{
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  {
   "cell_type": "markdown",
   "id": "6073eb74",
   "metadata": {},
   "source": [
    "# In Class Activity - Python - More for-loops and numpy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd755d44",
   "metadata": {},
   "source": [
    "### Problem 0: A more complex for-loop over a dictionary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67e11322",
   "metadata": {},
   "source": [
    "Here is a dictionary `purchases` that records a series of purchases, broken down into different categories. Each category is a list of the relevant purchases under that category."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fb934ead",
   "metadata": {},
   "outputs": [],
   "source": [
    "purchases = {}\n",
    "purchases['entertainment'] = [100., 50.50, 22.12]\n",
    "purchases['food'] = [5.45, 1.20, 65.20, 5.99, 12.23]\n",
    "purchases['transportation'] = [24.20, 26.11, 5.03, 9.99]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce17ffbc",
   "metadata": {},
   "source": [
    "Write a nested for-loop to compute the total cost of all the purchases. Alternatively, you can use the python `sum` function and a single for-loop."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b37b0b1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# your answer goes here, after this comment"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0c2970a",
   "metadata": {},
   "source": [
    "### Problem 1: Using numpy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b90d30d",
   "metadata": {},
   "source": [
    "The code below imports numpy and creates a random matrix `A` with 5 rows and 4 columns. The entries in `A` are uniform random samples from $0,\\dots,2$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6182e6a2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import numpy.random as npr\n",
    "\n",
    "A = npr.randint(0,3,size=(5,4))\n",
    "A"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "062cb464",
   "metadata": {},
   "source": [
    "Use numpy to compute the sum of each column (google the numpy function for `sum`)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1e9dc7f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your answer here"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b73c8c0",
   "metadata": {},
   "source": [
    "Use numpy to compute the sum of each row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "24f922bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your answer here"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d0b174f",
   "metadata": {},
   "source": [
    "Use numpy to compute the overall sum across the entire matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0f222f73",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your answer here"
   ]
  }
 ],
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