEK6Zl09k3yM4oXbpIC3CI+f2GDftquW5mLvExOvmOim5F6QlMyU6i9Fgz3VE4XaUW4BDbcaKZ+vZebtDmB6UAuHxqFv2Dft491mQ7SshpAQ6x9XtriPV6uC6ClyVXaiyykuOYXZDK7spW2rr7bccJKS3AIWSMYf2+Gq6cnk1KfIztOEq5xrIpmSDw9pHoGqKsBTiE9p1qo6q5m9VztflBqeFS4mNYVJxOWU079e29tuOEjBbgENqwrwaPwMo5uvabUqdbWpJBvM/Da+X1UTNEWQtwCK3fW8Olk7PITNIlWZQ6XXyMl0unZFHZ3M3RhugYoqwFOEQq6topr+vQwRdKjWB+URoZiTG8VtHAYBQMUdYCHCLP7qrGI7BmvhZgpc7G6xGump5DS1c/u6sif3CGFuAQMMbw512nWDYli9wUXXpIqZFMykpkYmYi2442RfzgDC3AIbDvVBtHGjq5eWGh7ShKuZ6IcNX0bPoG/GyL8G5pWoBD4Lldp/B5RNt/lRql7OQ45hWlsftkK02dfbbjBI0W4HFSPLEEETnDxcPPnnubtkPbyEiKO8tjxnZRKhosm5JJjNfDK4cit1uaLus6TqoqT5xxVdhTLd08sb2KD1w2n1l/f9e4HCuSVoVV6mwSY31cNiWLVw7VU1HXwfS8FNuRxp2eAQfZodp2vB5hck6S7ShKhZ0FRWnkJMfxankDfQORN2ewFuAg8vsNh2o7mJyVRJxPp55Uaqw8HuHamTl09A7wTgTOlha0AiwixSKyRUT2i8g+Efmysz1TRDaJSLnzMyNYGWyraummu3+QGfnJtqMoFbYK0xOYU5DKeyeaI+4LuWCeAQ8A/90YMwdYBnxeROYA9wGbjTHTgc3O7Yh0qLadGK8wOUubH5S6EFdMyyLG62HLwTrbUcZV0AqwMabaGLPDud4OlAFFwC3AOudh64Bbg5XBpkG/oaKug6k5yfh04U2lLkhirI/Lp2ZR1dxN4uyrbccZNyGpDCIyCVgMbAPyjDHVzl01wBmnBhORe0SkVERK6+vrQxFzXB1v7KR3wM+MCPzmVikb5hWlkZsSR+aKz9HSFRlNEUEvwCKSDPwR+Iox5q/WnzaBzn1n7OBnjHnYGLPUGLM0Jyf8Vo/YX91GQoyXiZmJtqMoFRE8IqycnYcnIZXvPF9mO864CGoBFpEYAsX3UWPMU87mWhEpcO4vACKrUQfo7h/kaEMnM/NT8Hp04IRS4yUnJY62t5/kye1VvFYefp+MTxfMXhACPAKUGWMeHHbXs8Ba5/pa4JlgZbDlUG07fgNzClJtR1Eq4rS8+ThTcpL45lN76OwdsB3nggTzDPgK4G5guYjsdC43Ag8A14tIObDSuR1RyqrbyE6OJSclznYUpSLPYD8PfGgBVc3d/GjjIdtpLkjQhiIbY14Hzvb5e0WwjmtbU2cftW29XDUt23YUpSLWJZMz+cSyifz6zaN8cGEBiyeG53AC7R81zsqq2xBgZr72flAqmL6xehb5qfF8/cnd9ITpvMFagMeR3xgO1LQzMSuRpDid50ipYEqJj+GBDy+goq6DH27424mwwoEW4HF0orGLjt4B5uqXb0qFxDUzcrh7WQmPvHGUtw6H3+TtWoDH0d5TrSTEeJmSo3M/KBUq37xxFpOykvjaE7to7+m3HWdMtACPE09SOkcbOpldoH1/lQqlxFgfP7pjIdWt3dz/3H7bccZEC/A4SZ63Ar+BuYVptqMoFXUumpjB56+bxpPbq9iwr8Z2nFHTAjwOjDEkL7iBwvR4MpNibcdRKip9cfl05ham8s2n9lDb1mM7zqhoAR4Hbx1pJCazkHl69quUNbE+Dw/duZjuvkG++vudDPrdv46cFuBx8Pg7lfh7Opieq1++KWXTtNxk7r9lLm8ebuTnWytsxzknLcAXqK69hxf3VtOx92Wd91cpF7h9yQRuXljIj18qp9TlyxhpxbhAj79TSf+goX3Hn21HUUoBIsJ3b5tHUXoCX358J61d7u2apgX4AvQP+vndthNcNT2bgeZTtuMopRwp8TH89GOLqW3r4Rt/3E1g6nH30QJ8ATbtr6WmrYe1l02yHUWdD/EgIiG7qHEyyv+3RRMzqHvpP1m/r4bUiz5wXv9nxRNLgvpP0QkLLsC6N48xISOB62bl2o6izofx8+DG0M0hcO+qmSE7VkQbw/+bMYZndp3Cu+YLfPFfvzfmKWKD/X+mZ8Dn6UBNG9uONnH3shId+aaUS4kIq+bkEe/z8MKeanoH3DVrmhbg8/Tr148R5/Nwx9Ji21GUUiNIjPWxZl4BrT39bC6rc1V7sBbg81DX3sPT753k9qUTyNCRb0q5XlFGAldMzaa8roNdVa224/yFFuDz8Ns3j9Pv9/OZK6fYjqKUGqWLJqYzJTuJ18rrqW7tth0H0AI8Zl19A/zX28e5YU4+k7OTbMdRSo2SiHD9nDyS43y8sKeG7j777cFagMfoD+9W0trdz+eu1rNfpcJNfIyXG+cX0N03yIZ9Ndbbg7UAj8HAoJ9H3jjKkpIMlpSE5yKASkW7vNR4rpmRw/GmLt6xPFRZC/AYPL+nmsqmbj53lZ79KhXO5hWlMis/hbePNHGiqctaDi3AozToN/z05Qpm5qWwak6e7ThKqQsgIiyflUtmUizr99bQ0TNgJYcW4FF6cW81FXUdfHHFNDw68EKpsBfj9fCB+QUM+P28sLfayvzBWoBHwe83/HRzBdNyk1kzr8B2HKXUOMlMimXFrDyqW3t443BDyI+vBXgUNu6v4WBtO19cPk2HHSsVYWbmp7BgQhrvnWihvLY9pMfWAnwOfr/hoc0VTMlO4qYFhbbjKKWC4Krp2eSnxvNSWR3NnX0hO27QCrCI/EpE6kRk77BtmSKySUTKnZ+u78v13O5TlFW38aUV0/XsV6kI5fN4uHF+Pl6P8Oc91fQN+ENy3GCeAf8GWH3atvuAzcaY6cBm57Zr9Q34+dHGQ8wuSOXmhXr2q1QkS4mPYfW8fJo7+9h8oDYkgzSCVoCNMa8Cp/dyvgVY51xfB9warOOPh8feOcGJpi7uWzNLez4oFQUmZiaybGoWh2o72B2CSXtC3QacZ4ypdq7XAGftUCsi94hIqYiU1tfXhybdMB29A/xkczmXT83i6unZIT++UsqOi0symJydxKvl9cQWzgrqsax9CWcC5/dnPcc3xjxsjFlqjFmak5MTwmQBD796hMbOPr6xepYuJ6NUFBmaxD0lPoacW++joaM3aMcKdQGuFZECAOdnXYiPPyqVTV388pXD3LSggIXF6bbjKKVCLD7GywfmFzDY3kRXb/BmTQt1AX4WWOtcXws8E+Ljj8p3ny/DI8L/uHG27ShKKUtyUuKo+a97mZiVGLRjBLMb2mPAW8BMEakSkc8ADwDXi0g5sNK57SqvHqpn/b4avrB8GoXpCbbjKKUiWNBWRTbGfOwsd60I1jEvVN+An28/t49JWYl89qrJtuMopSKcLks/zP//2hGO1Hfy67+7mDif13YcpVSE06HIjoq6dh56qZwb5+dz3cxc23GUUlFACzCBuX6//uRukuK83H/zPNtxlFJRQpsggF+9fpT3TrTw0J2LyEmJsx1HKRUlov4MuKKugx9uPMjK2Xk634NSKqSiugD39A/yhd/tICnOx7/dNk9HvCmlQiqqmyC+8/x+DtS08+u/u5jc1HjbcZRSUSZqz4Bf3FPN/337BPdcPUV7PSilrIjKAlxR18E//XE3C4vT+dqqmbbjKKWiVNQV4JauPj677l3ifB5+9vHFxPqi7iVQSrlEVLUB9w/6+cdHd3CqpYfH7rmUCRnBm2RDKaXOJWoKsDGGbz2zlzcPN/Kj2xeypCTTdiSlVJSLis/fxhgeePEAj71Tyeevm8qHl0ywHUkppaKjAP9sSwW/fPUIdy8r0S/dlFKuEfEF+BevHOaHGw/xocVF3H/zXB1soZRyjYhtAzbG8MD6A/zylSPctKCA739kga5srJRylYgswIN+wz8/vYfH363kE8smcv/N8/Bq8VVKuUxEFuDXyut5/N1KvrR8Gl+9foY2OyilXCkiC/C1M3P50+evYJGuaKyUcrGI/RJOi69Syu0itgADFE8sQURCclFKqbGKyCaIIVWVJ3hw48GQHOte7V+slBqjiD4DVkopN9MCrJRSlmgBVkopS7QAK6WUJVqAlVLKEi3ASilliZUCLCKrReSgiFSIyH02MiillG0hL8Ai4gV+BqwB5gAfE5E5oc6hlFK22TgDvgSoMMYcMcb0AY8Dt1jIoZRSVokxJrQHFPkIsNoY81nn9t3ApcaYL5z2uHuAe5ybM4HhQ9qygYYQxA2GcM2uuUMvXLOHa24Yv+wNxpjV53qQa4ciG2MeBh4+030iUmqMWRriSOMiXLNr7tAL1+zhmhtCn91GE8RJoHjY7QnONqWUiio2CvC7wHQRmSwiscCdwLMWciillFUhb4IwxgyIyBeADYAX+JUxZt8Yn+aMTRNhIlyza+7QC9fs4ZobQpw95F/CKaWUCtCRcEopZYkWYKWUssSVBVhEfiUidSKyd9i234vITudyTER2Drvvm86w5oMicoOd1GfNvUhE3nZyl4rIJc52EZGfOLl3i8hFtnI7ec6UfaGIvCUie0TkORFJHXafW17zYhHZIiL7RWSfiHzZ2Z4pIptEpNz5meFsd8XrPkLu253bfhFZeto+bn/NfyAiB5zX9WkRSR+2j/XsI+T+X07mnSKyUUQKne3B/10xxrjuAlwNXATsPcv9PwK+5VyfA+wC4oDJwGHA65bcwEZgjXP9RmDrsOsvAgIsA7a57TUn0GPlGuf6p4H/5cLXvAC4yLmeAhxy8n0fuM/Zfh/wPTe97iPknk1g4NFWYOmwx4fDa74K8DnbvzfsNXdF9hFypw57zJeAX4Tqd8WVZ8DGmFeBpjPdJ4EVMO8AHnM23QI8bozpNcYcBSoIDHcOubPkNsDQmWMacMq5fgvwWxPwNpAuIgWhSfq3zpJ9BvCqc30T8GHnupte82pjzA7nejtQBhQ5Gdc5D1sH3Opcd8XrfrbcxpgyY8yZFjJ0/WtujNlojBlwHvY2gT7+4JLsI+RuG/awJALvWQjB74orC/A5XAXUGmPKndtFQOWw+6ucbW7xFeAHIlIJ/BD4prPd7bkB9vH+PB238/4AGldmF5FJwGJgG5BnjKl27qoB8pzrrst+Wu6zcV1uGDH7pwmcPYILs5+eW0S+67xH7wK+5Tws6LnDsQB/jPfPfsPBfwO+aowpBr4KPGI5z1h8GvhHEdlO4CNbn+U8ZyUiycAfga+cdkaDCXyedGV/y5Fyu93ZsovIPwMDwKO2so3kTLmNMf/svEcfBb4w0v7jKawKsIj4gA8Bvx+22e1Dm9cCTznXn+D9j15uz40x5oAxZpUxZgmBP3qHnbtclV1EYgi8oR41xgy91rVDHxedn3XOdtdkP0vus3FNbjh7dhH5FHATcJfzhw9clH0Ur/mjvN/UFvTcYVWAgZXAAWNM1bBtzwJ3ikiciEwGpgPvWEl3ZqeAa5zry4GhppNngU8637QuA1qHfWR2BRHJdX56gH8BfuHc5ZrX3PlO4BGgzBjz4LC7niXwxw/n5zPDtlt/3UfIfTauf81FZDXwT8DNxpiuYbu4IvsIuacPe9gtwAHnevB/V0L9TeRoLgTOtqqBfgLtLp9xtv8G+IczPP6fCZydHcTpceCW3MCVwHYC3wJvA5Y4jxUCE9MfBvYw7BtvF2X/MoFvig8BD+CMnHTZa34lgeaF3cBO53IjkAVsJvAH7yUg002v+wi5b3Ne/16gFtgQRq95BYE206Ftv3BT9hFy/xHY62x/jsAXcyH5XdGhyEopZUm4NUEopVTE0AKslFKWaAFWSilLtAArpZQlWoCVUsoSLcBKKWWJFmA1LkTkSyJSJiInReR/O9v+QUQ+aSnPMRHJHufnnCQiHx92+1ND/1alzodrl6VXYecfCYxUXAksBTDG/GLEPS6QM7JJjDH+YB5nmEnAx4Hfheh4KsLpGbC6YCLyC2AKgdmvMoZt/7aIfM25vlVEHnImvd4r709M/20R+S8JTPxeLiKfG7b/10XkXWcy7PudbZOcSb1/S2D00vCx+mfL9wkRecc59i9FxOts73BmwdolgUnz85ztU53be0TkOyLS4TzVA8BVzvN81dlWKCLrnezfP0eODglMWr5PRF4SkUuc1+WIiNzsPOZTIvInCUwif0xEviAi94rIe06mzHP/j6hwoQVYXTBjzD8QmPPiOqB5hIcmGmMWEThb/tWw7QsIzJNxGfAtESkUkVUE5gy4BFgELBGRq53HTwf+jzFmrjHm+EjZRGQ28FHgCufYgwSmHITA3K9vG2MWEpj3eKj4PwQ8ZIyZT2BY8JD7gNeMMYuMMT92ti1ynn8+8FERGekPQhLwsjFmLtAOfAe4nsDw4/857HHzCEw6dTHwXaDLGLMYeAuw0qSjgkObIFQoPQaByd9FJFXeX7LmGWNMN9AtIlsIFN0rCayw8J7zmGQChfcEcNwEJsgejRXAEuDdQIsFCbw/M1of8Gfn+nYCxRACfwiGJnD/HYF5nM9mszGmFUBE9gMl/PUcssP1Aeud63uAXmNMv4jsIdC8MWSLCUwY3i4irQTmJxjaZ8EIWVSY0QKsQun0iUfMCNsF+HdjzC+H3yGBibQ7x3BMAdYZY755hvv6zfuToQxyfu+H3mHXz/Ucw4/nH9rXGON3plo903P6h932n2dG5VLaBKFC6aMAInIlgan9Wp3tt4hIvIhkAdcSWItuA/BpCUyejYgUDU2POUabgY8Mm1ozU0RKzrHP27w/J+ydw7a3E5iYXqlxoX9NVSj1iMh7QAyB1TaG7Aa2ANkEFv48BZxy2m/fcpoOOoBPEDjLHDVjzH4R+RdgozOvcT/weWCktuOvAP9XAis7rAeG/lDsBgZFZBeBqVFHau9W6px0OkoVEiKyFfiaMab0tO3fBjqMMSO1s4aUiCQC3cYYIyJ3Ah8zxtxyrv2UGis9A1bqby0B/rfTz7iFvz5bV2rc6BmwCmsisg2IO23z3caYPTbygDszKXfSAqyUUpZoLwillLJEC7BSSlmiBVgppSzRAqyUUpb8P9VmgCZKDX+IAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(data=penguins, x=\"flipper_length_mm\", kde=\"true\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(tips['total_bill']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are a couple key things about the `displot()` function.  The first is that there is a histogram with certain bins (which we might need to adjust), and there is a smoothed kernel-density estimate (KDE).  You can turn the KDE off like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(tips['total_bill'], kde=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seaborn chooses reasonable bin widths and numbers of bins for you but you can change these things pretty easily.  For example, you can decrease the number of bins:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWAAAAFgCAYAAACFYaNMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAE/JJREFUeJzt3X+wpQV93/H3R1b8nSzoDYPsMksiNaU0onOlCDZDICZrQoW0FrBWNynpmpGk/koImD+YdsYZnWSipmmsW6GsU4pQxEISQ0IRxcYIWfAHIFq3GGA3wF5U1GijXfj2j/MQb9dl97J7n/O9P96vmTv3PM95zrnfZ+by3ofnnvOcVBWSpOl7SvcAkrRaGWBJamKAJamJAZakJgZYkpoYYElqYoAlqYkBlqQmBliSmqzpHuBgbNy4sa6//vruMSRpT1nIRsv6CPjhhx/uHkGSDtiyDrAkLWcGWJKaGGBJamKAJamJAZakJgZYkpoYYElqYoAlqYkBlqQmowU4yaVJdiW5cy/3vS1JJXnesJwkv5dke5LPJ3nJWHNJ0lIx5hHwZcDGPVcmWQ/8DHDfvNWvBI4dvjYD7xtxLklaEkYLcFXdDHxtL3e9G7gAqHnrzgQ+WBOfBtYmOXKs2SRpKZjq1dCSnAnsrKrPJf/fxYKOAu6ft7xjWPfAXp5jM5OjZI4++ugDmuOo9Ufz1zvu3/+GOmDPX7eenffft/8NpVVsagFO8kzg7UxOPxywqtoCbAGYnZ2t/Wy+V3+9437Oef+nDmYM7ceVbzi5ewRpyZvmEfCPAccAjx/9rgNuT3IisBNYP2/bdcM6SVqxpvYytKq6o6p+pKo2VNUGJqcZXlJVDwLXAa8fXg1xEvCNqvqB0w+StJKM+TK0K4C/AF6YZEeS8/ax+UeBe4DtwH8C3jjWXJK0VIx2CqKqXrOf+zfMu13A+WPNIklLke+Ek6QmBliSmhhgSWpigCWpiQGWpCYGWJKaGGBJamKAJamJAZakJgZYkpoYYElqYoAlqYkBlqQmBliSmhhgSWpigCWpiQGWpCYGWJKaGGBJamKAJamJAZakJgZYkpoYYElqYoAlqYkBlqQmBliSmhhgSWpigCWpiQGWpCYGWJKaGGBJamKAJanJaAFOcmmSXUnunLfut5N8Mcnnk3wkydp5912UZHuSLyX52bHmkqSlYswj4MuAjXusuwE4vqp+AvhfwEUASY4DzgX+wfCYP0hyyIizSVK70QJcVTcDX9tj3Z9V1e5h8dPAuuH2mcCHquq7VfUVYDtw4lizSdJS0HkO+F8BfzLcPgq4f959O4Z1krRitQQ4yW8Bu4HLD+Cxm5NsS7Jtbm5u8YeTpCmZeoCT/CJwBvDaqqph9U5g/bzN1g3rfkBVbamq2aqanZmZGXVWSRrTVAOcZCNwAfCqqvrOvLuuA85N8rQkxwDHArdOczZJmrY1Yz1xkiuAU4HnJdkBXMzkVQ9PA25IAvDpqvqVqroryVXAF5icmji/qh4dazZJWgpGC3BVvWYvqy/Zx/bvAN4x1jyStNT4TjhJamKAJamJAZakJgZYkpoYYElqYoAlqYkBlqQmBliSmhhgSWpigCWpiQGWpCYGWJKaGGBJamKAJamJAZakJgZYkpoYYElqYoAlqYkBlqQmBliSmhhgSWpigCWpiQGWpCYGWJKaGGBJamKAJamJAZakJgZYkpoYYElqYoAlqYkBlqQmBliSmhhgSWoyWoCTXJpkV5I75607PMkNSb48fD9sWJ8kv5dke5LPJ3nJWHNJ0lIx5hHwZcDGPdZdCNxYVccCNw7LAK8Ejh2+NgPvG3EuSVoSRgtwVd0MfG2P1WcCW4fbW4Gz5q3/YE18Glib5MixZpOkpWDa54CPqKoHhtsPAkcMt48C7p+33Y5h3Q9IsjnJtiTb5ubmxptUkkbW9ke4qiqgDuBxW6pqtqpmZ2ZmRphMkqZj2gF+6PFTC8P3XcP6ncD6edutG9ZJ0oo17QBfB2wabm8Crp23/vXDqyFOAr4x71SFJK1Ia8Z64iRXAKcCz0uyA7gYeCdwVZLzgHuBs4fNPwr8HLAd+A7wS2PNJUlLxWgBrqrXPMFdp+9l2wLOH2sWSVqKfCecJDUxwJLUxABLUhMDLElNDLAkNTHAktTEAEtSEwMsSU0MsCQ1McCS1MQAS1ITAyxJTQywJDUxwJLUxABLUhMDLElNDLAkNTHAktTEAEtSk9E+E06r3FPWkKR7ihXt+evWs/P++7rH0EEwwBrHY7s55/2f6p5iRbvyDSd3j6CD5CkISWpigCWpiQGWpCYGWJKaGGBJamKAJamJAZakJgZYkpoYYElqYoAlqYkBlqQmLQFO8pYkdyW5M8kVSZ6e5JgktyTZnuTKJId2zCZJ0zL1ACc5Cvg3wGxVHQ8cApwLvAt4d1W9APg6cN60Z5Okaeo6BbEGeEaSNcAzgQeA04Crh/u3Amc1zSZJUzH1AFfVTuB3gPuYhPcbwG3AI1W1e9hsB3DU3h6fZHOSbUm2zc3NTWNkSRrFggKc5JSFrFvgcx0GnAkcAzwfeBawcaGPr6otVTVbVbMzMzMHMoIkLQkLPQL+9wtctxA/DXylquaq6v8C1wCnAGuHUxIA64CdB/j8krQs7PMTMZK8DDgZmEny1nl3/RCTP54diPuAk5I8E/g/wOnANuAm4NXAh4BNwLUH+PyStCzs7wj4UODZTEL9nHlf32QSyyetqm5h8se224E7hhm2AL8JvDXJduC5wCUH8vyStFzs8wi4qj4BfCLJZVV172L90Kq6GLh4j9X3ACcu1s+QpKVuoR/K+bQkW4AN8x9TVaeNMZQkrQYLDfB/A/4j8AHg0fHGkaTVY6EB3l1V7xt1EklaZRb6MrQ/TPLGJEcmOfzxr1Enk6QVbqFHwJuG778xb10BP7q440jS6rGgAFfVMWMPIkmrzYICnOT1e1tfVR9c3HEkafVY6CmIl867/XQm7167HTDAknSAFnoK4tfmLydZy+Qtw5KkA3Sgl6P8NpOrmUmSDtBCzwH/IZNXPcDkIjx/H7hqrKEkaTVY6Dng35l3ezdwb1XtGGEeSVo1FnQKYrgozxeZXAntMOB7Yw4lSavBQj8R42zgVuCfA2cDtyQ5oMtRSpImFnoK4reAl1bVLoAkM8D/4PsfoilJepIW+iqIpzwe38FXn8RjJUl7sdAj4OuT/ClwxbB8DvDRcUaSpNVhf58J9wLgiKr6jST/FHj5cNdfAJePPZwkrWT7OwJ+D3ARQFVdw+QTjEnyD4f7/smo00nSCra/87hHVNUde64c1m0YZSJJWiX2F+C1+7jvGYs5iCStNvsL8LYk/3rPlUl+GbhtnJEkaXXY3zngNwMfSfJavh/cWeBQ4BfGHEySVrp9BriqHgJOTvJTwPHD6j+uqo+NPpkkrXALvR7wTcBNI88iSauK72aTpCYGWJKaGGBJamKAJamJAZakJgZYkpoYYElq0hLgJGuTXJ3ki0nuTvKyJIcnuSHJl4fvh3XMJknT0nUE/F7g+qr6ceBFwN3AhcCNVXUscOOwLEkr1tQDnOSHgZ8ELgGoqu9V1SPAmcDWYbOtwFnTnk2SpqnjCPgYYA74z0k+k+QDSZ7F5NrDDwzbPAgcsbcHJ9mcZFuSbXNzc1MaWZIWX0eA1wAvAd5XVS8Gvs0epxuqqoDa24OraktVzVbV7MzMzOjDStJYOgK8A9hRVbcMy1czCfJDSY4EGL7veoLHS9KKMPUAV9WDwP1JXjisOh34AnAdsGlYtwm4dtqzSdI0LfRj6RfbrwGXJzkUuAf4JSb/GFyV5DzgXuDsptkkaSpaAlxVn2XyyRp7On3as0hSF98JJ0lNDLAkNTHAktTEAEtSEwMsSU0MsCQ1McCS1MQAS1ITAyxJTQywJDUxwJLUxABLUhMDLElNDLAkNTHAktTEAEtSEwMsSU0MsCQ1McCS1MQAS1ITAyxJTQywJDUxwJLUxABLUhMDLElNDLAkNTHAktTEAEtSEwMsSU0MsCQ1McCS1MQAS1KTtgAnOSTJZ5L80bB8TJJbkmxPcmWSQ7tmk6Rp6DwCfhNw97zldwHvrqoXAF8HzmuZSpKmpCXASdYBPw98YFgOcBpw9bDJVuCsjtkkaVq6joDfA1wAPDYsPxd4pKp2D8s7gKP29sAkm5NsS7Jtbm5u/EklaSRTD3CSM4BdVXXbgTy+qrZU1WxVzc7MzCzydJI0PWsafuYpwKuS/BzwdOCHgPcCa5OsGY6C1wE7G2aTpKmZ+hFwVV1UVeuqagNwLvCxqnotcBPw6mGzTcC1055NkqZpKb0O+DeBtybZzuSc8CXN80jSqDpOQfydqvo48PHh9j3AiZ3zSNI0LaUjYElaVQywJDUxwJLUxABLUhMDLElNDLAkNTHAktTEAEtSEwMsSU0MsCQ1McCS1MQAS1ITAyxJTQywJDUxwJLUxABLUhMDLElNDLAkNTHAktTEAEtSEwMsSU0MsCQ1McCS1MQAS1ITAyxJTQywJDUxwJLUxABLUhMDLElNDLAkNTHAktTEAEtSk6kHOMn6JDcl+UKSu5K8aVh/eJIbknx5+H7YtGeTpGnqOALeDbytqo4DTgLOT3IccCFwY1UdC9w4LEvSijX1AFfVA1V1+3D7W8DdwFHAmcDWYbOtwFnTnk2Spqn1HHCSDcCLgVuAI6rqgeGuB4EjmsaSpKloC3CSZwMfBt5cVd+cf19VFVBP8LjNSbYl2TY3NzeFSSVpHC0BTvJUJvG9vKquGVY/lOTI4f4jgV17e2xVbamq2aqanZmZmc7AkjSCjldBBLgEuLuqfnfeXdcBm4bbm4Brpz2bJE3TmoafeQrwOuCOJJ8d1r0deCdwVZLzgHuBsxtmk6SpmXqAq+p/AnmCu0+f5iyS1Ml3wklSEwMsSU0MsCQ16fgjnKTF8JQ1TF5UpDE9f916dt5/3yjPbYCl5eqx3Zzz/k91T7HiXfmGk0d7bk9BSFITAyxJTQywJDUxwJLUxABLUhMDLElNDLAkNTHAktTEAEtSEwMsSU0MsCQ1McCS1MQAS1ITAyxJTQywJDUxwJLUxABLUhMDLElNDLAkNTHAktTEAEtSEwMsSU0MsCQ1McCS1MQAS1ITAyxJTQywJDUxwJLUZMkFOMnGJF9Ksj3Jhd3zSNJYllSAkxwC/AfglcBxwGuSHNc7lSSNY0kFGDgR2F5V91TV94APAWc2zyRJo0hVdc/wd5K8GthYVb88LL8O+EdV9avzttkMbB4WXwh8aeqDjut5wMPdQ4zI/Vve3L+FebiqNu5vozWL8IOmqqq2AFu65xhLkm1VNds9x1jcv+XN/VtcS+0UxE5g/bzldcM6SVpxllqA/xI4NskxSQ4FzgWua55JkkaxpE5BVNXuJL8K/ClwCHBpVd3VPNa0rdjTKwP3b3lz/xbRkvojnCStJkvtFIQkrRoGWJKaGOAmSS5NsivJnfPWHZ7khiRfHr4f1jnjwUiyPslNSb6Q5K4kbxrWr4h9TPL0JLcm+dywf/92WH9MkluGt9JfOfwxedlKckiSzyT5o2F5pe3fXyW5I8lnk2wb1k3td9QA97kM2POF2hcCN1bVscCNw/JytRt4W1UdB5wEnD+8rXyl7ON3gdOq6kXACcDGJCcB7wLeXVUvAL4OnNc442J4E3D3vOWVtn8AP1VVJ8x7/e/UfkcNcJOquhn42h6rzwS2Dre3AmdNdahFVFUPVNXtw+1vMfmP+ChWyD7WxN8Mi08dvgo4Dbh6WL9s9w8gyTrg54EPDMthBe3fPkztd9QALy1HVNUDw+0HgSM6h1ksSTYALwZuYQXt4/C/558FdgE3AP8beKSqdg+b7GDyj85y9R7gAuCxYfm5rKz9g8k/mn+W5LbhMgcwxd/RJfU6YH1fVVWSZf8awSTPBj4MvLmqvjk5iJpY7vtYVY8CJyRZC3wE+PHmkRZNkjOAXVV1W5JTu+cZ0curameSHwFuSPLF+XeO/TvqEfDS8lCSIwGG77ua5zkoSZ7KJL6XV9U1w+oVtY8AVfUIcBPwMmBtkscPbJbzW+lPAV6V5K+YXJXwNOC9rJz9A6Cqdg7fdzH5R/REpvg7aoCXluuATcPtTcC1jbMclOF84SXA3VX1u/PuWhH7mGRmOPIlyTOAVzA5z30T8Ophs2W7f1V1UVWtq6oNTC4J8LGqei0rZP8AkjwryXMevw38DHAnU/wd9Z1wTZJcAZzK5PJ3DwEXA/8duAo4GrgXOLuq9vxD3bKQ5OXAJ4E7+P45xLczOQ+87PcxyU8w+QPNIUwOZK6qqn+X5EeZHDEeDnwG+JdV9d2+SQ/ecAri16vqjJW0f8O+fGRYXAP816p6R5LnMqXfUQMsSU08BSFJTQywJDUxwJLUxABLUhMDLElNDLAkNTHAWpaSrE3yxv1ssyHJv1jAc22Yf1nQvdz/i0l+/wnu+9Sez5Hk1Mcv3yjtiwHWcrUW2GeAgQ3AfgN8MKrq5DGfXyubAdZy9U7gx4YLaf/28HXncHHtc+Zt84+Hbd4yHKV+Msntw9eTief6JB8fLtJ98eMrk/zNvh4k7YtXQ9NydSFwfFWdkOSfAb8CvIjJW7v/MsnNwza/XlVnACR5JvCKqvrbJMcCVwCze3/6H3AicDzwneH5/7iqti3uLmm1McBaCV4OXDFcHvKhJJ8AXgp8c4/tngr8fpITgEeBv/ckfsYNVfVVgCTXDD/TAOugGGCtJm9hcuGjFzE5/fa3T+Kxe140xYuo6KB5DljL1beA5wy3PwmcM3xCxQzwk8Cte2wD8MPAA1X1GPA6JlcyW6hXDB/W+AwmH1Hz5we7A5JHwFqWquqrSf58eOnXnwCfBz7H5Mj0gqp6MMlXgUeTfI7Jh6D+AfDhJK8Hrge+/SR+5K1MLi6/Dvgvnv/VYvBylJLUxFMQktTEUxDSIMnPAu/aY/VXquoXOubRyucpCElq4ikISWpigCWpiQGWpCYGWJKa/D8PqN/3dwNgZQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(tips['total_bill'], kde=False, bins=3);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or increase them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(tips['total_bill'], kde=False, bins=50);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also specify them directly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(tips['total_bill'], kde=False, bins=np.linspace(0,100,20));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This later example uses `np.linspace()` to create a set of 20 bins ranging from zero 0 to 100.  This goes far past the largest observation we have (around 50) but can be useful in cases where you expected such observation to occur.\n",
    "\n",
    "The full set of options for the `displot` command is [here](https://seaborn.pydata.org/generated/seaborn.distplot.html). Most of it makes sense and is easy to read but one in particularly you might be interested in is `norm_hist` option which can be `True` or `False` (it is false by default for all the examples we've done so far).  This adjust things so instead of showing the **number** of values that fall in a given bin is shows a density (more or less the fraction of total points that fall in the bin).  This can be useful in some circumstances."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want to combine more than one histogram into the same plot you can provide the different datasets in a list it will combine the data on the same axes.  Here is an example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x12691e240>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 402.375x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.random.normal(0,1,size=100) # zero centered normal distribution\n",
    "y = np.random.normal(3,1,size=100) # shift this one over\n",
    "sns.displot([x,y])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bivariate histograms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One generalization of a histogram is to consider the relationship between two variables.  One version of this we have already encountered (the scatterplot).  We can augment our scatterplots with histograms on the margins (sides) of the figure.  This lets us see the distribution of both the x and y values while also seeing how the two variables relate to one another."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# make some data\n",
    "mean, cov = [0, 1], [(1, .5), (.5, 1)]\n",
    "data = np.random.multivariate_normal(mean, cov, 200)\n",
    "df = pd.DataFrame(data, columns=[\"x\", \"y\"])\n",
    "\n",
    "sns.jointplot(x=\"x\", y=\"y\", data=df);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One generalization of a univariate histogram is the hexbin.  The hexbin divides the entire plot space into a tiling of hexagonal shapes and then counts how many of the scatter points fall in that cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x, y = np.random.multivariate_normal(mean, cov, 1000).T\n",
    "with sns.axes_style(\"white\"):\n",
    "    sns.jointplot(x=x, y=y, kind=\"hex\", color=\"k\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is pretty cool looking!\n",
    "\n",
    "Maybe even more futuristic is the kernel density estimator applied in two dimensions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x=\"x\", y=\"y\", data=df, kind=\"kde\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This give you something that looks like a elevation map or terain over which parts of the figure have the most data (i.e., which combinations of the x and y are common)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pairwise relationship plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So far we have mostly consider univariate plots like a histogram or bivariate plots (as in the previous section).  However many dataset have many, many variables.  We want to visualize them all!  The problem is that when you get more than 2 dimensions it starts requiring three dimensional plots and when we go above three dimensions it can be hard to visualize things.  One approach for multivariate data is to look at all combinations of the pairwise relationships.  This can be done easily in seaborn with the `sns.pairplot()` figure level function.  Let's look at the classic `iris` dataset which includes a number of features of common iris flowers:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   sepal_length  sepal_width  petal_length  petal_width species\n",
       "0           5.1          3.5           1.4          0.2  setosa\n",
       "1           4.9          3.0           1.4          0.2  setosa\n",
       "2           4.7          3.2           1.3          0.2  setosa\n",
       "3           4.6          3.1           1.5          0.2  setosa\n",
       "4           5.0          3.6           1.4          0.2  setosa"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris = sns.load_dataset(\"iris\")\n",
    "iris.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following plots shows scatter plots of each continuous feature (sepal_length, sepal_width, petal_length, petal_width) against every other in a matrix.  In addition, on the diagonal it has plotted the univariate histogram (instead of a plots of x versus x which would always look like a line)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(iris);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This function includes the hue semantics making quite interesting and rich plots:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 806.85x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(iris, hue=\"species\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Linear relationships"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The last type of plot we will consider involves adding to the plot some type of statistical model.  This most interesting in the case of scatterplots.  When we plot a scatterplot we are often interested in the strength of the relationship between two variables.  However, when there is a lot of noise in a dataset it can be hard to see this relationship and so we often turn to models such as linear regression to assess the relationship.  \n",
    "\n",
    "A full discussion of linear regression will need to wait until a later chapter.  However, it is helpful to know that seaborn has a variety of scatterplots that also will fit and display a linear regression on your data.  If you remember we made scatterplots using `sns.replot()`.  To instead explore the regression form of the plot use `sns.lmplot()`.\n",
    "\n",
    "Let's go back to the `tips` data set we considered earlier:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x=\"total_bill\", y=\"tip\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also plot a linear relationship with ordered factors (like the size of the party):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x=\"size\", y=\"total_bill\", x_jitter=.05, data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " Here we can clearly see how the total bill goes up as the number of people in the party increases.  The linear regression line here is useful because of the large number of 2 party tables.  We might not be able to make sense of that big cloud of points visually but the regression helps us understand it better."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally you can very easily plot different regression lines by grouping the data based on another factor (in this case smoker status):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 418.459x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x=\"total_bill\", y=\"tip\", hue=\"smoker\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is quite powerful because in one line you can actually compare the strength of the linear relationship within two subsets of the data.  There are a lot more options and details to the `lmplot()` functions but we will end here and instead refer you to the [seaborn tutorial on visualizing linear relationships. for more information](https://seaborn.pydata.org/tutorial/regression.html).  The important goal for this chapter is to just raise your awareness of the options and plot types."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving Figures"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When you have a plot that you like in your jupyter notebook you often then want to include it in a presentation or a paper.   One way to do this is to simply click on the image in jupyter and select \"save image as...\" and it will save to a location you choose.  However, a slightly better way, allowing more control over the file type is to call the seaborn `savefig()` function.  Here is an example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 418.459x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "myfig = sns.lmplot(x=\"total_bill\", y=\"tip\", hue=\"smoker\", data=tips);\n",
    "myfig.savefig('smoking_tips.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This will explore to the same folder as your notebook a PNG (portable network graphics) version of the file.  This actually calls the matplotlib `savefig` function which is documented [here](https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.savefig.html).  You can choose a variety of file types includeing PNG, JPG, TIFF, or PDF.  In addition there are options to adjust the dots per inch in the figure which can be needed for high quality printing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating Figures for Presentations and Publications versus Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We conclude this chapter with a short discussion about the difference between creating figures for exploratory data analysis and for presentation/communication to others.  When we are using a tool like seaborn to perform exploratory data analysis we tend to let the default options of seaborn go and not worry too much about the details of our figures.  The key is here being quick and having very short, readable code for analyzing and exploring.\n",
    "\n",
    "However, when we come to a final conclusion about a dataset, perhaps backed up by statistics, we often have to choose from one of several plots to include in a paper or presentation about our data.  These are often the most important or interesting results that we want to tell others about.  In this case, it is helpful to do several extra steps to prepare for publication-quality images.  For example, the default font size in seaborn is quite small.  When you are working in a Jupyter notebook this is not problem.  However, if you present a seaborn plot directly on a projector in a slide presentation it can be hard to read the axis labels.  In addition, by default seaborn uses the names of columns of a data frame as axis labels:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 418.459x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x=\"total_bill\", y=\"tip\", hue=\"smoker\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since we are familiar with the `tips` dataframe we know what `total_bill` is and the assumed units (dollars? cents?).  However in a presentation we can't count on a audience member knowing these things or keeping track of them in their mind.  As a result we usually want to make a figure more clear, using thicker lines and larger fonts.\n",
    "\n",
    "Interesting seaborn can help with this as well with a method call `set_context()`.  There are several pre-set context including `paper`, `notebook`, `talk`, and `poster`.  `notebook` theme is the default we have been using, so we don't need to explore that one.  Let's examine how each of these other context alter the plot above."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The `paper` theme"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The paper theme makes the axis and legend features even smaller which might be ok when printed out on a higher resolution pdf."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 406.805x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"paper\")\n",
    "sns.lmplot(x=\"total_bill\", y=\"tip\", hue=\"smoker\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The `talk` theme"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The talk theme makes the dots and lines thicker and increases the font size for being projected on a wall or large lower resolution screen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 447.884x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"talk\")\n",
    "sns.lmplot(x=\"total_bill\", y=\"tip\", hue=\"smoker\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The `poster` theme"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The poster theme makes the dots and lines even thicker than the talk theme!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 477.044x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"poster\")\n",
    "sns.lmplot(x=\"total_bill\", y=\"tip\", hue=\"smoker\", data=tips);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition to changing the visibility of these elements for higher and lower resolution output devices it also makes sense in a communicative setting to make the axis labels human-readable.  We often do that using matplotlib functions to change the axis labels:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x126ab0e10>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 447.884x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"talk\")\n",
    "g=sns.lmplot(x=\"total_bill\", y=\"tip\", hue=\"smoker\", data=tips);\n",
    "g.set_axis_labels(\"Total bill (dollars)\", \"Tip (dollars)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, you might not take the time to make these changes while doing exploratory analysis in the Jupyter notebook but when you decide a graph is important enough to communicate to someone else, you often want to make some changes to it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```{warning}\n",
    "If you remember from a previous chapter the mantra for the course is **do everything in code**.  This applies to creating figures as well.  It is not a good practice to generate figures in Jupyter/seaborn and then export them and edit them in photoshop or illustrator or another drawing program.  Although this offers even more customization and can be easier than struggling with the seaborn/matplotlib documentation to figure out how to do something, it leads to figures which are not easy to replicate by someone and can introduce distortions and modifications of the data which are misleading.  If you do everything in code there is always a trail of how things were made and that can be verified by someone else!\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Moving Data - Animations and Interactive Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So far we have focused on plots that fig in a single graphic or across multiple panels of a graphic.  This makes sense because at least until recently academic papers are largely static documents with words and pictures.  However, this is changing and unlikely to be true for very long and of course in a presentation you can include movies and animations to help grab the attention of your audience.  We will talk about this as \"moving data\" because we can change aspects of a plot over time by plotting different data or changing the mapping between data point and visual features of a plot over time.\n",
    "\n",
    "One of the most famous talks that makes use of animated plots is the [TED Talk](https://www.ted.com/talks) by [Hans Rosling](https://en.wikipedia.org/wiki/Hans_Rosling).  Watch it here and then test your understanding by trying to answer a few comprehension questions.\n",
    "\n",
    "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/usdJgEwMinM\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n",
    "\n",
    "\n",
    "```{admonition} Test yourself: Why is using average data within countries \"dangerous\"?\n",
    ":class: hint\n",
    "- The values are hard to measure and therefore unreliable\n",
    "- The world is changing\n",
    "- The within-country variance in outcomes is influenced by income distribution\n",
    "```\n",
    "```{admonition} Click the button to reveal the answer!\n",
    ":class: dropdown\n",
    "Hans shows at [this timepoint](https://youtu.be/usdJgEwMinM?t=835) that within countries the richest and poorest people have significant differences in child survival.\n",
    "```\n",
    "\n",
    "\n",
    "\n",
    "```{admonition} Test yourself: What is the mistaken understanding of the world exhibited by Hans' students?\n",
    ":class: hint\n",
    "- The developed world has small families and long lives and developing world has large families and short lives\n",
    "- The change in laws in the middle east influenced life expectancies\n",
    "- Opening the Chinese economy improved life expectancy\n",
    "```\n",
    "```{admonition} Click the button to reveal the answer!\n",
    ":class: dropdown\n",
    "Hans describes the general incorrect assumption of this students about the developed world having small families and long lives while the developing world has large families and short lives [this timepoint](https://youtu.be/usdJgEwMinM?t=188).  His animations show this is changing quickly and there are important individual countries and regional differences.\n",
    "```\n",
    "\n",
    "The reason the video by Rosling is so famous is that the nature of his dynamic visualizations help people understand how the world is changing over the last several decades.  These plots challenge people's stereotypes about parts of the world and help them see better the nuance between the impacts of development and public health."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Making animations  and interactive plots in Python and Jupyter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Completely describing how to make animation and interactive visualization in Python is beyond the scope of this course unfortunately.  There are lots of software packages that help with this and also several different approaches that you might want to use if, for instance, you mainly want a interactive visualization for use in Jupyter (to aid your data analysis) versus including in a talk.  However, I will quickly show two code snippets that let you make animations and interactive plots."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you are interested in making a bunch of seaborn or matplotlib plots and then animating them like a flip book the [Celluloid package](https://github.com/jwkvam/celluloid) can help.  The basic idea if that you make a \"camera\" object and snap a photo of each frame of your movie, each time replotting your figure.  The library then animates it and can explore it is a movie."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "from celluloid import Camera\n",
    "\n",
    "fig, axes = plt.subplots()\n",
    "camera = Camera(fig)\n",
    "for _ in range(50):\n",
    "    north_pole = npr.uniform(1,10,10)\n",
    "    south_pole = npr.uniform(1,10,10)\n",
    "    sns.regplot(north_pole, south_pole, ci=None, ax=axes)\n",
    "    plt.xlim([0,10])\n",
    "    plt.ylim([0,10])\n",
    "    camera.snap()\n",
    "\n",
    "animation = camera.animate()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then to display the animation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\">\n",
       "  Your browser does not support the video tag.\n",
       "</video>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(HTML(animation.to_html5_video()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then to save the movie to a file for like a talk you can do:\n",
    "`animation.save('animation.mp4')`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another approach to making plots is to make them more interactive.  This is useful if you are sharing your Jupyter notebook with some so they can access a Jupyter kernel (these interactive elements do not easily run outside of the notebook interface).  To learn more about this read about the [ipywidgets](https://ipywidgets.readthedocs.io/en/stable/) library."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Further Reading and Resources\n",
    "\n",
    "- A create and comprehensive [seaborn tutorial](https://seaborn.pydata.org/tutorial.html)\n",
    "- [Data visualization: A practical introduction](https://socviz.co)\n",
    "- Another approach to [creating animated graphs in python](https://towardsdatascience.com/how-to-create-animated-graphs-in-python-bb619cc2dec1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "\n",
    "```{bibliography} ../../references.bib\n",
    ":filter: docname in docnames\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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