{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b4ea92ee",
   "metadata": {},
   "source": [
    "# Making slope graphs by combining charts/geoms in plotnine (aka graphing based on multiple columns)\n",
    "\n",
    "If your data isn't in a tidy or long format, sometimes things can be a little more difficult when using plotnine. But don't worry, all things are still possible! Let's take a look.\n",
    "\n",
    "## Steps to a slope graph\n",
    "\n",
    "Let's say we have some information about school test scores, and how they changed between two years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "635d981a",
   "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>school_name</th>\n",
       "      <th>2015_score</th>\n",
       "      <th>2020_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>School A</td>\n",
       "      <td>84</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>School B</td>\n",
       "      <td>64</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>School C</td>\n",
       "      <td>87</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>School D</td>\n",
       "      <td>95</td>\n",
       "      <td>98</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  school_name  2015_score  2020_score\n",
       "0    School A          84          99\n",
       "1    School B          64          89\n",
       "2    School C          87          78\n",
       "3    School D          95          98"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from plotnine import *\n",
    "\n",
    "df = pd.DataFrame([\n",
    "    { 'school_name': 'School A', '2015_score': 84, '2020_score': 99 },\n",
    "    { 'school_name': 'School B', '2015_score': 64, '2020_score': 89 },\n",
    "    { 'school_name': 'School C', '2015_score': 87, '2020_score': 78 },\n",
    "    { 'school_name': 'School D', '2015_score': 95, '2020_score': 98 },\n",
    "])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae6d8726",
   "metadata": {},
   "source": [
    "We *could* reshape (we'll do that down below), but we can learn a little more about ggplot by doing it the long way...\n",
    "\n",
    "First, **let's plot 2015's scores.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "517933f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (319714088)>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    ggplot(df)\n",
    "    + aes(y='2015_score', x=0, color='school_name')\n",
    "    + geom_point()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54f1a9ac",
   "metadata": {},
   "source": [
    "`aes` is smart and realizes that `y='2015_score'` refers to a column, while `x=0` refers to a spot on the graph. While the `y` axis is related to 2015's score, x is *always going to be at zero*.\n",
    "\n",
    "One thing you think *might* work is to just add in another set of points representing 2020's score. We'll do that by adding another `aes` and another `geom_point()` – we'll make these points be over at `x=10` instead of at `x=0`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "802c6080",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (319763959)>"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    ggplot(df)\n",
    "    + aes(y='2015_score', x=0, color='school_name')\n",
    "    + geom_point()\n",
    "    + aes(y='2020_score', x=10, color='school_name')\n",
    "    + geom_point()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0616a6e",
   "metadata": {},
   "source": [
    "Unfortunately it only displays the second set of points! To add multiple points to the plotnine chart, we need to get very very specific, and give each `geom_point` its own `aes`. With that tiny change, our points show up in the right spots!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "f878ef57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (319503357)>"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    ggplot(df)\n",
    "    + geom_point(aes(y='2015_score', x=0, color='school_name'))\n",
    "    + geom_point(aes(y='2020_score', x=10, color='school_name'))\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab2d2a6f",
   "metadata": {},
   "source": [
    "To draw a line between them, we'll use `geom_segment`, which draws a line segment. This segment can take not only an `x` and a `y`, but also an optional `xend` and a `yend` – this makes it draw a point between `(x, y)` and `(xend, yend)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "3910e184",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (319461949)>"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    ggplot(df)\n",
    "    + geom_point(aes(y='2015_score', x=0, color='school_name'))\n",
    "    + geom_point(aes(y='2020_score', x=10, color='school_name'))\n",
    "    + geom_segment(aes(\n",
    "        x=0,\n",
    "        y='2015_score',\n",
    "        xend=10,\n",
    "        yend='2020_score',\n",
    "        color='school_name'\n",
    "    ))\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8a57ae7",
   "metadata": {},
   "source": [
    "Note that if you don't want color, you'll need to use `group='school_name'` instead of `color='school_name'`, otherwise plotnine will try to connect all of the lines together."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "e302dc89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (319899859)>"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    ggplot(df)\n",
    "    + geom_point(aes(y='2015_score', x=0))\n",
    "    + geom_point(aes(y='2020_score', x=10))\n",
    "    + geom_segment(aes(\n",
    "        x=0,\n",
    "        y='2015_score',\n",
    "        xend=10,\n",
    "        yend='2020_score',\n",
    "        group='school_name'\n",
    "    ))\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1544c1c",
   "metadata": {},
   "source": [
    "### The reshaped version\n",
    "\n",
    "To perform the reshaped version, we'll just need to shift from wide to long (or \"tidy\" data) using `.melt`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "d90633c6",
   "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>school_name</th>\n",
       "      <th>year</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>School A</td>\n",
       "      <td>2015</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>School B</td>\n",
       "      <td>2015</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>School C</td>\n",
       "      <td>2015</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>School D</td>\n",
       "      <td>2015</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>School A</td>\n",
       "      <td>2020</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  school_name  year  score\n",
       "0    School A  2015     84\n",
       "1    School B  2015     64\n",
       "2    School C  2015     87\n",
       "3    School D  2015     95\n",
       "4    School A  2020     99"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "melted = df.melt(id_vars='school_name', value_name='score', var_name='year')\n",
    "# Clean up the year column into just a number\n",
    "melted.year = melted.year.str.replace(\"_score\", \"\").astype(int)\n",
    "melted.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f582bb1d",
   "metadata": {},
   "source": [
    "Once the data is in long format, now we can just say, \"put the year on the x axis and the score on the y axis\" and the chart gets built like magic! No more manual fudging with the details of ggplot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "e497dee5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (319982577)>"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    ggplot(melted)\n",
    "    + aes(x='year', y='score', group='school_name', color='school_name')\n",
    "    + geom_point()\n",
    "    + geom_line()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10b1f503",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}