1_make-plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import os\n",
    "import numpy as np\n",
    "import math\n",
    "\n",
    "sns.set_context(\"poster\")\n",
    "sns.set_style(\"white\")\n",
    "\n",
    "sns.set_palette('muted')\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "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>year</th>\n",
       "      <th>count</th>\n",
       "      <th>count_domain</th>\n",
       "      <th>category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>6180</td>\n",
       "      <td>218240</td>\n",
       "      <td>Materials Science</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021</td>\n",
       "      <td>4443</td>\n",
       "      <td>229275</td>\n",
       "      <td>Materials Science</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>2751</td>\n",
       "      <td>203388</td>\n",
       "      <td>Materials Science</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019</td>\n",
       "      <td>1600</td>\n",
       "      <td>193931</td>\n",
       "      <td>Materials Science</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>699</td>\n",
       "      <td>166626</td>\n",
       "      <td>Materials Science</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  count  count_domain           category\n",
       "0  2022   6180        218240  Materials Science\n",
       "1  2021   4443        229275  Materials Science\n",
       "2  2020   2751        203388  Materials Science\n",
       "3  2019   1600        193931  Materials Science\n",
       "4  2018    699        166626  Materials Science"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output_dir = \"./output/\"\n",
    "df = pd.read_csv(\"./data/1-cat.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calculate relevant stats on the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/nl/djsswp9n6l1792htfvwly1lw0000gn/T/ipykernel_98005/1719550333.py:18: FutureWarning: Not prepending group keys to the result index of transform-like apply. In the future, the group keys will be included in the index, regardless of whether the applied function returns a like-indexed object.\n",
      "To preserve the previous behavior, use\n",
      "\n",
      "\t>>> .groupby(..., group_keys=False)\n",
      "\n",
      "To adopt the future behavior and silence this warning, use \n",
      "\n",
      "\t>>> .groupby(..., group_keys=True)\n",
      "  df = df.groupby('category').apply(calculate_stats)\n"
     ]
    }
   ],
   "source": [
    "def growth(x):\n",
    "    return  (x[-1]-x[0]) / x[0]\n",
    "    \n",
    "def cagr(x):\n",
    "    return  (x[-1] / x[0]) ** (1 / (len(x) - 1)) - 1\n",
    "\n",
    "        \n",
    "def calculate_stats(group):\n",
    "    group['yoy_1'] = group.sort_values(by=['year'], ascending=True)['count'].rolling(2,2).apply(growth, raw=True)\n",
    "    group['yoy_2'] = group.sort_values(by=['year'], ascending=True)['count'].rolling(3,2).apply(growth, raw=True)\n",
    "    group['yoy_5'] = group.sort_values(by=['year'], ascending=True)['count'].rolling(6,2).apply(growth, raw=True)\n",
    "    group['cagr_1'] = group.sort_values(by=['year'], ascending=True)['count'].rolling(2,2).apply(cagr, raw=True)*100\n",
    "    group['cagr_2'] = group.sort_values(by=['year'], ascending=True)['count'].rolling(3,2).apply(cagr, raw=True)*100\n",
    "    group['cagr_5'] = group.sort_values(by=['year'], ascending=True)['count'].rolling(6,2).apply(cagr, raw=True)*100\n",
    "    return group\n",
    "\n",
    "df['normalized'] = 100*df['count']/df['count_domain']\n",
    "df = df.groupby('category').apply(calculate_stats)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Show Latest Stats\n",
    "\n",
    "cagr - Compound Annual Growth Rate (%)\n",
    "\n",
    "yoy_n - current count / count n years ago"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>year</th>\n",
       "      <th>count</th>\n",
       "      <th>count_domain</th>\n",
       "      <th>category</th>\n",
       "      <th>normalized</th>\n",
       "      <th>yoy_1</th>\n",
       "      <th>yoy_2</th>\n",
       "      <th>yoy_5</th>\n",
       "      <th>cagr_1</th>\n",
       "      <th>cagr_2</th>\n",
       "      <th>cagr_5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>6180</td>\n",
       "      <td>218240</td>\n",
       "      <td>Materials Science</td>\n",
       "      <td>2.831745</td>\n",
       "      <td>0.390952</td>\n",
       "      <td>1.246456</td>\n",
       "      <td>12.522976</td>\n",
       "      <td>39.095206</td>\n",
       "      <td>49.881815</td>\n",
       "      <td>68.350517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2022</td>\n",
       "      <td>8842</td>\n",
       "      <td>297229</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>2.974811</td>\n",
       "      <td>0.274063</td>\n",
       "      <td>0.783021</td>\n",
       "      <td>4.512469</td>\n",
       "      <td>27.406340</td>\n",
       "      <td>33.529801</td>\n",
       "      <td>40.691944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2022</td>\n",
       "      <td>6829</td>\n",
       "      <td>184803</td>\n",
       "      <td>Physics</td>\n",
       "      <td>3.695286</td>\n",
       "      <td>0.293126</td>\n",
       "      <td>0.940057</td>\n",
       "      <td>12.260194</td>\n",
       "      <td>29.312630</td>\n",
       "      <td>39.285922</td>\n",
       "      <td>67.691086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>2022</td>\n",
       "      <td>2328</td>\n",
       "      <td>34490</td>\n",
       "      <td>Geosciences, Multidisciplinary</td>\n",
       "      <td>6.749783</td>\n",
       "      <td>0.053871</td>\n",
       "      <td>0.640592</td>\n",
       "      <td>12.227273</td>\n",
       "      <td>5.387053</td>\n",
       "      <td>28.085595</td>\n",
       "      <td>67.607737</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     year  count  count_domain                        category  normalized  \\\n",
       "0    2022   6180        218240               Materials Science    2.831745   \n",
       "23   2022   8842        297229                       Chemistry    2.974811   \n",
       "46   2022   6829        184803                         Physics    3.695286   \n",
       "113  2022   2328         34490  Geosciences, Multidisciplinary    6.749783   \n",
       "\n",
       "        yoy_1     yoy_2      yoy_5     cagr_1     cagr_2     cagr_5  \n",
       "0    0.390952  1.246456  12.522976  39.095206  49.881815  68.350517  \n",
       "23   0.274063  0.783021   4.512469  27.406340  33.529801  40.691944  \n",
       "46   0.293126  0.940057  12.260194  29.312630  39.285922  67.691086  \n",
       "113  0.053871  0.640592  12.227273   5.387053  28.085595  67.607737  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.year==2022]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set plot time range\n",
    "years = (2000, 2022)\n",
    "\n",
    "# Set some marker defaults\n",
    "marker_size = 150\n",
    "marker_alpha = 0.6\n",
    "\n",
    "# Set figure save parameters\n",
    "fig_dpi = 1000\n",
    "\n",
    "# Define plot sizes\n",
    "golden = [4*1.618,4]\n",
    "\n",
    "# Define palette options\n",
    "colors = [\"blue\",\"orange\",\"green\"]*3\n",
    "sns.set_palette(\"deep\")\n",
    "sns.palplot(sns.color_palette())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize with MatplotLib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## All Together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Materials Science', 'Chemistry', 'Physics', 'Computer Science',\n",
       "       'Computer Science, Artificial Intelligence',\n",
       "       'Geosciences, Multidisciplinary'], dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.category.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[6.472, 4]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "golden"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Normalized Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"poster\")\n",
    "sns.set_style('white')\n",
    "\n",
    "\n",
    "\n",
    "sns.set_palette('muted')\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(8,8)\n",
    "\n",
    "ax1_list = [\"Materials Science\", \"Chemistry\", \"Physics\"]\n",
    "#ax2_list = [\"Computer Science, Artificial Intelligence\"]\n",
    "\n",
    "\n",
    "\n",
    "data1 = df[df['category'].isin(ax1_list)]\n",
    "#data2 = df[df['category'].isin(ax2_list)]\n",
    "\n",
    "data1 = data1[data1['year']>=2000]\n",
    "\n",
    "g = sns.lineplot(x=\"year\", \n",
    "             y=\"normalized\",\n",
    "             hue=\"category\", \n",
    "             data=data1,\n",
    "             marker=\"o\",\n",
    "             alpha=marker_alpha,\n",
    "             ax=ax)\n",
    "\n",
    "ax.tick_params(bottom=True, left=True)\n",
    "ax.set_xlabel(\"Year\")\n",
    "ax.set_ylabel(\"Percentage of Articles\")\n",
    "plt.tight_layout()\n",
    "plt.legend(title='Domain', loc='upper left')\n",
    "sns.despine()\n",
    "\n",
    "\n",
    "fig.savefig(os.path.join(output_dir,'2023-normalized.png'),\n",
    "             dpi=fig_dpi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Raw Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"poster\")\n",
    "sns.set_style(\"white\")\n",
    "\n",
    "sns.set_palette('muted')\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(9,9)\n",
    "\n",
    "ax1_list = [\"Materials Science\", \"Chemistry\", \"Physics\"]\n",
    "\n",
    "\n",
    "\n",
    "data1 = df[df['category'].isin(ax1_list)]\n",
    "\n",
    "data1 = data1[data1['year']>=2000]\n",
    "\n",
    "g = sns.lineplot(x=\"year\", \n",
    "             y=\"count\",\n",
    "             hue=\"category\", \n",
    "             data=data1,\n",
    "             marker=\"o\",\n",
    "             alpha=marker_alpha,\n",
    "             ax=ax)\n",
    "\n",
    "ax.tick_params(bottom=True, left=True)\n",
    "ax.set_xlabel(\"Year\")\n",
    "ax.set_ylabel(\"Number of Articles\")\n",
    "plt.tight_layout()\n",
    "plt.legend(title='Domain', loc='upper left', prop={'size': 20})\n",
    "sns.despine()\n",
    "\n",
    "\n",
    "fig.savefig(os.path.join(output_dir,'2023-count.png'),\n",
    "             dpi=fig_dpi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/nl/djsswp9n6l1792htfvwly1lw0000gn/T/ipykernel_98005/2321775041.py:11: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  data1 = data1[df['year']>2010]\n",
      "/var/folders/nl/djsswp9n6l1792htfvwly1lw0000gn/T/ipykernel_98005/2321775041.py:12: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  data2 = data2[df['year']>years[0]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 647.2x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(golden)\n",
    "\n",
    "ax1_list = [\"Materials Science\", \"Chemistry\", \"Physics\"]\n",
    "ax2_list = [\"Computer Science\"]\n",
    "\n",
    "\n",
    "data1 = df[df['category'].isin(ax1_list)]\n",
    "data2 = df[df['category'].isin(ax2_list)]\n",
    "\n",
    "data1 = data1[df['year']>2010]\n",
    "data2 = data2[df['year']>years[0]]\n",
    "\n",
    "\n",
    "sns.scatterplot(x=\"year\", y=\"normalized\",\n",
    "             hue=\"category\", data=data1, \n",
    "                s=marker_size, alpha=marker_alpha)\n",
    "\n",
    "ax.set_xlabel(\"Year\")\n",
    "ax.set_ylabel(\"Article %\")\n",
    "sns.despine()\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'data' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[11], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m sns\u001b[38;5;241m.\u001b[39mscatterplot(x\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124myear\u001b[39m\u001b[38;5;124m\"\u001b[39m, y\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnormalized\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m----> 2\u001b[0m                 hue\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcategory\u001b[39m\u001b[38;5;124m\"\u001b[39m, data\u001b[38;5;241m=\u001b[39m\u001b[43mdata\u001b[49m, \n\u001b[1;32m      3\u001b[0m                 s\u001b[38;5;241m=\u001b[39mmarker_size, alpha\u001b[38;5;241m=\u001b[39mmarker_alpha,\n\u001b[1;32m      4\u001b[0m                 ax\u001b[38;5;241m=\u001b[39max)\n\u001b[1;32m      5\u001b[0m ax2 \u001b[38;5;241m=\u001b[39m plt\u001b[38;5;241m.\u001b[39mtwinx()\n\u001b[1;32m      6\u001b[0m sns\u001b[38;5;241m.\u001b[39mlineplot(data\u001b[38;5;241m=\u001b[39mdf\u001b[38;5;241m.\u001b[39mcolumn2, color\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m, ax\u001b[38;5;241m=\u001b[39max2)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'data' is not defined"
     ]
    }
   ],
   "source": [
    "sns.scatterplot(x=\"year\", y=\"normalized\",\n",
    "                hue=\"category\", data=data, \n",
    "                s=marker_size, alpha=marker_alpha,\n",
    "                ax=ax)\n",
    "ax2 = plt.twinx()\n",
    "sns.lineplot(data=df.column2, color=\"b\", ax=ax2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ax = df.plot(x=\"date\", y=\"column1\", legend=False)\n",
    "ax2 = ax.twinx()\n",
    "df.plot(x=\"date\", y=\"column2\", ax=ax2, legend=False, color=\"r\")\n",
    "ax.figure.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(golden)\n",
    "add_events = False\n",
    "\n",
    "category_list = [\"Computer Science\", \"Materials Science\", \"Chemistry\", \"Physics\"]\n",
    "\n",
    "df = df[df['category'].isin(category_list)]\n",
    "data = df[df['year']>years[0]]\n",
    "\n",
    "sns.lineplot(x=\"year\", \n",
    "             y=\"count\",\n",
    "             hue=\"category\", \n",
    "             data=data,\n",
    "             marker=\"o\",\n",
    "             alpha=marker_alpha,\n",
    "             ax=ax)\n",
    "\n",
    "# sns.scatterplot(x=\"year\", y=\"normalized\",\n",
    "#                 hue=\"category\", data=data, \n",
    "#                 s=marker_size, alpha=marker_alpha,\n",
    "#                 ax=ax)\n",
    "ax.set_xlabel(\"Year\")\n",
    "ax.set_ylabel(\"# Articles\")\n",
    "sns.despine()\n",
    "plt.tight_layout()\n",
    "\n",
    "# plt.text(2012, 1.8, 'Preliminary Update', fontsize=12, fontweight=\"bold\")\n",
    "# plt.text(2012, 1.6, '2022-01-20', fontsize=12)\n",
    "# plt.text(2012, 1.4, '2021 data incomplete', fontsize=12)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "if add_events:\n",
    "    plt.axvline(x=2011.58, alpha=0.5) # June 24, 2011, Holdren OSP memo \n",
    "    plt.text(2011.7, 0.75, 'MGI Whitepaper', fontsize=12)\n",
    "    plt.legend(title='', loc='upper left', labels=[\"Materials Science\", \"Chemistry\",\"Physics\"])\n",
    "#     plt.text(2012.5, 0.9, 'MDF Funded')\n",
    "\n",
    "\n",
    "\n",
    "fig.savefig(os.path.join(output_dir,'1-all-line.png'),\n",
    "             dpi=fig_dpi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(golden)\n",
    "add_events = False\n",
    "\n",
    "category_list = [\"Materials Science\", \"Chemistry\", \"Physics\"]\n",
    "\n",
    "df = df[df['category'].isin(category_list)]\n",
    "data = df[df['year']>years[0]]\n",
    "\n",
    "sns.lineplot(x=\"year\", \n",
    "             y=\"normalized\",\n",
    "             hue=\"category\", \n",
    "             data=data,\n",
    "             marker=\"o\",\n",
    "             alpha=marker_alpha,\n",
    "             ax=ax)\n",
    "\n",
    "# sns.scatterplot(x=\"year\", y=\"normalized\",\n",
    "#                 hue=\"category\", data=data, \n",
    "#                 s=marker_size, alpha=marker_alpha,\n",
    "#                 ax=ax)\n",
    "ax.set_xlabel(\"Year\")\n",
    "ax.set_ylabel(\"Article Fraction (%)\")\n",
    "sns.despine()\n",
    "plt.tight_layout()\n",
    "\n",
    "# plt.text(2012, 1.8, 'Preliminary Update', fontsize=12, fontweight=\"bold\")\n",
    "# plt.text(2012, 1.6, '2022-01-20', fontsize=12)\n",
    "# plt.text(2012, 1.4, '2021 data incomplete', fontsize=12)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "if add_events:\n",
    "    plt.axvline(x=2011.58, alpha=0.5) # June 24, 2011, Holdren OSP memo \n",
    "    plt.text(2011.7, 0.75, 'MGI Whitepaper', fontsize=12)\n",
    "    plt.legend(title='', loc='upper left', labels=[\"Materials Science\", \"Chemistry\",\"Physics\"])\n",
    "#     plt.text(2012.5, 0.9, 'MDF Funded')\n",
    "\n",
    "\n",
    "\n",
    "fig.savefig(os.path.join(output_dir,'1-all-line-norm.png'),\n",
    "             dpi=fig_dpi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>count</th>\n",
       "      <th>count_domain</th>\n",
       "      <th>category</th>\n",
       "      <th>normalized</th>\n",
       "      <th>yoy_1</th>\n",
       "      <th>yoy_2</th>\n",
       "      <th>yoy_5</th>\n",
       "      <th>cagr_1</th>\n",
       "      <th>cagr_2</th>\n",
       "      <th>cagr_5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021</td>\n",
       "      <td>3498</td>\n",
       "      <td>215277</td>\n",
       "      <td>Materials Science</td>\n",
       "      <td>1.624883</td>\n",
       "      <td>0.543689</td>\n",
       "      <td>1.807384</td>\n",
       "      <td>28.394958</td>\n",
       "      <td>54.368932</td>\n",
       "      <td>67.552488</td>\n",
       "      <td>96.632169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020</td>\n",
       "      <td>2266</td>\n",
       "      <td>202620</td>\n",
       "      <td>Materials Science</td>\n",
       "      <td>1.118350</td>\n",
       "      <td>0.818620</td>\n",
       "      <td>3.811040</td>\n",
       "      <td>20.177570</td>\n",
       "      <td>81.861958</td>\n",
       "      <td>119.340838</td>\n",
       "      <td>84.151485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019</td>\n",
       "      <td>1246</td>\n",
       "      <td>193664</td>\n",
       "      <td>Materials Science</td>\n",
       "      <td>0.643382</td>\n",
       "      <td>1.645435</td>\n",
       "      <td>4.235294</td>\n",
       "      <td>18.468750</td>\n",
       "      <td>164.543524</td>\n",
       "      <td>128.807651</td>\n",
       "      <td>81.078802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018</td>\n",
       "      <td>471</td>\n",
       "      <td>166364</td>\n",
       "      <td>Materials Science</td>\n",
       "      <td>0.283114</td>\n",
       "      <td>0.978992</td>\n",
       "      <td>2.957983</td>\n",
       "      <td>9.239130</td>\n",
       "      <td>97.899160</td>\n",
       "      <td>98.946807</td>\n",
       "      <td>59.240164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017</td>\n",
       "      <td>238</td>\n",
       "      <td>153367</td>\n",
       "      <td>Materials Science</td>\n",
       "      <td>0.155183</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.224299</td>\n",
       "      <td>7.814815</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>49.140842</td>\n",
       "      <td>54.540616</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2004</td>\n",
       "      <td>16</td>\n",
       "      <td>109419</td>\n",
       "      <td>Physics</td>\n",
       "      <td>0.014623</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.066667</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>3.279556</td>\n",
       "      <td>7.456993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2003</td>\n",
       "      <td>12</td>\n",
       "      <td>103159</td>\n",
       "      <td>Physics</td>\n",
       "      <td>0.011633</td>\n",
       "      <td>-0.200000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-20.000000</td>\n",
       "      <td>15.470054</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>100191</td>\n",
       "      <td>Physics</td>\n",
       "      <td>0.014971</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>66.666667</td>\n",
       "      <td>11.803399</td>\n",
       "      <td>11.803399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2001</td>\n",
       "      <td>9</td>\n",
       "      <td>94797</td>\n",
       "      <td>Physics</td>\n",
       "      <td>0.009494</td>\n",
       "      <td>-0.250000</td>\n",
       "      <td>-0.250000</td>\n",
       "      <td>-0.250000</td>\n",
       "      <td>-25.000000</td>\n",
       "      <td>-25.000000</td>\n",
       "      <td>-25.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2000</td>\n",
       "      <td>12</td>\n",
       "      <td>93891</td>\n",
       "      <td>Physics</td>\n",
       "      <td>0.012781</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    year  count  count_domain           category  normalized     yoy_1  \\\n",
       "0   2021   3498        215277  Materials Science    1.624883  0.543689   \n",
       "1   2020   2266        202620  Materials Science    1.118350  0.818620   \n",
       "2   2019   1246        193664  Materials Science    0.643382  1.645435   \n",
       "3   2018    471        166364  Materials Science    0.283114  0.978992   \n",
       "4   2017    238        153367  Materials Science    0.155183  1.000000   \n",
       "..   ...    ...           ...                ...         ...       ...   \n",
       "61  2004     16        109419            Physics    0.014623  0.333333   \n",
       "62  2003     12        103159            Physics    0.011633 -0.200000   \n",
       "63  2002     15        100191            Physics    0.014971  0.666667   \n",
       "64  2001      9         94797            Physics    0.009494 -0.250000   \n",
       "65  2000     12         93891            Physics    0.012781       NaN   \n",
       "\n",
       "       yoy_2      yoy_5      cagr_1      cagr_2     cagr_5  \n",
       "0   1.807384  28.394958   54.368932   67.552488  96.632169  \n",
       "1   3.811040  20.177570   81.861958  119.340838  84.151485  \n",
       "2   4.235294  18.468750  164.543524  128.807651  81.078802  \n",
       "3   2.957983   9.239130   97.899160   98.946807  59.240164  \n",
       "4   1.224299   7.814815  100.000000   49.140842  54.540616  \n",
       "..       ...        ...         ...         ...        ...  \n",
       "61  0.066667   0.333333   33.333333    3.279556   7.456993  \n",
       "62  0.333333   0.000000  -20.000000   15.470054   0.000000  \n",
       "63  0.250000   0.250000   66.666667   11.803399  11.803399  \n",
       "64 -0.250000  -0.250000  -25.000000  -25.000000 -25.000000  \n",
       "65       NaN        NaN         NaN         NaN        NaN  \n",
       "\n",
       "[66 rows x 11 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>count</th>\n",
       "      <th>count_domain</th>\n",
       "      <th>category</th>\n",
       "      <th>normalized</th>\n",
       "      <th>yoy_1</th>\n",
       "      <th>yoy_2</th>\n",
       "      <th>yoy_5</th>\n",
       "      <th>cagr_1</th>\n",
       "      <th>cagr_2</th>\n",
       "      <th>cagr_5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2021</td>\n",
       "      <td>5801</td>\n",
       "      <td>294371</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>1.970642</td>\n",
       "      <td>0.340652</td>\n",
       "      <td>0.940783</td>\n",
       "      <td>4.202691</td>\n",
       "      <td>34.065172</td>\n",
       "      <td>39.311983</td>\n",
       "      <td>39.073889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2020</td>\n",
       "      <td>4327</td>\n",
       "      <td>283166</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>1.528079</td>\n",
       "      <td>0.447641</td>\n",
       "      <td>1.228115</td>\n",
       "      <td>2.962454</td>\n",
       "      <td>44.764135</td>\n",
       "      <td>49.268729</td>\n",
       "      <td>31.702146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019</td>\n",
       "      <td>2989</td>\n",
       "      <td>288324</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>1.036681</td>\n",
       "      <td>0.539135</td>\n",
       "      <td>1.210799</td>\n",
       "      <td>2.071942</td>\n",
       "      <td>53.913491</td>\n",
       "      <td>48.687552</td>\n",
       "      <td>25.164917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2018</td>\n",
       "      <td>1942</td>\n",
       "      <td>260615</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.745160</td>\n",
       "      <td>0.436391</td>\n",
       "      <td>0.741704</td>\n",
       "      <td>0.826905</td>\n",
       "      <td>43.639053</td>\n",
       "      <td>31.973635</td>\n",
       "      <td>12.808855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2017</td>\n",
       "      <td>1352</td>\n",
       "      <td>247021</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.547322</td>\n",
       "      <td>0.212556</td>\n",
       "      <td>0.238095</td>\n",
       "      <td>0.291309</td>\n",
       "      <td>21.255605</td>\n",
       "      <td>11.269728</td>\n",
       "      <td>5.246098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2016</td>\n",
       "      <td>1115</td>\n",
       "      <td>236354</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.471750</td>\n",
       "      <td>0.021062</td>\n",
       "      <td>0.145940</td>\n",
       "      <td>0.135438</td>\n",
       "      <td>2.106227</td>\n",
       "      <td>7.048605</td>\n",
       "      <td>2.572910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2015</td>\n",
       "      <td>1092</td>\n",
       "      <td>229803</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.475190</td>\n",
       "      <td>0.122302</td>\n",
       "      <td>0.027281</td>\n",
       "      <td>0.189542</td>\n",
       "      <td>12.230216</td>\n",
       "      <td>1.354885</td>\n",
       "      <td>3.532331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2014</td>\n",
       "      <td>973</td>\n",
       "      <td>222546</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.437213</td>\n",
       "      <td>-0.084666</td>\n",
       "      <td>-0.070678</td>\n",
       "      <td>0.007246</td>\n",
       "      <td>-8.466604</td>\n",
       "      <td>-3.598658</td>\n",
       "      <td>0.144509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2013</td>\n",
       "      <td>1063</td>\n",
       "      <td>206685</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.514309</td>\n",
       "      <td>0.015282</td>\n",
       "      <td>0.082485</td>\n",
       "      <td>0.174586</td>\n",
       "      <td>1.528176</td>\n",
       "      <td>4.042526</td>\n",
       "      <td>3.270656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2012</td>\n",
       "      <td>1047</td>\n",
       "      <td>198814</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.526623</td>\n",
       "      <td>0.066191</td>\n",
       "      <td>0.140523</td>\n",
       "      <td>0.352713</td>\n",
       "      <td>6.619145</td>\n",
       "      <td>6.795266</td>\n",
       "      <td>6.228523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2011</td>\n",
       "      <td>982</td>\n",
       "      <td>192372</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.510469</td>\n",
       "      <td>0.069717</td>\n",
       "      <td>0.016563</td>\n",
       "      <td>0.336054</td>\n",
       "      <td>6.971678</td>\n",
       "      <td>0.824756</td>\n",
       "      <td>5.965582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2010</td>\n",
       "      <td>918</td>\n",
       "      <td>173352</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.529558</td>\n",
       "      <td>-0.049689</td>\n",
       "      <td>0.014365</td>\n",
       "      <td>0.344070</td>\n",
       "      <td>-4.968944</td>\n",
       "      <td>0.715671</td>\n",
       "      <td>6.092430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2009</td>\n",
       "      <td>966</td>\n",
       "      <td>170592</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.566263</td>\n",
       "      <td>0.067403</td>\n",
       "      <td>0.248062</td>\n",
       "      <td>0.502333</td>\n",
       "      <td>6.740331</td>\n",
       "      <td>11.716696</td>\n",
       "      <td>8.480888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2008</td>\n",
       "      <td>905</td>\n",
       "      <td>165960</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.545312</td>\n",
       "      <td>0.169251</td>\n",
       "      <td>0.231293</td>\n",
       "      <td>0.737044</td>\n",
       "      <td>16.925065</td>\n",
       "      <td>10.963621</td>\n",
       "      <td>11.676597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2007</td>\n",
       "      <td>774</td>\n",
       "      <td>157396</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.491753</td>\n",
       "      <td>0.053061</td>\n",
       "      <td>0.133236</td>\n",
       "      <td>0.723831</td>\n",
       "      <td>5.306122</td>\n",
       "      <td>6.453545</td>\n",
       "      <td>11.506176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2006</td>\n",
       "      <td>735</td>\n",
       "      <td>153534</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.478721</td>\n",
       "      <td>0.076135</td>\n",
       "      <td>0.143079</td>\n",
       "      <td>0.914062</td>\n",
       "      <td>7.613470</td>\n",
       "      <td>6.914887</td>\n",
       "      <td>13.865255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2005</td>\n",
       "      <td>683</td>\n",
       "      <td>144206</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.473628</td>\n",
       "      <td>0.062208</td>\n",
       "      <td>0.310940</td>\n",
       "      <td>1.127726</td>\n",
       "      <td>6.220840</td>\n",
       "      <td>14.496310</td>\n",
       "      <td>16.300916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2004</td>\n",
       "      <td>643</td>\n",
       "      <td>134367</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.478540</td>\n",
       "      <td>0.234165</td>\n",
       "      <td>0.432071</td>\n",
       "      <td>1.003115</td>\n",
       "      <td>23.416507</td>\n",
       "      <td>19.669180</td>\n",
       "      <td>18.966993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2003</td>\n",
       "      <td>521</td>\n",
       "      <td>125499</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.415143</td>\n",
       "      <td>0.160356</td>\n",
       "      <td>0.356771</td>\n",
       "      <td>0.623053</td>\n",
       "      <td>16.035635</td>\n",
       "      <td>16.480506</td>\n",
       "      <td>17.519760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2002</td>\n",
       "      <td>449</td>\n",
       "      <td>120465</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.372722</td>\n",
       "      <td>0.169271</td>\n",
       "      <td>0.398754</td>\n",
       "      <td>0.398754</td>\n",
       "      <td>16.927083</td>\n",
       "      <td>18.268926</td>\n",
       "      <td>18.268926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2001</td>\n",
       "      <td>384</td>\n",
       "      <td>115755</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.331735</td>\n",
       "      <td>0.196262</td>\n",
       "      <td>0.196262</td>\n",
       "      <td>0.196262</td>\n",
       "      <td>19.626168</td>\n",
       "      <td>19.626168</td>\n",
       "      <td>19.626168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2000</td>\n",
       "      <td>321</td>\n",
       "      <td>113643</td>\n",
       "      <td>Chemistry</td>\n",
       "      <td>0.282464</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    year  count  count_domain   category  normalized     yoy_1     yoy_2  \\\n",
       "22  2021   5801        294371  Chemistry    1.970642  0.340652  0.940783   \n",
       "23  2020   4327        283166  Chemistry    1.528079  0.447641  1.228115   \n",
       "24  2019   2989        288324  Chemistry    1.036681  0.539135  1.210799   \n",
       "25  2018   1942        260615  Chemistry    0.745160  0.436391  0.741704   \n",
       "26  2017   1352        247021  Chemistry    0.547322  0.212556  0.238095   \n",
       "27  2016   1115        236354  Chemistry    0.471750  0.021062  0.145940   \n",
       "28  2015   1092        229803  Chemistry    0.475190  0.122302  0.027281   \n",
       "29  2014    973        222546  Chemistry    0.437213 -0.084666 -0.070678   \n",
       "30  2013   1063        206685  Chemistry    0.514309  0.015282  0.082485   \n",
       "31  2012   1047        198814  Chemistry    0.526623  0.066191  0.140523   \n",
       "32  2011    982        192372  Chemistry    0.510469  0.069717  0.016563   \n",
       "33  2010    918        173352  Chemistry    0.529558 -0.049689  0.014365   \n",
       "34  2009    966        170592  Chemistry    0.566263  0.067403  0.248062   \n",
       "35  2008    905        165960  Chemistry    0.545312  0.169251  0.231293   \n",
       "36  2007    774        157396  Chemistry    0.491753  0.053061  0.133236   \n",
       "37  2006    735        153534  Chemistry    0.478721  0.076135  0.143079   \n",
       "38  2005    683        144206  Chemistry    0.473628  0.062208  0.310940   \n",
       "39  2004    643        134367  Chemistry    0.478540  0.234165  0.432071   \n",
       "40  2003    521        125499  Chemistry    0.415143  0.160356  0.356771   \n",
       "41  2002    449        120465  Chemistry    0.372722  0.169271  0.398754   \n",
       "42  2001    384        115755  Chemistry    0.331735  0.196262  0.196262   \n",
       "43  2000    321        113643  Chemistry    0.282464       NaN       NaN   \n",
       "\n",
       "       yoy_5     cagr_1     cagr_2     cagr_5  \n",
       "22  4.202691  34.065172  39.311983  39.073889  \n",
       "23  2.962454  44.764135  49.268729  31.702146  \n",
       "24  2.071942  53.913491  48.687552  25.164917  \n",
       "25  0.826905  43.639053  31.973635  12.808855  \n",
       "26  0.291309  21.255605  11.269728   5.246098  \n",
       "27  0.135438   2.106227   7.048605   2.572910  \n",
       "28  0.189542  12.230216   1.354885   3.532331  \n",
       "29  0.007246  -8.466604  -3.598658   0.144509  \n",
       "30  0.174586   1.528176   4.042526   3.270656  \n",
       "31  0.352713   6.619145   6.795266   6.228523  \n",
       "32  0.336054   6.971678   0.824756   5.965582  \n",
       "33  0.344070  -4.968944   0.715671   6.092430  \n",
       "34  0.502333   6.740331  11.716696   8.480888  \n",
       "35  0.737044  16.925065  10.963621  11.676597  \n",
       "36  0.723831   5.306122   6.453545  11.506176  \n",
       "37  0.914062   7.613470   6.914887  13.865255  \n",
       "38  1.127726   6.220840  14.496310  16.300916  \n",
       "39  1.003115  23.416507  19.669180  18.966993  \n",
       "40  0.623053  16.035635  16.480506  17.519760  \n",
       "41  0.398754  16.927083  18.268926  18.268926  \n",
       "42  0.196262  19.626168  19.626168  19.626168  \n",
       "43       NaN        NaN        NaN        NaN  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.category=='Chemistry']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Initialize a grid of plots with an Axes for each domain\n",
    "categories = df['category'].unique()\n",
    "f, axs = plt.subplots(1,len(categories), sharey=True, figsize=(15,6))\n",
    "\n",
    "for i, cat in enumerate(categories):\n",
    "    data = df[(df['category']==cat) & (df['year']>years[0])]\n",
    "    axs[i].plot(data['year'], data['normalized'], \n",
    "                marker=\"o\", markersize=12, color=colors[i], \n",
    "                alpha=marker_alpha) #c=colors[i], alpha=marker_alpha, s=marker_size)\n",
    "    axs[i].set_title(cat)\n",
    "    axs[i].set_xlabel(\"Year\")\n",
    "    axs[i].set_ylabel(\"Article %\")\n",
    "    sns.despine()\n",
    "    plt.tight_layout()\n",
    "f.savefig(os.path.join(output_dir,'1-grid-line-norm.png'),dpi=fig_dpi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Initialize a grid of plots with an Axes for each domain\n",
    "categories = df['category'].unique()\n",
    "f, axs = plt.subplots(1,len(categories), sharey=True, figsize=(15,6))\n",
    "\n",
    "for i, cat in enumerate(categories):\n",
    "    data = df[(df['category']==cat) & (df['year']>years[0])]\n",
    "    axs[i].plot(data['year'], data['count'], \n",
    "                marker=\"o\", markersize=12, color=colors[i], \n",
    "                alpha=marker_alpha) #c=colors[i], alpha=marker_alpha, s=marker_size)\n",
    "    axs[i].set_title(cat)\n",
    "    axs[i].set_xlabel(\"Year\")\n",
    "    axs[i].set_ylabel(\"Article Count\")\n",
    "    sns.despine()\n",
    "    plt.tight_layout()\n",
    "f.savefig(os.path.join(output_dir,'1-grid-line.png'),dpi=fig_dpi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = df[df['year']>years[0]]\n",
    "sns_fig = sns.lmplot(x=\"year\", y=\"normalized\", col=\"category\", \n",
    "           hue=\"category\", data=data,\n",
    "           col_wrap=3, ci=None, palette=\"muted\", height=4, fit_reg=False,\n",
    "           scatter_kws={\"s\": marker_size/2, \"alpha\": marker_alpha})\n",
    "sns_fig.set_axis_labels(\"Year\",\"Article %\")\n",
    "sns_fig.savefig(os.path.join(output_dir,\"1-grid-norm.png\"), dpi=fig_dpi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = df[df['year']>years[0]]\n",
    "sns_fig = sns.lmplot(x=\"year\", y=\"count\", col=\"category\", \n",
    "           hue=\"category\", data=data,\n",
    "           col_wrap=3, ci=None, palette=\"muted\", height=4, fit_reg=False,\n",
    "           scatter_kws={\"s\": marker_size/2, \"alpha\": marker_alpha})\n",
    "sns_fig.set_axis_labels(\"Year\",\"Article Count\")\n",
    "sns_fig.savefig(os.path.join(output_dir,\"1-grid.png\"), dpi=fig_dpi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Individual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i,category in enumerate(df['category'].unique()):\n",
    "    fig = plt.figure()\n",
    "\n",
    "    data = df[(df['category']==category) & (df['year']>years[0])]\n",
    "    ax = sns.scatterplot(x=\"year\", y=\"normalized\",\n",
    "                        data=data, s=marker_size, \n",
    "                        alpha=marker_alpha, color=colors[i])\n",
    "    ax.set_xlabel(\"Year\")\n",
    "    ax.set_ylabel(\"Article %\")\n",
    "    sns.despine()\n",
    "    fig.savefig(os.path.join(output_dir,'1-{}-norm.png'.format(category)),dpi=fig_dpi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i,category in enumerate(df['category'].unique()):\n",
    "    fig = plt.figure()\n",
    "\n",
    "    data = df[(df['category']==category) & (df['year']>years[0])]\n",
    "    ax = sns.scatterplot(x=\"year\", y=\"count\",\n",
    "                        data=data, s=marker_size, \n",
    "                        alpha=marker_alpha, color=colors[i])\n",
    "    ax.set_xlabel(\"Year\")\n",
    "    ax.set_ylabel(\"Article Count\")\n",
    "    sns.despine()\n",
    "    fig.savefig(os.path.join(output_dir,'1-{}.png'.format(category)),dpi=fig_dpi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize with Altair"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## All Together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: altair in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (4.2.0)\n",
      "Requirement already satisfied: jsonschema>=3.0 in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (from altair) (4.4.0)\n",
      "Requirement already satisfied: pandas>=0.18 in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (from altair) (1.2.2)\n",
      "Requirement already satisfied: entrypoints in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (from altair) (0.3)\n",
      "Requirement already satisfied: numpy in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (from altair) (1.22.1)\n",
      "Requirement already satisfied: toolz in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages/toolz-0.11.1-py3.9.egg (from altair) (0.11.1)\n",
      "Requirement already satisfied: jinja2 in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (from altair) (2.11.3)\n",
      "Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (from jsonschema>=3.0->altair) (0.17.3)\n",
      "Requirement already satisfied: attrs>=17.4.0 in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (from jsonschema>=3.0->altair) (20.3.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7.3 in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (from pandas>=0.18->altair) (2.8.1)\n",
      "Requirement already satisfied: pytz>=2017.3 in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (from pandas>=0.18->altair) (2021.1)\n",
      "Requirement already satisfied: MarkupSafe>=0.23 in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (from jinja2->altair) (1.1.1)\n",
      "Requirement already satisfied: six>=1.5 in /Users/ben/anaconda3/envs/jupyter/lib/python3.9/site-packages (from python-dateutil>=2.7.3->pandas>=0.18->altair) (1.16.0)\n",
      "\u001b[33mWARNING: You are using pip version 21.3.1; however, version 22.0.3 is available.\n",
      "You should consider upgrading via the '/Users/ben/anaconda3/envs/jupyter/bin/python -m pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install altair"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import altair as alt\n",
    "data = df[df['category']=='Chemistry']\n",
    "\n",
    "charts = []\n",
    "\n",
    "for i, category in enumerate(df['category'].unique()):\n",
    "    data = df[df['category']==category]\n",
    "    chart = alt.Chart(data[['year','count']]).mark_circle(size=marker_size, color=colors[i]).encode(\n",
    "        x=alt.X('year', scale=alt.Scale(domain=(2000, 2019))),\n",
    "        y=alt.Y('count')).properties(\n",
    "        width=500,\n",
    "        height=350,\n",
    "        title=category\n",
    "    )\n",
    "    charts.append(chart)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## All Together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div id=\"altair-viz-941a1e9b27574c658c1c7555d4d2a5c0\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
       "  (function(spec, embedOpt){\n",
       "    let outputDiv = document.currentScript.previousElementSibling;\n",
       "    if (outputDiv.id !== \"altair-viz-941a1e9b27574c658c1c7555d4d2a5c0\") {\n",
       "      outputDiv = document.getElementById(\"altair-viz-941a1e9b27574c658c1c7555d4d2a5c0\");\n",
       "    }\n",
       "    const paths = {\n",
       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.17.0?noext\",\n",
       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
       "    };\n",
       "\n",
       "    function maybeLoadScript(lib, version) {\n",
       "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
       "      return (VEGA_DEBUG[key] == version) ?\n",
       "        Promise.resolve(paths[lib]) :\n",
       "        new Promise(function(resolve, reject) {\n",
       "          var s = document.createElement('script');\n",
       "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "          s.async = true;\n",
       "          s.onload = () => {\n",
       "            VEGA_DEBUG[key] = version;\n",
       "            return resolve(paths[lib]);\n",
       "          };\n",
       "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
       "          s.src = paths[lib];\n",
       "        });\n",
       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else {\n",
       "      maybeLoadScript(\"vega\", \"5\")\n",
       "        .then(() => maybeLoadScript(\"vega-lite\", \"4.17.0\"))\n",
       "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"layer\": [{\"data\": {\"name\": \"data-08d307d0bc8762788144a993a1f3f3fe\"}, \"mark\": {\"type\": \"circle\", \"color\": \"blue\", \"size\": 150}, \"encoding\": {\"x\": {\"field\": \"year\", \"scale\": {\"domain\": [2000, 2019]}, \"type\": \"quantitative\"}, \"y\": {\"field\": \"count\", \"type\": \"quantitative\"}}, \"height\": 350, \"title\": \"Materials Science\", \"width\": 500}, {\"data\": {\"name\": \"data-f3eeb04e7142781a92128d38c6849748\"}, \"mark\": {\"type\": \"circle\", \"color\": \"orange\", \"size\": 150}, \"encoding\": {\"x\": {\"field\": \"year\", \"scale\": {\"domain\": [2000, 2019]}, \"type\": \"quantitative\"}, \"y\": {\"field\": \"count\", \"type\": \"quantitative\"}}, \"height\": 350, \"title\": \"Chemistry\", \"width\": 500}, {\"data\": {\"name\": \"data-67c508535019cdcae2e95bc67cb64cf9\"}, \"mark\": {\"type\": \"circle\", \"color\": \"green\", \"size\": 150}, \"encoding\": {\"x\": {\"field\": \"year\", \"scale\": {\"domain\": [2000, 2019]}, \"type\": \"quantitative\"}, \"y\": {\"field\": \"count\", \"type\": \"quantitative\"}}, \"height\": 350, \"title\": \"Physics\", \"width\": 500}], \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.17.0.json\", \"datasets\": {\"data-08d307d0bc8762788144a993a1f3f3fe\": [{\"year\": 2021, \"count\": 3498}, {\"year\": 2020, \"count\": 2266}, {\"year\": 2019, \"count\": 1246}, {\"year\": 2018, \"count\": 471}, {\"year\": 2017, \"count\": 238}, {\"year\": 2016, \"count\": 119}, {\"year\": 2015, \"count\": 107}, {\"year\": 2014, \"count\": 64}, {\"year\": 2013, \"count\": 46}, {\"year\": 2012, \"count\": 27}, {\"year\": 2011, \"count\": 29}, {\"year\": 2010, \"count\": 32}, {\"year\": 2009, \"count\": 46}, {\"year\": 2008, \"count\": 26}, {\"year\": 2007, \"count\": 22}, {\"year\": 2006, \"count\": 26}, {\"year\": 2005, \"count\": 17}, {\"year\": 2004, \"count\": 10}, {\"year\": 2003, \"count\": 9}, {\"year\": 2002, \"count\": 3}, {\"year\": 2001, \"count\": 9}, {\"year\": 2000, \"count\": 6}], \"data-f3eeb04e7142781a92128d38c6849748\": [{\"year\": 2021, \"count\": 5801}, {\"year\": 2020, \"count\": 4327}, {\"year\": 2019, \"count\": 2989}, {\"year\": 2018, \"count\": 1942}, {\"year\": 2017, \"count\": 1352}, {\"year\": 2016, \"count\": 1115}, {\"year\": 2015, \"count\": 1092}, {\"year\": 2014, \"count\": 973}, {\"year\": 2013, \"count\": 1063}, {\"year\": 2012, \"count\": 1047}, {\"year\": 2011, \"count\": 982}, {\"year\": 2010, \"count\": 918}, {\"year\": 2009, \"count\": 966}, {\"year\": 2008, \"count\": 905}, {\"year\": 2007, \"count\": 774}, {\"year\": 2006, \"count\": 735}, {\"year\": 2005, \"count\": 683}, {\"year\": 2004, \"count\": 643}, {\"year\": 2003, \"count\": 521}, {\"year\": 2002, \"count\": 449}, {\"year\": 2001, \"count\": 384}, {\"year\": 2000, \"count\": 321}], \"data-67c508535019cdcae2e95bc67cb64cf9\": [{\"year\": 2021, \"count\": 4463}, {\"year\": 2020, \"count\": 3121}, {\"year\": 2019, \"count\": 1663}, {\"year\": 2018, \"count\": 775}, {\"year\": 2017, \"count\": 383}, {\"year\": 2016, \"count\": 219}, {\"year\": 2015, \"count\": 156}, {\"year\": 2014, \"count\": 94}, {\"year\": 2013, \"count\": 84}, {\"year\": 2012, \"count\": 59}, {\"year\": 2011, \"count\": 70}, {\"year\": 2010, \"count\": 47}, {\"year\": 2009, \"count\": 51}, {\"year\": 2008, \"count\": 43}, {\"year\": 2007, \"count\": 39}, {\"year\": 2006, \"count\": 33}, {\"year\": 2005, \"count\": 37}, {\"year\": 2004, \"count\": 16}, {\"year\": 2003, \"count\": 12}, {\"year\": 2002, \"count\": 15}, {\"year\": 2001, \"count\": 9}, {\"year\": 2000, \"count\": 12}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.LayerChart(...)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "charts[0] + charts[1] + charts[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div id=\"altair-viz-78c9ed8d84d94250bf808382df99e2b0\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
       "  (function(spec, embedOpt){\n",
       "    let outputDiv = document.currentScript.previousElementSibling;\n",
       "    if (outputDiv.id !== \"altair-viz-78c9ed8d84d94250bf808382df99e2b0\") {\n",
       "      outputDiv = document.getElementById(\"altair-viz-78c9ed8d84d94250bf808382df99e2b0\");\n",
       "    }\n",
       "    const paths = {\n",
       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.17.0?noext\",\n",
       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
       "    };\n",
       "\n",
       "    function maybeLoadScript(lib, version) {\n",
       "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
       "      return (VEGA_DEBUG[key] == version) ?\n",
       "        Promise.resolve(paths[lib]) :\n",
       "        new Promise(function(resolve, reject) {\n",
       "          var s = document.createElement('script');\n",
       "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "          s.async = true;\n",
       "          s.onload = () => {\n",
       "            VEGA_DEBUG[key] = version;\n",
       "            return resolve(paths[lib]);\n",
       "          };\n",
       "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
       "          s.src = paths[lib];\n",
       "        });\n",
       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else {\n",
       "      maybeLoadScript(\"vega\", \"5\")\n",
       "        .then(() => maybeLoadScript(\"vega-lite\", \"4.17.0\"))\n",
       "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"hconcat\": [{\"data\": {\"name\": \"data-08d307d0bc8762788144a993a1f3f3fe\"}, \"mark\": {\"type\": \"circle\", \"color\": \"blue\", \"size\": 150}, \"encoding\": {\"x\": {\"field\": \"year\", \"scale\": {\"domain\": [2000, 2019]}, \"type\": \"quantitative\"}, \"y\": {\"field\": \"count\", \"type\": \"quantitative\"}}, \"height\": 350, \"title\": \"Materials Science\", \"width\": 500}, {\"data\": {\"name\": \"data-f3eeb04e7142781a92128d38c6849748\"}, \"mark\": {\"type\": \"circle\", \"color\": \"orange\", \"size\": 150}, \"encoding\": {\"x\": {\"field\": \"year\", \"scale\": {\"domain\": [2000, 2019]}, \"type\": \"quantitative\"}, \"y\": {\"field\": \"count\", \"type\": \"quantitative\"}}, \"height\": 350, \"title\": \"Chemistry\", \"width\": 500}, {\"data\": {\"name\": \"data-67c508535019cdcae2e95bc67cb64cf9\"}, \"mark\": {\"type\": \"circle\", \"color\": \"green\", \"size\": 150}, \"encoding\": {\"x\": {\"field\": \"year\", \"scale\": {\"domain\": [2000, 2019]}, \"type\": \"quantitative\"}, \"y\": {\"field\": \"count\", \"type\": \"quantitative\"}}, \"height\": 350, \"title\": \"Physics\", \"width\": 500}], \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.17.0.json\", \"datasets\": {\"data-08d307d0bc8762788144a993a1f3f3fe\": [{\"year\": 2021, \"count\": 3498}, {\"year\": 2020, \"count\": 2266}, {\"year\": 2019, \"count\": 1246}, {\"year\": 2018, \"count\": 471}, {\"year\": 2017, \"count\": 238}, {\"year\": 2016, \"count\": 119}, {\"year\": 2015, \"count\": 107}, {\"year\": 2014, \"count\": 64}, {\"year\": 2013, \"count\": 46}, {\"year\": 2012, \"count\": 27}, {\"year\": 2011, \"count\": 29}, {\"year\": 2010, \"count\": 32}, {\"year\": 2009, \"count\": 46}, {\"year\": 2008, \"count\": 26}, {\"year\": 2007, \"count\": 22}, {\"year\": 2006, \"count\": 26}, {\"year\": 2005, \"count\": 17}, {\"year\": 2004, \"count\": 10}, {\"year\": 2003, \"count\": 9}, {\"year\": 2002, \"count\": 3}, {\"year\": 2001, \"count\": 9}, {\"year\": 2000, \"count\": 6}], \"data-f3eeb04e7142781a92128d38c6849748\": [{\"year\": 2021, \"count\": 5801}, {\"year\": 2020, \"count\": 4327}, {\"year\": 2019, \"count\": 2989}, {\"year\": 2018, \"count\": 1942}, {\"year\": 2017, \"count\": 1352}, {\"year\": 2016, \"count\": 1115}, {\"year\": 2015, \"count\": 1092}, {\"year\": 2014, \"count\": 973}, {\"year\": 2013, \"count\": 1063}, {\"year\": 2012, \"count\": 1047}, {\"year\": 2011, \"count\": 982}, {\"year\": 2010, \"count\": 918}, {\"year\": 2009, \"count\": 966}, {\"year\": 2008, \"count\": 905}, {\"year\": 2007, \"count\": 774}, {\"year\": 2006, \"count\": 735}, {\"year\": 2005, \"count\": 683}, {\"year\": 2004, \"count\": 643}, {\"year\": 2003, \"count\": 521}, {\"year\": 2002, \"count\": 449}, {\"year\": 2001, \"count\": 384}, {\"year\": 2000, \"count\": 321}], \"data-67c508535019cdcae2e95bc67cb64cf9\": [{\"year\": 2021, \"count\": 4463}, {\"year\": 2020, \"count\": 3121}, {\"year\": 2019, \"count\": 1663}, {\"year\": 2018, \"count\": 775}, {\"year\": 2017, \"count\": 383}, {\"year\": 2016, \"count\": 219}, {\"year\": 2015, \"count\": 156}, {\"year\": 2014, \"count\": 94}, {\"year\": 2013, \"count\": 84}, {\"year\": 2012, \"count\": 59}, {\"year\": 2011, \"count\": 70}, {\"year\": 2010, \"count\": 47}, {\"year\": 2009, \"count\": 51}, {\"year\": 2008, \"count\": 43}, {\"year\": 2007, \"count\": 39}, {\"year\": 2006, \"count\": 33}, {\"year\": 2005, \"count\": 37}, {\"year\": 2004, \"count\": 16}, {\"year\": 2003, \"count\": 12}, {\"year\": 2002, \"count\": 15}, {\"year\": 2001, \"count\": 9}, {\"year\": 2000, \"count\": 12}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.HConcatChart(...)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "charts[0] | charts[1] | charts[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Individual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div id=\"altair-viz-b98bf6753cd045cf8b3d716bef9da061\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
       "  (function(spec, embedOpt){\n",
       "    let outputDiv = document.currentScript.previousElementSibling;\n",
       "    if (outputDiv.id !== \"altair-viz-b98bf6753cd045cf8b3d716bef9da061\") {\n",
       "      outputDiv = document.getElementById(\"altair-viz-b98bf6753cd045cf8b3d716bef9da061\");\n",
       "    }\n",
       "    const paths = {\n",
       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.17.0?noext\",\n",
       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
       "    };\n",
       "\n",
       "    function maybeLoadScript(lib, version) {\n",
       "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
       "      return (VEGA_DEBUG[key] == version) ?\n",
       "        Promise.resolve(paths[lib]) :\n",
       "        new Promise(function(resolve, reject) {\n",
       "          var s = document.createElement('script');\n",
       "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "          s.async = true;\n",
       "          s.onload = () => {\n",
       "            VEGA_DEBUG[key] = version;\n",
       "            return resolve(paths[lib]);\n",
       "          };\n",
       "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
       "          s.src = paths[lib];\n",
       "        });\n",
       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else {\n",
       "      maybeLoadScript(\"vega\", \"5\")\n",
       "        .then(() => maybeLoadScript(\"vega-lite\", \"4.17.0\"))\n",
       "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-08d307d0bc8762788144a993a1f3f3fe\"}, \"mark\": {\"type\": \"circle\", \"color\": \"blue\", \"size\": 150}, \"encoding\": {\"x\": {\"field\": \"year\", \"scale\": {\"domain\": [2000, 2019]}, \"type\": \"quantitative\"}, \"y\": {\"field\": \"count\", \"type\": \"quantitative\"}}, \"height\": 350, \"title\": \"Materials Science\", \"width\": 500, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.17.0.json\", \"datasets\": {\"data-08d307d0bc8762788144a993a1f3f3fe\": [{\"year\": 2021, \"count\": 3498}, {\"year\": 2020, \"count\": 2266}, {\"year\": 2019, \"count\": 1246}, {\"year\": 2018, \"count\": 471}, {\"year\": 2017, \"count\": 238}, {\"year\": 2016, \"count\": 119}, {\"year\": 2015, \"count\": 107}, {\"year\": 2014, \"count\": 64}, {\"year\": 2013, \"count\": 46}, {\"year\": 2012, \"count\": 27}, {\"year\": 2011, \"count\": 29}, {\"year\": 2010, \"count\": 32}, {\"year\": 2009, \"count\": 46}, {\"year\": 2008, \"count\": 26}, {\"year\": 2007, \"count\": 22}, {\"year\": 2006, \"count\": 26}, {\"year\": 2005, \"count\": 17}, {\"year\": 2004, \"count\": 10}, {\"year\": 2003, \"count\": 9}, {\"year\": 2002, \"count\": 3}, {\"year\": 2001, \"count\": 9}, {\"year\": 2000, \"count\": 6}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "charts[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div id=\"altair-viz-76c5472e0d6d4797ae6fca799d04cde6\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
       "  (function(spec, embedOpt){\n",
       "    let outputDiv = document.currentScript.previousElementSibling;\n",
       "    if (outputDiv.id !== \"altair-viz-76c5472e0d6d4797ae6fca799d04cde6\") {\n",
       "      outputDiv = document.getElementById(\"altair-viz-76c5472e0d6d4797ae6fca799d04cde6\");\n",
       "    }\n",
       "    const paths = {\n",
       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.17.0?noext\",\n",
       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
       "    };\n",
       "\n",
       "    function maybeLoadScript(lib, version) {\n",
       "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
       "      return (VEGA_DEBUG[key] == version) ?\n",
       "        Promise.resolve(paths[lib]) :\n",
       "        new Promise(function(resolve, reject) {\n",
       "          var s = document.createElement('script');\n",
       "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "          s.async = true;\n",
       "          s.onload = () => {\n",
       "            VEGA_DEBUG[key] = version;\n",
       "            return resolve(paths[lib]);\n",
       "          };\n",
       "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
       "          s.src = paths[lib];\n",
       "        });\n",
       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else {\n",
       "      maybeLoadScript(\"vega\", \"5\")\n",
       "        .then(() => maybeLoadScript(\"vega-lite\", \"4.17.0\"))\n",
       "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-f3eeb04e7142781a92128d38c6849748\"}, \"mark\": {\"type\": \"circle\", \"color\": \"orange\", \"size\": 150}, \"encoding\": {\"x\": {\"field\": \"year\", \"scale\": {\"domain\": [2000, 2019]}, \"type\": \"quantitative\"}, \"y\": {\"field\": \"count\", \"type\": \"quantitative\"}}, \"height\": 350, \"title\": \"Chemistry\", \"width\": 500, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.17.0.json\", \"datasets\": {\"data-f3eeb04e7142781a92128d38c6849748\": [{\"year\": 2021, \"count\": 5801}, {\"year\": 2020, \"count\": 4327}, {\"year\": 2019, \"count\": 2989}, {\"year\": 2018, \"count\": 1942}, {\"year\": 2017, \"count\": 1352}, {\"year\": 2016, \"count\": 1115}, {\"year\": 2015, \"count\": 1092}, {\"year\": 2014, \"count\": 973}, {\"year\": 2013, \"count\": 1063}, {\"year\": 2012, \"count\": 1047}, {\"year\": 2011, \"count\": 982}, {\"year\": 2010, \"count\": 918}, {\"year\": 2009, \"count\": 966}, {\"year\": 2008, \"count\": 905}, {\"year\": 2007, \"count\": 774}, {\"year\": 2006, \"count\": 735}, {\"year\": 2005, \"count\": 683}, {\"year\": 2004, \"count\": 643}, {\"year\": 2003, \"count\": 521}, {\"year\": 2002, \"count\": 449}, {\"year\": 2001, \"count\": 384}, {\"year\": 2000, \"count\": 321}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
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   "cell_type": "code",
   "execution_count": 22,
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   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div id=\"altair-viz-c036d83c651d431cb48e0f2ba6afbac3\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
       "  (function(spec, embedOpt){\n",
       "    let outputDiv = document.currentScript.previousElementSibling;\n",
       "    if (outputDiv.id !== \"altair-viz-c036d83c651d431cb48e0f2ba6afbac3\") {\n",
       "      outputDiv = document.getElementById(\"altair-viz-c036d83c651d431cb48e0f2ba6afbac3\");\n",
       "    }\n",
       "    const paths = {\n",
       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.17.0?noext\",\n",
       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
       "    };\n",
       "\n",
       "    function maybeLoadScript(lib, version) {\n",
       "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
       "      return (VEGA_DEBUG[key] == version) ?\n",
       "        Promise.resolve(paths[lib]) :\n",
       "        new Promise(function(resolve, reject) {\n",
       "          var s = document.createElement('script');\n",
       "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "          s.async = true;\n",
       "          s.onload = () => {\n",
       "            VEGA_DEBUG[key] = version;\n",
       "            return resolve(paths[lib]);\n",
       "          };\n",
       "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
       "          s.src = paths[lib];\n",
       "        });\n",
       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else {\n",
       "      maybeLoadScript(\"vega\", \"5\")\n",
       "        .then(() => maybeLoadScript(\"vega-lite\", \"4.17.0\"))\n",
       "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-67c508535019cdcae2e95bc67cb64cf9\"}, \"mark\": {\"type\": \"circle\", \"color\": \"green\", \"size\": 150}, \"encoding\": {\"x\": {\"field\": \"year\", \"scale\": {\"domain\": [2000, 2019]}, \"type\": \"quantitative\"}, \"y\": {\"field\": \"count\", \"type\": \"quantitative\"}}, \"height\": 350, \"title\": \"Physics\", \"width\": 500, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.17.0.json\", \"datasets\": {\"data-67c508535019cdcae2e95bc67cb64cf9\": [{\"year\": 2021, \"count\": 4463}, {\"year\": 2020, \"count\": 3121}, {\"year\": 2019, \"count\": 1663}, {\"year\": 2018, \"count\": 775}, {\"year\": 2017, \"count\": 383}, {\"year\": 2016, \"count\": 219}, {\"year\": 2015, \"count\": 156}, {\"year\": 2014, \"count\": 94}, {\"year\": 2013, \"count\": 84}, {\"year\": 2012, \"count\": 59}, {\"year\": 2011, \"count\": 70}, {\"year\": 2010, \"count\": 47}, {\"year\": 2009, \"count\": 51}, {\"year\": 2008, \"count\": 43}, {\"year\": 2007, \"count\": 39}, {\"year\": 2006, \"count\": 33}, {\"year\": 2005, \"count\": 37}, {\"year\": 2004, \"count\": 16}, {\"year\": 2003, \"count\": 12}, {\"year\": 2002, \"count\": 15}, {\"year\": 2001, \"count\": 9}, {\"year\": 2000, \"count\": 12}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "charts[2]"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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   "cell_type": "code",
   "execution_count": null,
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   "cell_type": "code",
   "execution_count": null,
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