BasicNumpy_ans.ipynb

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   "source": [
    "# Numpy Practice - Answers"
   ]
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   "source": [
    "## Step 1\n",
    "- import numpy, pandas, matplotlib, \n",
    "- Initialize a numpy array with the integers: 1, 2, 3, 4 - call it dat1\n",
    "- Initialize a numpy array with the integers: 5, 6, 7, 8 - call it dat2"
   ]
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   "source": [
    "# Imports\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
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   "source": [
    "# Define the arrays\n",
    "dat1 = np.array([1, 2, 3, 4])\n",
    "dat2 = np.array([5, 6, 7, 8])"
   ]
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   "source": [
    "## Step 2\n",
    "\n",
    "- Combine dat1 & dat2 into a new array, with shape [2, 4]\n",
    "- Call the new array dat3\n",
    "- Print out the shape of the new array"
   ]
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   "source": [
    "# Stack the arrays, vertically\n",
    "dat3 = np.vstack([dat1, dat2])"
   ]
  },
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   "cell_type": "code",
   "execution_count": 7,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 4)"
      ]
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     "execution_count": 7,
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   "source": [
    "# Check the array shape\n",
    "dat3.shape"
   ]
  },
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   "cell_type": "code",
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       "(2, 4)"
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   "source": [
    "# Or, this is another way to get the shape\n",
    "np.shape(dat3)"
   ]
  },
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   "source": [
    "## Step 3\n",
    "- Find the average across the columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2.5,  6.5])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
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    }
   ],
   "source": [
    "# Use the np.mean function, specifying which axis to operate across\n",
    "np.mean(dat3, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2.5,  6.5])"
      ]
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     "execution_count": 25,
     "metadata": {},
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   "source": [
    "# Alternatively, you can access 'mean' as a method available to the array object\n",
    "dat3.mean(axis=1)"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 4\n",
    "- Find all of the elements in 'dat3' that are divisible by three.\n",
    "- Hint: your answer for this can / should be a boolean array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
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   "source": [
    "# Create a boolean array indicating whether each element is evenly divisible by 3\n",
    "inds = dat3 % 3 == 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 5\n",
    "- Use your answer from step 4 to extract the values from 'dat3'"
   ]
  },
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   "cell_type": "code",
   "execution_count": 30,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 6])"
      ]
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     "execution_count": 30,
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   ],
   "source": [
    "# Index into 'dat3' with the boolean array\n",
    "dat3[inds]"
   ]
  }
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