correlation-and-clustering-with-pandas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6a56054a",
   "metadata": {},
   "source": [
    "# Correlation and clustering with Pandas\n",
    "\n",
    "By [Allison Parrish](https://www.decontextualize.com/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1e17378d",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "plt.rcParams[\"figure.figsize\"] = (10, 4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6b37550",
   "metadata": {},
   "source": [
    "But first, a little digression!\n",
    "\n",
    "## Making up data\n",
    "\n",
    "Sometimes it's useful to be able to make up some fake \"toy\" data, as a way of testing out different visualization techniques or statistical calculations that we're interested in. Finding the \"perfect\" dataset for experimenting with something can be kind of a drag. You could just type in a bunch of numbers, but why go to all that effort? That's what we have computers for, after all.\n",
    "\n",
    "### Lines\n",
    "\n",
    "So I'm going to show you a handful of functions in the `numpy` library (which we imported above) that make it easy to make up fake data. The first is `np.linspace()`, which generates an array of numbers across a range, evenly spaced. The first parameter is the beginning of the range, the second parameter is the end of the range (inclusive), and the final number is how many numbers to generate. For example, the following generates an array of numbers starting at 10, ending at 50, with 17 evenly-spaced elements:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1383786f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([10. , 12.5, 15. , 17.5, 20. , 22.5, 25. , 27.5, 30. , 32.5, 35. ,\n",
       "       37.5, 40. , 42.5, 45. , 47.5, 50. ])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.linspace(10, 50, 17)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94cc5673",
   "metadata": {},
   "source": [
    "We can easily turn this into a Pandas series and draw a graph to see what it looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3d126a0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.Series(np.linspace(10, 50, 17)).plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "969e7859",
   "metadata": {},
   "source": [
    "### Noise\n",
    "\n",
    "Another helpful function is `np.random.uniform()`, which generates a sequence of random numbers (drawn from a uniform distribution). The first parameter to this function is the bottom of the range of random numbers, and the second is the top of the range. The `size` parameter specifies how many numbers we want. For example, the following cell gives us twenty-five random numbers between -10 and 10:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f4df7b8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-5.90736281, -9.71567398,  9.15083346, -5.62880999,  7.62551047,\n",
       "        2.3064266 ,  1.94754784,  1.88023417,  0.69939609, -0.68291035,\n",
       "       -1.65675312, -6.82421261,  8.39791431,  5.89168559,  6.46876198,\n",
       "        8.71838307, -0.45231008,  9.92317873,  3.32899491, -0.68545617,\n",
       "        5.39297569,  5.91665654,  3.17238783,  3.64167337, -7.13028274])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.uniform(-10, 10, size=25)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16562f5d",
   "metadata": {},
   "source": [
    "Plotted as a Pandas series:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c2679fdc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.Series(np.random.uniform(-10, 10, size=25)).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "282d9cbc",
   "metadata": {},
   "source": [
    "Both `linspace` and `random` return `numpy` arrays, which you can use in mathematical expressions. In particular, adding two numpy arrays together results in the element-wise sum of the two arrays (but note that the arrays need to have the same length). Using this property, we can generate a sequence of numbers with `np.linspace()` and add a bit of \"noise\" to it with `np.random.uniform()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c156b46f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "noisy_line = np.linspace(0, 100, 25) + np.random.uniform(-5, 5, size=25)\n",
    "pd.Series(noisy_line).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cf6e7ea",
   "metadata": {},
   "source": [
    "(Larger numbers in `np.random.uniform()` will increase the amount of \"noise.\")\n",
    "\n",
    "### Periodic\n",
    "\n",
    "We can create data that looks like it has repeating patterns with `np.sin()`. This function takes the sine of each value in the array that you pass as a parameter. Remember from your trigonometry class that $sin(0)$ is 0; $sin(\\frac{\\pi}{2})$ is 1; $sin(\\pi)$ is 0 again; $sin(\\frac{3}{2}\\pi)$ is -1, and $sin(2\\pi)$ is zero again, and those points are connected with a pleasant curvy line. Calling `np.sin()` on the value returned from `np.linspace()` generates a repeating pattern of peaks and valleys.\n",
    "\n",
    "For example, the following is one \"cycle\" of $sin()$. Note how it starts at zero, gradually increases to 1, gets smaller again, goes to -1, then back to zero:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b733c25d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.00000000e+00,  1.27877162e-01,  2.53654584e-01,  3.75267005e-01,\n",
       "        4.90717552e-01,  5.98110530e-01,  6.95682551e-01,  7.81831482e-01,\n",
       "        8.55142763e-01,  9.14412623e-01,  9.58667853e-01,  9.87181783e-01,\n",
       "        9.99486216e-01,  9.95379113e-01,  9.74927912e-01,  9.38468422e-01,\n",
       "        8.86599306e-01,  8.20172255e-01,  7.40277997e-01,  6.48228395e-01,\n",
       "        5.45534901e-01,  4.33883739e-01,  3.15108218e-01,  1.91158629e-01,\n",
       "        6.40702200e-02, -6.40702200e-02, -1.91158629e-01, -3.15108218e-01,\n",
       "       -4.33883739e-01, -5.45534901e-01, -6.48228395e-01, -7.40277997e-01,\n",
       "       -8.20172255e-01, -8.86599306e-01, -9.38468422e-01, -9.74927912e-01,\n",
       "       -9.95379113e-01, -9.99486216e-01, -9.87181783e-01, -9.58667853e-01,\n",
       "       -9.14412623e-01, -8.55142763e-01, -7.81831482e-01, -6.95682551e-01,\n",
       "       -5.98110530e-01, -4.90717552e-01, -3.75267005e-01, -2.53654584e-01,\n",
       "       -1.27877162e-01, -2.44929360e-16])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sin(np.linspace(0, np.pi * 2, 50))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5cc98b29",
   "metadata": {},
   "source": [
    "Plotted:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "73920da8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.Series(np.sin(np.linspace(0, np.pi * 2, 50))).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d4d6460",
   "metadata": {},
   "source": [
    "You can make multiple cycles by increasing the numbers passed to `np.linspace()` and increase the heights and depths of the peaks and valleys by multiplying the result of `np.sin()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6c837515",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.Series(np.sin(np.linspace(0, 20, 100))*3).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13ce3db7",
   "metadata": {},
   "source": [
    "Putting this all together: we can create a line that has a repeating wavy pattern with a bit of noise:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8f381074",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.Series(\n",
    "    np.linspace(-100, 100, 50) + (np.sin(np.linspace(0, 20, 50)) * 20) + np.random.uniform(-5, 5, size=50)\n",
    ").plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e7d10da",
   "metadata": {},
   "source": [
    "## Correlation: a toy scenario\n",
    "\n",
    "Two variables (i.e., columns in a dataset) are considered to be \"correlated\" if there is a linear relationship between them. If the value in column `a` of the table tend to be higher as the values in column `b` get higher, then the two columns are correlated. If the values in one column tend to go *lower* as values in the other column go higher, then the values are said to be *negatively correlated* (or inversely correlated).\n",
    "\n",
    "I'm going to demonstrate some correlations, first with toy data, and then with some actual data.\n",
    "\n",
    "Here's the toy data. I'm making a data frame with four columns, each of which is populated with synthetic data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d22ecf1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(\n",
    "    {\n",
    "        \"widgets\": np.linspace(1, 100, 50),\n",
    "        \"florpiness\": np.linspace(10, 75, 50) + np.sin(np.linspace(0, 40, 50)) * 5,\n",
    "        \"glormp_count\": np.linspace(200, 125, 50) + np.random.uniform(-10, 10, 50),\n",
    "        \"beep_value\": np.random.uniform(0, 25, size=50)\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "437cb95f",
   "metadata": {},
   "source": [
    "Here's a little preview of the data frame, showing what the data look like. The `widgets` column increases linearly; the `florpiness` column has a bit of a wavy pattern, but also increases linearly; `glormp_count` is a noisy decreasing line; and `beep_value` is a uniformly distributed random number."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "61335a64",
   "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>widgets</th>\n",
       "      <th>florpiness</th>\n",
       "      <th>glormp_count</th>\n",
       "      <th>beep_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>199.167048</td>\n",
       "      <td>18.176731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.020408</td>\n",
       "      <td>14.969705</td>\n",
       "      <td>189.234256</td>\n",
       "      <td>12.123613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.040816</td>\n",
       "      <td>17.643499</td>\n",
       "      <td>206.130372</td>\n",
       "      <td>23.200101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.061224</td>\n",
       "      <td>17.172343</td>\n",
       "      <td>199.268667</td>\n",
       "      <td>15.652878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9.081633</td>\n",
       "      <td>14.689132</td>\n",
       "      <td>198.250686</td>\n",
       "      <td>24.704787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11.102041</td>\n",
       "      <td>12.594745</td>\n",
       "      <td>201.238916</td>\n",
       "      <td>1.715750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>13.122449</td>\n",
       "      <td>13.045028</td>\n",
       "      <td>195.741224</td>\n",
       "      <td>21.765844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>15.142857</td>\n",
       "      <td>16.592188</td>\n",
       "      <td>195.373523</td>\n",
       "      <td>21.985910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>17.163265</td>\n",
       "      <td>21.836795</td>\n",
       "      <td>181.600484</td>\n",
       "      <td>14.688121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>19.183673</td>\n",
       "      <td>26.309697</td>\n",
       "      <td>187.222707</td>\n",
       "      <td>1.218043</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     widgets  florpiness  glormp_count  beep_value\n",
       "0   1.000000   10.000000    199.167048   18.176731\n",
       "1   3.020408   14.969705    189.234256   12.123613\n",
       "2   5.040816   17.643499    206.130372   23.200101\n",
       "3   7.061224   17.172343    199.268667   15.652878\n",
       "4   9.081633   14.689132    198.250686   24.704787\n",
       "5  11.102041   12.594745    201.238916    1.715750\n",
       "6  13.122449   13.045028    195.741224   21.765844\n",
       "7  15.142857   16.592188    195.373523   21.985910\n",
       "8  17.163265   21.836795    181.600484   14.688121\n",
       "9  19.183673   26.309697    187.222707    1.218043"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73b11044",
   "metadata": {},
   "source": [
    "If we plot these data as is, we can clearly see the patterns of the synthetic data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1cf212a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfd2826a",
   "metadata": {},
   "source": [
    "Of course, looking at this graph, it's pretty clear how the data are correlated. But I want to emphasize that correlation has nothing to do with how the individual rows are ordered! To demonstrate, let's put the rows of the data frame in a random order:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "af0fd69e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.sample(len(df)).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d3cc2fb",
   "metadata": {},
   "source": [
    "Now that the rows of synthetic data are randomized, you don't see their original structure, though you can probably guess that the correlations are still there:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a97cd6cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51c0699a",
   "metadata": {},
   "source": [
    "### Intuiting correlation from the scatter plot\n",
    "\n",
    "An easy way to spot correlations is by doing a scatter plot of two different columns. In a scatter plot, there is one point for every row, and the point is positioned on the X/Y plane according to its value in the two specified columns. For example, let's look at `widgets` vs `flormpiness`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1fbf7a39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='widgets', ylabel='florpiness'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(kind=\"scatter\", x=\"widgets\", y=\"florpiness\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e37f8426",
   "metadata": {},
   "source": [
    "If you get a plot that looks somewhat organized around a line that increases from left to right, then the values are probably correlated—like `widgets` and `florpiness` above.\n",
    "\n",
    "Now let's look at `florpiness` against `glormp_count`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "89e292a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='florpiness', ylabel='glormp_count'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(kind=\"scatter\", x=\"florpiness\", y=\"glormp_count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04f35c0f",
   "metadata": {},
   "source": [
    "Here, the points form a descending line, meaning that the two variables are likely negatively correlated (i.e., the higher the `glormp_count`, the lower the `florpiness`).\n",
    "\n",
    "If we plot any of these values against `beep_value`, however, a different pattern emerges:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2e687f47",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='florpiness', ylabel='beep_value'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(kind=\"scatter\", x=\"florpiness\", y=\"beep_value\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69816532",
   "metadata": {},
   "source": [
    "In this plot, there's no clear relationship between the two variables. In the case of our toy data, this is expected, since we created `beep_value` using random numbers from a uniform distribution.\n",
    "\n",
    "### One scatterplot to rule them all\n",
    "\n",
    "Pandas provides a function to draw what's called a *scatter matrix*, which is a matrix of scatter plots for every combination of columns in the data frame. Here's what it looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a66d9e08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<Axes: xlabel='widgets', ylabel='widgets'>,\n",
       "        <Axes: xlabel='florpiness', ylabel='widgets'>,\n",
       "        <Axes: xlabel='glormp_count', ylabel='widgets'>,\n",
       "        <Axes: xlabel='beep_value', ylabel='widgets'>],\n",
       "       [<Axes: xlabel='widgets', ylabel='florpiness'>,\n",
       "        <Axes: xlabel='florpiness', ylabel='florpiness'>,\n",
       "        <Axes: xlabel='glormp_count', ylabel='florpiness'>,\n",
       "        <Axes: xlabel='beep_value', ylabel='florpiness'>],\n",
       "       [<Axes: xlabel='widgets', ylabel='glormp_count'>,\n",
       "        <Axes: xlabel='florpiness', ylabel='glormp_count'>,\n",
       "        <Axes: xlabel='glormp_count', ylabel='glormp_count'>,\n",
       "        <Axes: xlabel='beep_value', ylabel='glormp_count'>],\n",
       "       [<Axes: xlabel='widgets', ylabel='beep_value'>,\n",
       "        <Axes: xlabel='florpiness', ylabel='beep_value'>,\n",
       "        <Axes: xlabel='glormp_count', ylabel='beep_value'>,\n",
       "        <Axes: xlabel='beep_value', ylabel='beep_value'>]], dtype=object)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.plotting.scatter_matrix(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3b10e5a",
   "metadata": {},
   "source": [
    "It's a bit messy, but here's how you read it. Both the X axis and the Y axis of the matrix have every column. Each cell has the scatter plot for the two columns that correspond to the cell's X and Y position. It doesn't make sense to do a scatter plot of a column against itself (each column is always perfectly correlated with itself, after all), so Pandas shows the histogram for that column instead.\n",
    "\n",
    "The scatter matrix is a very easy way to get an overview of your data, and spot columns at a glance that might be correlated in some way."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7057ac3a",
   "metadata": {},
   "source": [
    "### Scoring correlations\n",
    "\n",
    "If just eyeballing the data isn't enough for you, it's also possible to compute a value for the correlation. This is useful for automatically finding correlations, or figuring out which correlations are more pronounced than others. The `.corr()` method of a Pandas `DataFrame` evaluates to a new data frame with a matrix of computed correlations. It looks like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6dd4c16f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\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>widgets</th>\n",
       "      <th>florpiness</th>\n",
       "      <th>glormp_count</th>\n",
       "      <th>beep_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>widgets</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.983441</td>\n",
       "      <td>-0.975385</td>\n",
       "      <td>-0.207085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>florpiness</th>\n",
       "      <td>0.983441</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.967650</td>\n",
       "      <td>-0.225806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>glormp_count</th>\n",
       "      <td>-0.975385</td>\n",
       "      <td>-0.967650</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.209233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beep_value</th>\n",
       "      <td>-0.207085</td>\n",
       "      <td>-0.225806</td>\n",
       "      <td>0.209233</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               widgets  florpiness  glormp_count  beep_value\n",
       "widgets       1.000000    0.983441     -0.975385   -0.207085\n",
       "florpiness    0.983441    1.000000     -0.967650   -0.225806\n",
       "glormp_count -0.975385   -0.967650      1.000000    0.209233\n",
       "beep_value   -0.207085   -0.225806      0.209233    1.000000"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f4380f6",
   "metadata": {},
   "source": [
    "The default correlation metric is the [Pearson correlation coefficient](https://en.wikipedia.org/wiki/Pearson_correlation_coefficient). Using this metric, perfectly correlated columns score 1; perfectly inversely correlated columns score -1; and columns that are not correlated at all score 0. You can find the correlation for two columns at the intersection of the column names in the data frame returned by `.corr()`. Here we can see that there is a strong correlation between, e.g., `widgets` and `florpiness`, whereas `beep_value`'s correlation scores are much closer to zero."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67c9cc70",
   "metadata": {},
   "source": [
    "## Correlation: example with real data\n",
    "\n",
    "Okay, so let's try this out with some actual data. I've prepared [a dataset of GitHub repository topics](github-topics-by-economy.csv), which you should download and put in the same directory as this notebook. I'm going to open it as a data frame first, and then explain what it is and how it works."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1441839e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# .set_index() below to use the first column as the data frame index (this will be handy later)\n",
    "df = pd.read_csv(\"./github-topics-by-economy.csv\").set_index(\"iso2_code\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8e7593fa",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>python</th>\n",
       "      <th>javascript</th>\n",
       "      <th>react</th>\n",
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       "      <td>0.039609</td>\n",
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       "      <td>0.028684</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004302</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002151</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT</th>\n",
       "      <td>0.143863</td>\n",
       "      <td>0.096892</td>\n",
       "      <td>0.016085</td>\n",
       "      <td>0.103127</td>\n",
       "      <td>0.056965</td>\n",
       "      <td>0.090896</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.021177</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004854</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AU</th>\n",
       "      <td>0.065165</td>\n",
       "      <td>0.051515</td>\n",
       "      <td>0.053479</td>\n",
       "      <td>0.038584</td>\n",
       "      <td>0.039427</td>\n",
       "      <td>0.024723</td>\n",
       "      <td>0.030011</td>\n",
       "      <td>0.016591</td>\n",
       "      <td>0.025528</td>\n",
       "      <td>0.016792</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008726</td>\n",
       "      <td>0.008860</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.007203</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001015</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BD</th>\n",
       "      <td>0.024566</td>\n",
       "      <td>0.046559</td>\n",
       "      <td>0.035475</td>\n",
       "      <td>0.001271</td>\n",
       "      <td>0.008511</td>\n",
       "      <td>0.013066</td>\n",
       "      <td>0.024214</td>\n",
       "      <td>0.029801</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.027155</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006169</td>\n",
       "      <td>0.002461</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013514</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BE</th>\n",
       "      <td>0.134137</td>\n",
       "      <td>0.076613</td>\n",
       "      <td>0.045815</td>\n",
       "      <td>0.076655</td>\n",
       "      <td>0.033513</td>\n",
       "      <td>0.038603</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009121</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>0.028277</td>\n",
       "      <td>0.020119</td>\n",
       "      <td>0.017519</td>\n",
       "      <td>0.014956</td>\n",
       "      <td>0.010669</td>\n",
       "      <td>0.011038</td>\n",
       "      <td>0.010387</td>\n",
       "      <td>0.007184</td>\n",
       "      <td>0.008272</td>\n",
       "      <td>0.006825</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004380</td>\n",
       "      <td>0.004345</td>\n",
       "      <td>0.002667</td>\n",
       "      <td>0.002495</td>\n",
       "      <td>0.003928</td>\n",
       "      <td>0.003589</td>\n",
       "      <td>0.001787</td>\n",
       "      <td>0.001829</td>\n",
       "      <td>0.003357</td>\n",
       "      <td>0.002935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UZ</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015633</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VE</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.036792</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VN</th>\n",
       "      <td>0.019918</td>\n",
       "      <td>0.028190</td>\n",
       "      <td>0.028847</td>\n",
       "      <td>0.004431</td>\n",
       "      <td>0.016845</td>\n",
       "      <td>0.016199</td>\n",
       "      <td>0.025307</td>\n",
       "      <td>0.007092</td>\n",
       "      <td>0.004442</td>\n",
       "      <td>0.005333</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003897</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZA</th>\n",
       "      <td>0.016711</td>\n",
       "      <td>0.025470</td>\n",
       "      <td>0.015814</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>64 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             python  javascript     react  hacktoberfest  typescript  \\\n",
       "iso2_code                                                              \n",
       "AR         0.039609    0.065067  0.058653       0.005784    0.022493   \n",
       "AT         0.143863    0.096892  0.016085       0.103127    0.056965   \n",
       "AU         0.065165    0.051515  0.053479       0.038584    0.039427   \n",
       "BD         0.024566    0.046559  0.035475       0.001271    0.008511   \n",
       "BE         0.134137    0.076613  0.045815       0.076655    0.033513   \n",
       "...             ...         ...       ...            ...         ...   \n",
       "US         0.028277    0.020119  0.017519       0.014956    0.010669   \n",
       "UZ         0.000000    0.015633  0.000000       0.000000    0.000000   \n",
       "VE         0.000000    0.036792  0.000000       0.000000    0.000000   \n",
       "VN         0.019918    0.028190  0.028847       0.004431    0.016845   \n",
       "ZA         0.016711    0.025470  0.015814       0.000000    0.000000   \n",
       "\n",
       "               java    nodejs       css    docker      html  ...      game  \\\n",
       "iso2_code                                                    ...             \n",
       "AR         0.019765  0.034730  0.034428  0.003161  0.028684  ...  0.000000   \n",
       "AT         0.090896  0.000000  0.000000  0.021177  0.000000  ...  0.000000   \n",
       "AU         0.024723  0.030011  0.016591  0.025528  0.016792  ...  0.008726   \n",
       "BD         0.013066  0.024214  0.029801  0.000000  0.027155  ...  0.000000   \n",
       "BE         0.038603  0.000000  0.000000  0.000000  0.000000  ...  0.000000   \n",
       "...             ...       ...       ...       ...       ...  ...       ...   \n",
       "US         0.011038  0.010387  0.007184  0.008272  0.006825  ...  0.004380   \n",
       "UZ         0.000000  0.000000  0.000000  0.000000  0.000000  ...  0.000000   \n",
       "VE         0.000000  0.000000  0.000000  0.000000  0.000000  ...  0.000000   \n",
       "VN         0.016199  0.025307  0.007092  0.004442  0.005333  ...  0.000000   \n",
       "ZA         0.000000  0.000000  0.000000  0.000000  0.000000  ...  0.000000   \n",
       "\n",
       "                cli    django     mysql  documentation    csharp    kotlin  \\\n",
       "iso2_code                                                                    \n",
       "AR         0.000000  0.000000  0.004302       0.000000  0.000000  0.000000   \n",
       "AT         0.000000  0.000000  0.000000       0.004854  0.000000  0.000000   \n",
       "AU         0.008860  0.000000  0.000000       0.007203  0.000000  0.000000   \n",
       "BD         0.000000  0.006169  0.002461       0.000000  0.000000  0.000000   \n",
       "BE         0.000000  0.000000  0.000000       0.009121  0.000000  0.000000   \n",
       "...             ...       ...       ...            ...       ...       ...   \n",
       "US         0.004345  0.002667  0.002495       0.003928  0.003589  0.001787   \n",
       "UZ         0.000000  0.000000  0.000000       0.000000  0.000000  0.000000   \n",
       "VE         0.000000  0.000000  0.000000       0.000000  0.000000  0.000000   \n",
       "VN         0.000000  0.000000  0.000000       0.000000  0.000000  0.000000   \n",
       "ZA         0.000000  0.000000  0.000000       0.000000  0.000000  0.000000   \n",
       "\n",
       "           tailwindcss       ios  blockchain  \n",
       "iso2_code                                     \n",
       "AR            0.002151  0.000000    0.000000  \n",
       "AT            0.000000  0.000000    0.000000  \n",
       "AU            0.001015  0.000000    0.000996  \n",
       "BD            0.013514  0.000000    0.000000  \n",
       "BE            0.000000  0.000000    0.000000  \n",
       "...                ...       ...         ...  \n",
       "US            0.001829  0.003357    0.002935  \n",
       "UZ            0.000000  0.000000    0.000000  \n",
       "VE            0.000000  0.000000    0.000000  \n",
       "VN            0.003897  0.000000    0.000000  \n",
       "ZA            0.000000  0.000000    0.000000  \n",
       "\n",
       "[64 rows x 40 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92e2b3be",
   "metadata": {},
   "source": [
    "This data is derived from the [GitHub Innovation Graph](https://github.com/github/innovationgraph/), which tracks public activity on GitHub. If you're not familiar, GitHub is a Microsoft-owned company that provides web hosting for source code. The main organizational unit of source code on GitHub is a \"repository,\" which generally holds the source code for a single project. Repositories are associated with \"topics,\" which are keywords that users assign to the repositories based on their contents. Users can also take actions on repositories (such as adding or editing code), and GitHub associates those actions with the user's IP address, which is then associated with a particular country (or \"economy\").\n",
    "\n",
    "The Innovation Graph database provides information about how many users from each country took actions on repositories, and breaks that down into a number of different categories. The data we're using here is derived from data on contributions to topics. Each column in our data frame represents a topic, and each row represents an \"economy.\" Each cell is a metric that reflects the total percentage of contributions made to repositories labelled with the topic in the column from the country in the row. For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0affd413",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0282770772955455"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[\"US\"][\"python\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "882c6887",
   "metadata": {},
   "source": [
    "... gives us the percentage of contributions originating in the United States to repositories labelled \"python.\"\n",
    "\n",
    "You can see how I prepared the data in [this notebook](github-topics-initial-work.ipynb). Note that I've only included the top 40 most popular topics, and also excluded some outliers (the `config` and `github-config` topics), so the values for each row don't perfectly add up to 1.\n",
    "\n",
    "### Correlating repository topics\n",
    "\n",
    "Columns in this data frame will be correlated if they tend to be found in similar proportions, regardless of economy. Drawing a scatter matrix of the entire data frame would take a long time and would be pretty overwhelming to read, so let's try drawing a little subset. The following grabs a little \"slice\" of the data frame including only the specified columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ff938a65",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_slice = df[[\"python\", \"php\", \"java\", \"javascript\", \"css\", \"blockchain\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "29f93b51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>python</th>\n",
       "      <th>php</th>\n",
       "      <th>java</th>\n",
       "      <th>javascript</th>\n",
       "      <th>css</th>\n",
       "      <th>blockchain</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>iso2_code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <td>0.039609</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.019765</td>\n",
       "      <td>0.065067</td>\n",
       "      <td>0.034428</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT</th>\n",
       "      <td>0.143863</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.090896</td>\n",
       "      <td>0.096892</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AU</th>\n",
       "      <td>0.065165</td>\n",
       "      <td>0.015786</td>\n",
       "      <td>0.024723</td>\n",
       "      <td>0.051515</td>\n",
       "      <td>0.016591</td>\n",
       "      <td>0.000996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BD</th>\n",
       "      <td>0.024566</td>\n",
       "      <td>0.015008</td>\n",
       "      <td>0.013066</td>\n",
       "      <td>0.046559</td>\n",
       "      <td>0.029801</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BE</th>\n",
       "      <td>0.134137</td>\n",
       "      <td>0.032580</td>\n",
       "      <td>0.038603</td>\n",
       "      <td>0.076613</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>0.028277</td>\n",
       "      <td>0.003501</td>\n",
       "      <td>0.011038</td>\n",
       "      <td>0.020119</td>\n",
       "      <td>0.007184</td>\n",
       "      <td>0.002935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UZ</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015633</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VE</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.036792</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VN</th>\n",
       "      <td>0.019918</td>\n",
       "      <td>0.002327</td>\n",
       "      <td>0.016199</td>\n",
       "      <td>0.028190</td>\n",
       "      <td>0.007092</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZA</th>\n",
       "      <td>0.016711</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.025470</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>64 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             python       php      java  javascript       css  blockchain\n",
       "iso2_code                                                                \n",
       "AR         0.039609  0.000000  0.019765    0.065067  0.034428    0.000000\n",
       "AT         0.143863  0.000000  0.090896    0.096892  0.000000    0.000000\n",
       "AU         0.065165  0.015786  0.024723    0.051515  0.016591    0.000996\n",
       "BD         0.024566  0.015008  0.013066    0.046559  0.029801    0.000000\n",
       "BE         0.134137  0.032580  0.038603    0.076613  0.000000    0.000000\n",
       "...             ...       ...       ...         ...       ...         ...\n",
       "US         0.028277  0.003501  0.011038    0.020119  0.007184    0.002935\n",
       "UZ         0.000000  0.000000  0.000000    0.015633  0.000000    0.000000\n",
       "VE         0.000000  0.000000  0.000000    0.036792  0.000000    0.000000\n",
       "VN         0.019918  0.002327  0.016199    0.028190  0.007092    0.000000\n",
       "ZA         0.016711  0.000000  0.000000    0.025470  0.000000    0.000000\n",
       "\n",
       "[64 rows x 6 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_slice"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59acc50f",
   "metadata": {},
   "source": [
    "And here's the scatter matrix:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c6154740",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 36 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# using \"plot =\" here to suppress the display of the value, which is long and weird for scatter_matrix\n",
    "plot = pd.plotting.scatter_matrix(df_slice)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60bff1df",
   "metadata": {},
   "source": [
    "Again, each dot in a scatter plot represents a row in the database—in our case, one economy. If we find that two topics are correlated, it means that if one topic is popular in a given economy, the other is popular as well.\n",
    "\n",
    "A quick eyeball of this data shows that the `python` topic is probably correlated fairly strongly with `php`, `java` and `javascript`, but not strongly correlated with `css` or `blockchain`. The `css` topic seems to be correlated with `javascript`, but doesn't have other strong correlations. We can put our eyeballs to the test with a quick call to `.corr()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "255cea8d",
   "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>python</th>\n",
       "      <th>php</th>\n",
       "      <th>java</th>\n",
       "      <th>javascript</th>\n",
       "      <th>css</th>\n",
       "      <th>blockchain</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>python</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.267850</td>\n",
       "      <td>0.612837</td>\n",
       "      <td>0.585947</td>\n",
       "      <td>-0.246902</td>\n",
       "      <td>0.070675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>php</th>\n",
       "      <td>0.267850</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.346770</td>\n",
       "      <td>0.050148</td>\n",
       "      <td>0.095875</td>\n",
       "      <td>0.344741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>java</th>\n",
       "      <td>0.612837</td>\n",
       "      <td>0.346770</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.523005</td>\n",
       "      <td>-0.114569</td>\n",
       "      <td>0.273783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>javascript</th>\n",
       "      <td>0.585947</td>\n",
       "      <td>0.050148</td>\n",
       "      <td>0.523005</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.014515</td>\n",
       "      <td>-0.142675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>css</th>\n",
       "      <td>-0.246902</td>\n",
       "      <td>0.095875</td>\n",
       "      <td>-0.114569</td>\n",
       "      <td>-0.014515</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.015614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>blockchain</th>\n",
       "      <td>0.070675</td>\n",
       "      <td>0.344741</td>\n",
       "      <td>0.273783</td>\n",
       "      <td>-0.142675</td>\n",
       "      <td>-0.015614</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              python       php      java  javascript       css  blockchain\n",
       "python      1.000000  0.267850  0.612837    0.585947 -0.246902    0.070675\n",
       "php         0.267850  1.000000  0.346770    0.050148  0.095875    0.344741\n",
       "java        0.612837  0.346770  1.000000    0.523005 -0.114569    0.273783\n",
       "javascript  0.585947  0.050148  0.523005    1.000000 -0.014515   -0.142675\n",
       "css        -0.246902  0.095875 -0.114569   -0.014515  1.000000   -0.015614\n",
       "blockchain  0.070675  0.344741  0.273783   -0.142675 -0.015614    1.000000"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_slice.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb3c4e50",
   "metadata": {},
   "source": [
    "... which bears out our observations. (Though in fact `css` has a negative correlation with `python`, and somehow `php` is the most highly correlated topic with `blockchain` in this sample of columns!)\n",
    "\n",
    "### Sorting through correlations\n",
    "\n",
    "Looking at the raw correlation matrix for a data frame this size is going to be pretty daunting, and it might be difficult to spot interesting patterns. Another way of poking through the correlations is on a column-by-column basis. Let's look at just the correlation scores for the `python` column, sorted in descending order:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "cd69d61e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "python              1.000000\n",
       "hacktoberfest       0.733542\n",
       "java                0.612837\n",
       "javascript          0.585947\n",
       "typescript          0.461957\n",
       "docker              0.392906\n",
       "react               0.366915\n",
       "php                 0.267850\n",
       "documentation       0.212785\n",
       "machine-learning    0.200749\n",
       "linux               0.182088\n",
       "kubernetes          0.163709\n",
       "nodejs              0.143030\n",
       "rust                0.122608\n",
       "golang              0.104656\n",
       "deep-learning       0.096169\n",
       "api                 0.081185\n",
       "blockchain          0.070675\n",
       "go                  0.058190\n",
       "dotfiles            0.057860\n",
       "cli                 0.012881\n",
       "game               -0.007755\n",
       "vue                -0.012221\n",
       "cpp                -0.019139\n",
       "blog               -0.030812\n",
       "python3            -0.039061\n",
       "website            -0.040422\n",
       "csharp             -0.059876\n",
       "android            -0.088875\n",
       "ios                -0.098411\n",
       "kotlin             -0.107205\n",
       "django             -0.108539\n",
       "mysql              -0.146326\n",
       "mongodb            -0.172419\n",
       "nextjs             -0.178071\n",
       "html5              -0.199006\n",
       "html               -0.211861\n",
       "css                -0.246902\n",
       "tailwindcss        -0.258969\n",
       "reactjs            -0.265028\n",
       "Name: python, dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()[\"python\"].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1ecb841",
   "metadata": {},
   "source": [
    "This tells us some potentially interesting things, e.g., that if people are programming in Python in your country, they're probably also programming in Java and JavaScript—but *not* in ReactJS.\n",
    "\n",
    "The same for the `blockchain` topic:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "132fa70a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "blockchain          1.000000\n",
       "deep-learning       0.825812\n",
       "machine-learning    0.771085\n",
       "cpp                 0.674569\n",
       "ios                 0.632550\n",
       "android             0.623655\n",
       "linux               0.588501\n",
       "python3             0.586005\n",
       "rust                0.582939\n",
       "go                  0.581567\n",
       "golang              0.551641\n",
       "docker              0.546328\n",
       "vue                 0.544050\n",
       "kotlin              0.525407\n",
       "blog                0.511948\n",
       "mysql               0.500201\n",
       "game                0.480335\n",
       "api                 0.478675\n",
       "cli                 0.465597\n",
       "documentation       0.455352\n",
       "kubernetes          0.390907\n",
       "csharp              0.372484\n",
       "php                 0.344741\n",
       "website             0.326996\n",
       "django              0.304351\n",
       "nodejs              0.297573\n",
       "java                0.273783\n",
       "nextjs              0.269549\n",
       "typescript          0.267711\n",
       "mongodb             0.256912\n",
       "dotfiles            0.228191\n",
       "python              0.070675\n",
       "tailwindcss         0.051642\n",
       "html                0.040865\n",
       "reactjs             0.012599\n",
       "hacktoberfest       0.010587\n",
       "html5              -0.004614\n",
       "css                -0.015614\n",
       "react              -0.035510\n",
       "javascript         -0.142675\n",
       "Name: blockchain, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()[\"blockchain\"].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c815ec2f",
   "metadata": {},
   "source": [
    "Blockchain and deep learning are very strongly correlated (cough chasing trends cough).\n",
    "\n",
    "Here's another example, showing all of the pairs of topics with very small correlation scores:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a716f8cf",
   "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>level_0</th>\n",
       "      <th>level_1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>hacktoberfest</td>\n",
       "      <td>game</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>typescript</td>\n",
       "      <td>html</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>java</td>\n",
       "      <td>nextjs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>292</th>\n",
       "      <td>css</td>\n",
       "      <td>machine-learning</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>css</td>\n",
       "      <td>kubernetes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>301</th>\n",
       "      <td>css</td>\n",
       "      <td>rust</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330</th>\n",
       "      <td>docker</td>\n",
       "      <td>reactjs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>html</td>\n",
       "      <td>typescript</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>377</th>\n",
       "      <td>html</td>\n",
       "      <td>vue</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>382</th>\n",
       "      <td>html</td>\n",
       "      <td>deep-learning</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408</th>\n",
       "      <td>reactjs</td>\n",
       "      <td>docker</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>413</th>\n",
       "      <td>reactjs</td>\n",
       "      <td>golang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>466</th>\n",
       "      <td>php</td>\n",
       "      <td>html5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>machine-learning</td>\n",
       "      <td>css</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>golang</td>\n",
       "      <td>reactjs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>689</th>\n",
       "      <td>vue</td>\n",
       "      <td>html</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>767</th>\n",
       "      <td>kubernetes</td>\n",
       "      <td>css</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>847</th>\n",
       "      <td>rust</td>\n",
       "      <td>css</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>deep-learning</td>\n",
       "      <td>html</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>965</th>\n",
       "      <td>nextjs</td>\n",
       "      <td>java</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1051</th>\n",
       "      <td>html5</td>\n",
       "      <td>php</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1079</th>\n",
       "      <td>html5</td>\n",
       "      <td>blockchain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1203</th>\n",
       "      <td>game</td>\n",
       "      <td>hacktoberfest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586</th>\n",
       "      <td>blockchain</td>\n",
       "      <td>html5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               level_0           level_1\n",
       "150      hacktoberfest              game\n",
       "169         typescript              html\n",
       "224               java            nextjs\n",
       "292                css  machine-learning\n",
       "299                css        kubernetes\n",
       "301                css              rust\n",
       "330             docker           reactjs\n",
       "364               html        typescript\n",
       "377               html               vue\n",
       "382               html     deep-learning\n",
       "408            reactjs            docker\n",
       "413            reactjs            golang\n",
       "466                php             html5\n",
       "487   machine-learning               css\n",
       "530             golang           reactjs\n",
       "689                vue              html\n",
       "767         kubernetes               css\n",
       "847               rust               css\n",
       "889      deep-learning              html\n",
       "965             nextjs              java\n",
       "1051             html5               php\n",
       "1079             html5        blockchain\n",
       "1203              game     hacktoberfest\n",
       "1586        blockchain             html5"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# using some tricks from https://stackoverflow.com/a/65439244\n",
    "df2 = (df.corr().abs() < 0.005).unstack().reset_index()\n",
    "df2[df2[0]][[\"level_0\", \"level_1\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf9968b4",
   "metadata": {},
   "source": [
    "### Correlating the transpose\n",
    "\n",
    "A data frame's *transpose* is a copy of that data frame where the rows and columns have swapped places. With the data frame we're working with here, the transpose will have the economies as columns, and the topics as rows. To get the transpose, use the `.T` attribute of the `DataFrame` object, like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ca141733",
   "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>iso2_code</th>\n",
       "      <th>AR</th>\n",
       "      <th>AT</th>\n",
       "      <th>AU</th>\n",
       "      <th>BD</th>\n",
       "      <th>BE</th>\n",
       "      <th>BG</th>\n",
       "      <th>BR</th>\n",
       "      <th>BY</th>\n",
       "      <th>CA</th>\n",
       "      <th>CH</th>\n",
       "      <th>...</th>\n",
       "      <th>SG</th>\n",
       "      <th>TH</th>\n",
       "      <th>TR</th>\n",
       "      <th>TW</th>\n",
       "      <th>UA</th>\n",
       "      <th>US</th>\n",
       "      <th>UZ</th>\n",
       "      <th>VE</th>\n",
       "      <th>VN</th>\n",
       "      <th>ZA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>python</th>\n",
       "      <td>0.039609</td>\n",
       "      <td>0.143863</td>\n",
       "      <td>0.065165</td>\n",
       "      <td>0.024566</td>\n",
       "      <td>0.134137</td>\n",
       "      <td>0.007872</td>\n",
       "      <td>0.021625</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.044755</td>\n",
       "      <td>0.126227</td>\n",
       "      <td>...</td>\n",
       "      <td>0.063989</td>\n",
       "      <td>0.012849</td>\n",
       "      <td>0.037755</td>\n",
       "      <td>0.091298</td>\n",
       "      <td>0.038350</td>\n",
       "      <td>0.028277</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.019918</td>\n",
       "      <td>0.016711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>javascript</th>\n",
       "      <td>0.065067</td>\n",
       "      <td>0.096892</td>\n",
       "      <td>0.051515</td>\n",
       "      <td>0.046559</td>\n",
       "      <td>0.076613</td>\n",
       "      <td>0.127643</td>\n",
       "      <td>0.042422</td>\n",
       "      <td>0.061616</td>\n",
       "      <td>0.042014</td>\n",
       "      <td>0.065189</td>\n",
       "      <td>...</td>\n",
       "      <td>0.054047</td>\n",
       "      <td>0.007482</td>\n",
       "      <td>0.040929</td>\n",
       "      <td>0.063431</td>\n",
       "      <td>0.049700</td>\n",
       "      <td>0.020119</td>\n",
       "      <td>0.015633</td>\n",
       "      <td>0.036792</td>\n",
       "      <td>0.028190</td>\n",
       "      <td>0.025470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>react</th>\n",
       "      <td>0.058653</td>\n",
       "      <td>0.016085</td>\n",
       "      <td>0.053479</td>\n",
       "      <td>0.035475</td>\n",
       "      <td>0.045815</td>\n",
       "      <td>0.055487</td>\n",
       "      <td>0.028838</td>\n",
       "      <td>0.152583</td>\n",
       "      <td>0.042520</td>\n",
       "      <td>0.048259</td>\n",
       "      <td>...</td>\n",
       "      <td>0.047007</td>\n",
       "      <td>0.023123</td>\n",
       "      <td>0.036754</td>\n",
       "      <td>0.069960</td>\n",
       "      <td>0.058654</td>\n",
       "      <td>0.017519</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.028847</td>\n",
       "      <td>0.015814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hacktoberfest</th>\n",
       "      <td>0.005784</td>\n",
       "      <td>0.103127</td>\n",
       "      <td>0.038584</td>\n",
       "      <td>0.001271</td>\n",
       "      <td>0.076655</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013039</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.024782</td>\n",
       "      <td>0.060714</td>\n",
       "      <td>...</td>\n",
       "      <td>0.046772</td>\n",
       "      <td>0.021334</td>\n",
       "      <td>0.005206</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013599</td>\n",
       "      <td>0.014956</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004431</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>typescript</th>\n",
       "      <td>0.022493</td>\n",
       "      <td>0.056965</td>\n",
       "      <td>0.039427</td>\n",
       "      <td>0.008511</td>\n",
       "      <td>0.033513</td>\n",
       "      <td>0.062741</td>\n",
       "      <td>0.026432</td>\n",
       "      <td>0.044069</td>\n",
       "      <td>0.024672</td>\n",
       "      <td>0.051805</td>\n",
       "      <td>...</td>\n",
       "      <td>0.038172</td>\n",
       "      <td>0.008376</td>\n",
       "      <td>0.020046</td>\n",
       "      <td>0.036175</td>\n",
       "      <td>0.035039</td>\n",
       "      <td>0.010669</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.016845</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>java</th>\n",
       "      <td>0.019765</td>\n",
       "      <td>0.090896</td>\n",
       "      <td>0.024723</td>\n",
       "      <td>0.013066</td>\n",
       "      <td>0.038603</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013997</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.019468</td>\n",
       "      <td>0.060324</td>\n",
       "      <td>...</td>\n",
       "      <td>0.036430</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.024695</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.025875</td>\n",
       "      <td>0.011038</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.016199</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nodejs</th>\n",
       "      <td>0.034730</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.030011</td>\n",
       "      <td>0.024214</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.024740</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.023837</td>\n",
       "      <td>0.029838</td>\n",
       "      <td>...</td>\n",
       "      <td>0.028321</td>\n",
       "      <td>0.003741</td>\n",
       "      <td>0.022382</td>\n",
       "      <td>0.040398</td>\n",
       "      <td>0.027843</td>\n",
       "      <td>0.010387</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.025307</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>css</th>\n",
       "      <td>0.034428</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.016591</td>\n",
       "      <td>0.029801</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.026389</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015945</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.017302</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.046888</td>\n",
       "      <td>0.007184</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.007092</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>docker</th>\n",
       "      <td>0.003161</td>\n",
       "      <td>0.021177</td>\n",
       "      <td>0.025528</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.010259</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.014581</td>\n",
       "      <td>0.056043</td>\n",
       "      <td>...</td>\n",
       "      <td>0.009851</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.007705</td>\n",
       "      <td>0.019060</td>\n",
       "      <td>0.021877</td>\n",
       "      <td>0.008272</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004442</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>html</th>\n",
       "      <td>0.028684</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.016792</td>\n",
       "      <td>0.027155</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.025875</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.014659</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015225</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.046940</td>\n",
       "      <td>0.006825</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005333</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reactjs</th>\n",
       "      <td>0.023713</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.014924</td>\n",
       "      <td>0.029777</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020836</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013828</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004028</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.019222</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.016140</td>\n",
       "      <td>0.005281</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.024772</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>php</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015786</td>\n",
       "      <td>0.015008</td>\n",
       "      <td>0.032580</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.007244</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008147</td>\n",
       "      <td>0.033600</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013416</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020575</td>\n",
       "      <td>0.003501</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002327</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 64 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "iso2_code            AR        AT        AU        BD        BE        BG  \\\n",
       "python         0.039609  0.143863  0.065165  0.024566  0.134137  0.007872   \n",
       "javascript     0.065067  0.096892  0.051515  0.046559  0.076613  0.127643   \n",
       "react          0.058653  0.016085  0.053479  0.035475  0.045815  0.055487   \n",
       "hacktoberfest  0.005784  0.103127  0.038584  0.001271  0.076655  0.000000   \n",
       "typescript     0.022493  0.056965  0.039427  0.008511  0.033513  0.062741   \n",
       "java           0.019765  0.090896  0.024723  0.013066  0.038603  0.000000   \n",
       "nodejs         0.034730  0.000000  0.030011  0.024214  0.000000  0.000000   \n",
       "css            0.034428  0.000000  0.016591  0.029801  0.000000  0.000000   \n",
       "docker         0.003161  0.021177  0.025528  0.000000  0.000000  0.000000   \n",
       "html           0.028684  0.000000  0.016792  0.027155  0.000000  0.000000   \n",
       "reactjs        0.023713  0.000000  0.014924  0.029777  0.000000  0.000000   \n",
       "php            0.000000  0.000000  0.015786  0.015008  0.032580  0.000000   \n",
       "\n",
       "iso2_code            BR        BY        CA        CH  ...        SG  \\\n",
       "python         0.021625  0.000000  0.044755  0.126227  ...  0.063989   \n",
       "javascript     0.042422  0.061616  0.042014  0.065189  ...  0.054047   \n",
       "react          0.028838  0.152583  0.042520  0.048259  ...  0.047007   \n",
       "hacktoberfest  0.013039  0.000000  0.024782  0.060714  ...  0.046772   \n",
       "typescript     0.026432  0.044069  0.024672  0.051805  ...  0.038172   \n",
       "java           0.013997  0.000000  0.019468  0.060324  ...  0.036430   \n",
       "nodejs         0.024740  0.000000  0.023837  0.029838  ...  0.028321   \n",
       "css            0.026389  0.000000  0.015945  0.000000  ...  0.000000   \n",
       "docker         0.010259  0.000000  0.014581  0.056043  ...  0.009851   \n",
       "html           0.025875  0.000000  0.014659  0.000000  ...  0.000000   \n",
       "reactjs        0.020836  0.000000  0.013828  0.000000  ...  0.004028   \n",
       "php            0.007244  0.000000  0.008147  0.033600  ...  0.000000   \n",
       "\n",
       "iso2_code            TH        TR        TW        UA        US        UZ  \\\n",
       "python         0.012849  0.037755  0.091298  0.038350  0.028277  0.000000   \n",
       "javascript     0.007482  0.040929  0.063431  0.049700  0.020119  0.015633   \n",
       "react          0.023123  0.036754  0.069960  0.058654  0.017519  0.000000   \n",
       "hacktoberfest  0.021334  0.005206  0.000000  0.013599  0.014956  0.000000   \n",
       "typescript     0.008376  0.020046  0.036175  0.035039  0.010669  0.000000   \n",
       "java           0.000000  0.024695  0.000000  0.025875  0.011038  0.000000   \n",
       "nodejs         0.003741  0.022382  0.040398  0.027843  0.010387  0.000000   \n",
       "css            0.000000  0.017302  0.000000  0.046888  0.007184  0.000000   \n",
       "docker         0.000000  0.007705  0.019060  0.021877  0.008272  0.000000   \n",
       "html           0.000000  0.015225  0.000000  0.046940  0.006825  0.000000   \n",
       "reactjs        0.000000  0.019222  0.000000  0.016140  0.005281  0.000000   \n",
       "php            0.000000  0.013416  0.000000  0.020575  0.003501  0.000000   \n",
       "\n",
       "iso2_code            VE        VN        ZA  \n",
       "python         0.000000  0.019918  0.016711  \n",
       "javascript     0.036792  0.028190  0.025470  \n",
       "react          0.000000  0.028847  0.015814  \n",
       "hacktoberfest  0.000000  0.004431  0.000000  \n",
       "typescript     0.000000  0.016845  0.000000  \n",
       "java           0.000000  0.016199  0.000000  \n",
       "nodejs         0.000000  0.025307  0.000000  \n",
       "css            0.000000  0.007092  0.000000  \n",
       "docker         0.000000  0.004442  0.000000  \n",
       "html           0.000000  0.005333  0.000000  \n",
       "reactjs        0.000000  0.024772  0.000000  \n",
       "php            0.000000  0.002327  0.000000  \n",
       "\n",
       "[12 rows x 64 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.T.head(12)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c8feb11",
   "metadata": {},
   "source": [
    "The beauty of the transpose is that now we can do all of the same correlations that we did with topics above, but now with economies. Here's the correlation score matrix:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "30175f47",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>iso2_code</th>\n",
       "      <th>AR</th>\n",
       "      <th>AT</th>\n",
       "      <th>AU</th>\n",
       "      <th>BD</th>\n",
       "      <th>BE</th>\n",
       "      <th>BG</th>\n",
       "      <th>BR</th>\n",
       "      <th>BY</th>\n",
       "      <th>CA</th>\n",
       "      <th>CH</th>\n",
       "      <th>...</th>\n",
       "      <th>SG</th>\n",
       "      <th>TH</th>\n",
       "      <th>TR</th>\n",
       "      <th>TW</th>\n",
       "      <th>UA</th>\n",
       "      <th>US</th>\n",
       "      <th>UZ</th>\n",
       "      <th>VE</th>\n",
       "      <th>VN</th>\n",
       "      <th>ZA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>iso2_code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.524220</td>\n",
       "      <td>0.779648</td>\n",
       "      <td>0.907110</td>\n",
       "      <td>0.590837</td>\n",
       "      <td>0.711644</td>\n",
       "      <td>0.948850</td>\n",
       "      <td>0.671156</td>\n",
       "      <td>0.862375</td>\n",
       "      <td>0.536234</td>\n",
       "      <td>...</td>\n",
       "      <td>0.674736</td>\n",
       "      <td>0.589135</td>\n",
       "      <td>0.880958</td>\n",
       "      <td>0.729375</td>\n",
       "      <td>0.864828</td>\n",
       "      <td>0.734447</td>\n",
       "      <td>0.543278</td>\n",
       "      <td>0.543278</td>\n",
       "      <td>0.898248</td>\n",
       "      <td>0.786915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT</th>\n",
       "      <td>0.524220</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.779421</td>\n",
       "      <td>0.355682</td>\n",
       "      <td>0.930824</td>\n",
       "      <td>0.461678</td>\n",
       "      <td>0.524470</td>\n",
       "      <td>0.211480</td>\n",
       "      <td>0.762752</td>\n",
       "      <td>0.871771</td>\n",
       "      <td>...</td>\n",
       "      <td>0.848906</td>\n",
       "      <td>0.629587</td>\n",
       "      <td>0.616665</td>\n",
       "      <td>0.598454</td>\n",
       "      <td>0.485520</td>\n",
       "      <td>0.842247</td>\n",
       "      <td>0.395217</td>\n",
       "      <td>0.395217</td>\n",
       "      <td>0.541174</td>\n",
       "      <td>0.614647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AU</th>\n",
       "      <td>0.779648</td>\n",
       "      <td>0.779421</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.593629</td>\n",
       "      <td>0.833766</td>\n",
       "      <td>0.603541</td>\n",
       "      <td>0.770416</td>\n",
       "      <td>0.566796</td>\n",
       "      <td>0.957181</td>\n",
       "      <td>0.860706</td>\n",
       "      <td>...</td>\n",
       "      <td>0.872875</td>\n",
       "      <td>0.772289</td>\n",
       "      <td>0.804193</td>\n",
       "      <td>0.798211</td>\n",
       "      <td>0.759000</td>\n",
       "      <td>0.934125</td>\n",
       "      <td>0.376539</td>\n",
       "      <td>0.376539</td>\n",
       "      <td>0.775018</td>\n",
       "      <td>0.728705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BD</th>\n",
       "      <td>0.907110</td>\n",
       "      <td>0.355682</td>\n",
       "      <td>0.593629</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.449863</td>\n",
       "      <td>0.573053</td>\n",
       "      <td>0.886824</td>\n",
       "      <td>0.509452</td>\n",
       "      <td>0.671094</td>\n",
       "      <td>0.350983</td>\n",
       "      <td>...</td>\n",
       "      <td>0.444079</td>\n",
       "      <td>0.388986</td>\n",
       "      <td>0.803387</td>\n",
       "      <td>0.525120</td>\n",
       "      <td>0.768483</td>\n",
       "      <td>0.531746</td>\n",
       "      <td>0.503584</td>\n",
       "      <td>0.503584</td>\n",
       "      <td>0.804208</td>\n",
       "      <td>0.656676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BE</th>\n",
       "      <td>0.590837</td>\n",
       "      <td>0.930824</td>\n",
       "      <td>0.833766</td>\n",
       "      <td>0.449863</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.490000</td>\n",
       "      <td>0.543840</td>\n",
       "      <td>0.356085</td>\n",
       "      <td>0.827748</td>\n",
       "      <td>0.878067</td>\n",
       "      <td>...</td>\n",
       "      <td>0.849764</td>\n",
       "      <td>0.740537</td>\n",
       "      <td>0.679141</td>\n",
       "      <td>0.713345</td>\n",
       "      <td>0.544739</td>\n",
       "      <td>0.886672</td>\n",
       "      <td>0.378850</td>\n",
       "      <td>0.378850</td>\n",
       "      <td>0.573887</td>\n",
       "      <td>0.737894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>0.734447</td>\n",
       "      <td>0.842247</td>\n",
       "      <td>0.934125</td>\n",
       "      <td>0.531746</td>\n",
       "      <td>0.886672</td>\n",
       "      <td>0.550268</td>\n",
       "      <td>0.674171</td>\n",
       "      <td>0.476610</td>\n",
       "      <td>0.958069</td>\n",
       "      <td>0.904895</td>\n",
       "      <td>...</td>\n",
       "      <td>0.920982</td>\n",
       "      <td>0.739113</td>\n",
       "      <td>0.779027</td>\n",
       "      <td>0.815323</td>\n",
       "      <td>0.677021</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.403460</td>\n",
       "      <td>0.403460</td>\n",
       "      <td>0.701750</td>\n",
       "      <td>0.783723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UZ</th>\n",
       "      <td>0.543278</td>\n",
       "      <td>0.395217</td>\n",
       "      <td>0.376539</td>\n",
       "      <td>0.503584</td>\n",
       "      <td>0.378850</td>\n",
       "      <td>0.832768</td>\n",
       "      <td>0.537041</td>\n",
       "      <td>0.337764</td>\n",
       "      <td>0.461898</td>\n",
       "      <td>0.283222</td>\n",
       "      <td>...</td>\n",
       "      <td>0.399336</td>\n",
       "      <td>0.164360</td>\n",
       "      <td>0.468109</td>\n",
       "      <td>0.396831</td>\n",
       "      <td>0.358103</td>\n",
       "      <td>0.403460</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.427096</td>\n",
       "      <td>0.735476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VE</th>\n",
       "      <td>0.543278</td>\n",
       "      <td>0.395217</td>\n",
       "      <td>0.376539</td>\n",
       "      <td>0.503584</td>\n",
       "      <td>0.378850</td>\n",
       "      <td>0.832768</td>\n",
       "      <td>0.537041</td>\n",
       "      <td>0.337764</td>\n",
       "      <td>0.461898</td>\n",
       "      <td>0.283222</td>\n",
       "      <td>...</td>\n",
       "      <td>0.399336</td>\n",
       "      <td>0.164360</td>\n",
       "      <td>0.468109</td>\n",
       "      <td>0.396831</td>\n",
       "      <td>0.358103</td>\n",
       "      <td>0.403460</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.427096</td>\n",
       "      <td>0.735476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VN</th>\n",
       "      <td>0.898248</td>\n",
       "      <td>0.541174</td>\n",
       "      <td>0.775018</td>\n",
       "      <td>0.804208</td>\n",
       "      <td>0.573887</td>\n",
       "      <td>0.634077</td>\n",
       "      <td>0.858428</td>\n",
       "      <td>0.614583</td>\n",
       "      <td>0.833397</td>\n",
       "      <td>0.580022</td>\n",
       "      <td>...</td>\n",
       "      <td>0.714803</td>\n",
       "      <td>0.582022</td>\n",
       "      <td>0.876039</td>\n",
       "      <td>0.710396</td>\n",
       "      <td>0.753416</td>\n",
       "      <td>0.701750</td>\n",
       "      <td>0.427096</td>\n",
       "      <td>0.427096</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.669123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZA</th>\n",
       "      <td>0.786915</td>\n",
       "      <td>0.614647</td>\n",
       "      <td>0.728705</td>\n",
       "      <td>0.656676</td>\n",
       "      <td>0.737894</td>\n",
       "      <td>0.797733</td>\n",
       "      <td>0.656280</td>\n",
       "      <td>0.659547</td>\n",
       "      <td>0.824975</td>\n",
       "      <td>0.623721</td>\n",
       "      <td>...</td>\n",
       "      <td>0.706597</td>\n",
       "      <td>0.585842</td>\n",
       "      <td>0.757344</td>\n",
       "      <td>0.813909</td>\n",
       "      <td>0.606379</td>\n",
       "      <td>0.783723</td>\n",
       "      <td>0.735476</td>\n",
       "      <td>0.735476</td>\n",
       "      <td>0.669123</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>64 rows × 64 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "iso2_code        AR        AT        AU        BD        BE        BG  \\\n",
       "iso2_code                                                               \n",
       "AR         1.000000  0.524220  0.779648  0.907110  0.590837  0.711644   \n",
       "AT         0.524220  1.000000  0.779421  0.355682  0.930824  0.461678   \n",
       "AU         0.779648  0.779421  1.000000  0.593629  0.833766  0.603541   \n",
       "BD         0.907110  0.355682  0.593629  1.000000  0.449863  0.573053   \n",
       "BE         0.590837  0.930824  0.833766  0.449863  1.000000  0.490000   \n",
       "...             ...       ...       ...       ...       ...       ...   \n",
       "US         0.734447  0.842247  0.934125  0.531746  0.886672  0.550268   \n",
       "UZ         0.543278  0.395217  0.376539  0.503584  0.378850  0.832768   \n",
       "VE         0.543278  0.395217  0.376539  0.503584  0.378850  0.832768   \n",
       "VN         0.898248  0.541174  0.775018  0.804208  0.573887  0.634077   \n",
       "ZA         0.786915  0.614647  0.728705  0.656676  0.737894  0.797733   \n",
       "\n",
       "iso2_code        BR        BY        CA        CH  ...        SG        TH  \\\n",
       "iso2_code                                          ...                       \n",
       "AR         0.948850  0.671156  0.862375  0.536234  ...  0.674736  0.589135   \n",
       "AT         0.524470  0.211480  0.762752  0.871771  ...  0.848906  0.629587   \n",
       "AU         0.770416  0.566796  0.957181  0.860706  ...  0.872875  0.772289   \n",
       "BD         0.886824  0.509452  0.671094  0.350983  ...  0.444079  0.388986   \n",
       "BE         0.543840  0.356085  0.827748  0.878067  ...  0.849764  0.740537   \n",
       "...             ...       ...       ...       ...  ...       ...       ...   \n",
       "US         0.674171  0.476610  0.958069  0.904895  ...  0.920982  0.739113   \n",
       "UZ         0.537041  0.337764  0.461898  0.283222  ...  0.399336  0.164360   \n",
       "VE         0.537041  0.337764  0.461898  0.283222  ...  0.399336  0.164360   \n",
       "VN         0.858428  0.614583  0.833397  0.580022  ...  0.714803  0.582022   \n",
       "ZA         0.656280  0.659547  0.824975  0.623721  ...  0.706597  0.585842   \n",
       "\n",
       "iso2_code        TR        TW        UA        US        UZ        VE  \\\n",
       "iso2_code                                                               \n",
       "AR         0.880958  0.729375  0.864828  0.734447  0.543278  0.543278   \n",
       "AT         0.616665  0.598454  0.485520  0.842247  0.395217  0.395217   \n",
       "AU         0.804193  0.798211  0.759000  0.934125  0.376539  0.376539   \n",
       "BD         0.803387  0.525120  0.768483  0.531746  0.503584  0.503584   \n",
       "BE         0.679141  0.713345  0.544739  0.886672  0.378850  0.378850   \n",
       "...             ...       ...       ...       ...       ...       ...   \n",
       "US         0.779027  0.815323  0.677021  1.000000  0.403460  0.403460   \n",
       "UZ         0.468109  0.396831  0.358103  0.403460  1.000000  1.000000   \n",
       "VE         0.468109  0.396831  0.358103  0.403460  1.000000  1.000000   \n",
       "VN         0.876039  0.710396  0.753416  0.701750  0.427096  0.427096   \n",
       "ZA         0.757344  0.813909  0.606379  0.783723  0.735476  0.735476   \n",
       "\n",
       "iso2_code        VN        ZA  \n",
       "iso2_code                      \n",
       "AR         0.898248  0.786915  \n",
       "AT         0.541174  0.614647  \n",
       "AU         0.775018  0.728705  \n",
       "BD         0.804208  0.656676  \n",
       "BE         0.573887  0.737894  \n",
       "...             ...       ...  \n",
       "US         0.701750  0.783723  \n",
       "UZ         0.427096  0.735476  \n",
       "VE         0.427096  0.735476  \n",
       "VN         1.000000  0.669123  \n",
       "ZA         0.669123  1.000000  \n",
       "\n",
       "[64 rows x 64 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.T.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28d6e271",
   "metadata": {},
   "source": [
    "And a little subset of economies and their correlations, visualized:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ae610e38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 36 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = pd.plotting.scatter_matrix(df.T[[\"US\", \"CA\", \"CN\", \"IN\", \"JP\", \"DE\"]])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce618111",
   "metadata": {},
   "source": [
    "You can see that the US and Canada are very strongly correlated in their topic choices, but China and Germany are hardly correlated at all.\n",
    "\n",
    "The top five economies most like the US in their topic choices:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d155d506",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iso2_code\n",
       "US    1.000000\n",
       "GB    0.986076\n",
       "CA    0.958069\n",
       "EU    0.953918\n",
       "ES    0.935035\n",
       "Name: US, dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.T.corr()[\"US\"].sort_values(ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7608cdb",
   "metadata": {},
   "source": [
    "Versus the top five most like China:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c79b3d6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iso2_code\n",
       "CN    1.000000\n",
       "HK    0.930800\n",
       "KR    0.718723\n",
       "TW    0.660345\n",
       "JP    0.643677\n",
       "Name: CN, dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.T.corr()[\"CN\"].sort_values(ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f3078e4",
   "metadata": {},
   "source": [
    "[This is a good source for looking up ISO country codes](https://github.com/lukes/ISO-3166-Countries-with-Regional-Codes/blob/master/slim-2/slim-2.csv), in case you're wondering what the codes stand for."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50bd1267",
   "metadata": {},
   "source": [
    "### What do you mean \"linear\"?\n",
    "\n",
    "The Pearson correlation coefficient (i.e., the metric that `.corr()` uses) only works for *linear* relationships. Linear in this case means a relationship that can be described by the formula for a line: $y = mx + b$ (where $m$ and $b$ are constants). We saw this in the examples above, where the scatter plots of highly correlated columns look more or less like diagonal lines.\n",
    "\n",
    "Pearson correlation won't necessarily pick up on *non-linear* relationships—i.e., relationships that can't be modeled using a line. \"Non-linear\" in this case means mathematical formula that produce graphs that have curves in them—say, a parabola, or the result of a trigonometric function. For example, let's say that we have two columns that are both the result of the $sin$ function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "fdf1d42f",
   "metadata": {},
   "outputs": [],
   "source": [
    "alpha = np.sin(np.linspace(0, 50, 100)) * 20\n",
    "beta = np.cos(np.linspace(0, 50, 100)) * 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "3fd16d33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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

github-topics-by-economy.csv

requirements.txt