Bar Chart Race.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Manim Community <span style=\"color: #008000; text-decoration-color: #008000\">v0.17.3</span>\n",
       "\n",
       "</pre>\n"
      ],
      "text/plain": [
       "Manim Community \u001b[32mv0.\u001b[0m\u001b[32m17.3\u001b[0m\n",
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from manim import *\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "config.media_width = \"75%\"\n",
    "config.verbosity = \"WARNING\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load The Dataset to Display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "file_name = Path('puppy_weights.csv')\n",
    "root_folder = Path('data')\n",
    "\n",
    "file_path = root_folder / file_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Emma</th>\n",
       "      <th>Simba</th>\n",
       "      <th>Ragnar</th>\n",
       "      <th>Luna</th>\n",
       "      <th>Rolo</th>\n",
       "      <th>Big Black</th>\n",
       "      <th>Jucumari</th>\n",
       "      <th>Tiny</th>\n",
       "      <th>Black1</th>\n",
       "      <th>Black2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-03-12</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-14</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.364</td>\n",
       "      <td>0.439</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.414</td>\n",
       "      <td>0.343</td>\n",
       "      <td>0.272</td>\n",
       "      <td>0.378</td>\n",
       "      <td>0.377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-16</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.477</td>\n",
       "      <td>0.545</td>\n",
       "      <td>0.383</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.519</td>\n",
       "      <td>0.410</td>\n",
       "      <td>0.350</td>\n",
       "      <td>0.499</td>\n",
       "      <td>0.496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-18</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.590</td>\n",
       "      <td>0.658</td>\n",
       "      <td>0.473</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.609</td>\n",
       "      <td>0.518</td>\n",
       "      <td>0.405</td>\n",
       "      <td>0.607</td>\n",
       "      <td>0.606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-19</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.666</td>\n",
       "      <td>0.718</td>\n",
       "      <td>0.504</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.668</td>\n",
       "      <td>0.562</td>\n",
       "      <td>0.460</td>\n",
       "      <td>0.704</td>\n",
       "      <td>0.698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-20</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.714</td>\n",
       "      <td>0.754</td>\n",
       "      <td>0.560</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.704</td>\n",
       "      <td>0.615</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.746</td>\n",
       "      <td>0.720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-21</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.775</td>\n",
       "      <td>0.825</td>\n",
       "      <td>0.637</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.784</td>\n",
       "      <td>0.663</td>\n",
       "      <td>0.543</td>\n",
       "      <td>0.812</td>\n",
       "      <td>0.794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-22</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.834</td>\n",
       "      <td>0.920</td>\n",
       "      <td>0.703</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.844</td>\n",
       "      <td>0.748</td>\n",
       "      <td>0.594</td>\n",
       "      <td>0.935</td>\n",
       "      <td>0.874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-23</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.912</td>\n",
       "      <td>0.964</td>\n",
       "      <td>0.725</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.926</td>\n",
       "      <td>0.794</td>\n",
       "      <td>0.640</td>\n",
       "      <td>0.992</td>\n",
       "      <td>0.926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-24</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.981</td>\n",
       "      <td>1.056</td>\n",
       "      <td>0.779</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.027</td>\n",
       "      <td>0.894</td>\n",
       "      <td>0.668</td>\n",
       "      <td>1.119</td>\n",
       "      <td>0.948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-25</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1.111</td>\n",
       "      <td>1.101</td>\n",
       "      <td>0.838</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.121</td>\n",
       "      <td>0.911</td>\n",
       "      <td>0.745</td>\n",
       "      <td>1.198</td>\n",
       "      <td>1.073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-26</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1.175</td>\n",
       "      <td>1.171</td>\n",
       "      <td>0.882</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.194</td>\n",
       "      <td>0.985</td>\n",
       "      <td>0.790</td>\n",
       "      <td>1.257</td>\n",
       "      <td>1.168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-27</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1.260</td>\n",
       "      <td>1.240</td>\n",
       "      <td>0.955</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.257</td>\n",
       "      <td>1.080</td>\n",
       "      <td>0.860</td>\n",
       "      <td>1.344</td>\n",
       "      <td>1.256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-28</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1.316</td>\n",
       "      <td>1.330</td>\n",
       "      <td>1.043</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.344</td>\n",
       "      <td>1.174</td>\n",
       "      <td>0.876</td>\n",
       "      <td>1.400</td>\n",
       "      <td>1.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-29</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1.371</td>\n",
       "      <td>1.368</td>\n",
       "      <td>1.090</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.413</td>\n",
       "      <td>1.250</td>\n",
       "      <td>0.972</td>\n",
       "      <td>1.512</td>\n",
       "      <td>1.400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-30</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1.468</td>\n",
       "      <td>1.462</td>\n",
       "      <td>1.180</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.507</td>\n",
       "      <td>1.298</td>\n",
       "      <td>1.033</td>\n",
       "      <td>1.580</td>\n",
       "      <td>1.469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-31</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1.560</td>\n",
       "      <td>1.510</td>\n",
       "      <td>1.226</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.600</td>\n",
       "      <td>1.335</td>\n",
       "      <td>1.095</td>\n",
       "      <td>1.680</td>\n",
       "      <td>1.566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-04-01</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1.663</td>\n",
       "      <td>1.562</td>\n",
       "      <td>1.278</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.680</td>\n",
       "      <td>1.401</td>\n",
       "      <td>1.132</td>\n",
       "      <td>1.749</td>\n",
       "      <td>1.591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-04-02</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1.723</td>\n",
       "      <td>1.651</td>\n",
       "      <td>1.360</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.745</td>\n",
       "      <td>1.490</td>\n",
       "      <td>1.144</td>\n",
       "      <td>1.818</td>\n",
       "      <td>1.667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-04-03</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1.844</td>\n",
       "      <td>1.696</td>\n",
       "      <td>1.502</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.817</td>\n",
       "      <td>1.542</td>\n",
       "      <td>1.239</td>\n",
       "      <td>1.895</td>\n",
       "      <td>1.708</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Emma  Simba  Ragnar   Luna  Rolo  Big Black  Jucumari   Tiny  \\\n",
       "Date                                                                       \n",
       "2019-03-12  28.0  0.000   0.000  0.000   0.0      0.000     0.000  0.000   \n",
       "2019-03-14  28.0  0.364   0.439  0.310   0.0      0.414     0.343  0.272   \n",
       "2019-03-16  28.0  0.477   0.545  0.383   0.0      0.519     0.410  0.350   \n",
       "2019-03-18  28.0  0.590   0.658  0.473   0.0      0.609     0.518  0.405   \n",
       "2019-03-19  28.0  0.666   0.718  0.504   0.0      0.668     0.562  0.460   \n",
       "2019-03-20  28.0  0.714   0.754  0.560   0.0      0.704     0.615  0.500   \n",
       "2019-03-21  28.0  0.775   0.825  0.637   0.0      0.784     0.663  0.543   \n",
       "2019-03-22  28.0  0.834   0.920  0.703   0.0      0.844     0.748  0.594   \n",
       "2019-03-23  28.0  0.912   0.964  0.725   0.0      0.926     0.794  0.640   \n",
       "2019-03-24  28.0  0.981   1.056  0.779   0.0      1.027     0.894  0.668   \n",
       "2019-03-25  28.0  1.111   1.101  0.838   0.0      1.121     0.911  0.745   \n",
       "2019-03-26  28.0  1.175   1.171  0.882   0.0      1.194     0.985  0.790   \n",
       "2019-03-27  28.0  1.260   1.240  0.955   0.0      1.257     1.080  0.860   \n",
       "2019-03-28  28.0  1.316   1.330  1.043   0.0      1.344     1.174  0.876   \n",
       "2019-03-29  28.0  1.371   1.368  1.090   0.0      1.413     1.250  0.972   \n",
       "2019-03-30  28.0  1.468   1.462  1.180   0.0      1.507     1.298  1.033   \n",
       "2019-03-31  28.0  1.560   1.510  1.226   0.0      1.600     1.335  1.095   \n",
       "2019-04-01  28.0  1.663   1.562  1.278   0.0      1.680     1.401  1.132   \n",
       "2019-04-02  28.0  1.723   1.651  1.360   0.0      1.745     1.490  1.144   \n",
       "2019-04-03  28.0  1.844   1.696  1.502   0.0      1.817     1.542  1.239   \n",
       "\n",
       "            Black1  Black2  \n",
       "Date                        \n",
       "2019-03-12   0.000   0.000  \n",
       "2019-03-14   0.378   0.377  \n",
       "2019-03-16   0.499   0.496  \n",
       "2019-03-18   0.607   0.606  \n",
       "2019-03-19   0.704   0.698  \n",
       "2019-03-20   0.746   0.720  \n",
       "2019-03-21   0.812   0.794  \n",
       "2019-03-22   0.935   0.874  \n",
       "2019-03-23   0.992   0.926  \n",
       "2019-03-24   1.119   0.948  \n",
       "2019-03-25   1.198   1.073  \n",
       "2019-03-26   1.257   1.168  \n",
       "2019-03-27   1.344   1.256  \n",
       "2019-03-28   1.400   1.340  \n",
       "2019-03-29   1.512   1.400  \n",
       "2019-03-30   1.580   1.469  \n",
       "2019-03-31   1.680   1.566  \n",
       "2019-04-01   1.749   1.591  \n",
       "2019-04-02   1.818   1.667  \n",
       "2019-04-03   1.895   1.708  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv_df = pd.read_csv(file_path).set_index('Date')\n",
    "\n",
    "csv_df /= 1000\n",
    "csv_df.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Emma         33.140\n",
       "Simba        36.700\n",
       "Ragnar       30.250\n",
       "Luna         33.980\n",
       "Rolo         36.050\n",
       "Big Black     3.938\n",
       "Jucumari      2.491\n",
       "Tiny          2.377\n",
       "Black1        3.154\n",
       "Black2        2.755\n",
       "dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv_df.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 [28.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n",
      "1 [28.0, 0.364, 0.439, 0.31, 0.0, 0.414, 0.343, 0.272, 0.378, 0.377]\n",
      "2 [28.0, 0.477, 0.545, 0.383, 0.0, 0.519, 0.41, 0.35, 0.499, 0.496]\n",
      "3 [28.0, 0.59, 0.658, 0.473, 0.0, 0.609, 0.518, 0.405, 0.607, 0.606]\n",
      "4 [28.0, 0.666, 0.718, 0.504, 0.0, 0.668, 0.562, 0.46, 0.704, 0.698]\n",
      "5 [28.0, 0.714, 0.754, 0.56, 0.0, 0.704, 0.615, 0.5, 0.746, 0.72]\n",
      "6 [28.0, 0.775, 0.825, 0.637, 0.0, 0.784, 0.663, 0.543, 0.812, 0.794]\n",
      "7 [28.0, 0.834, 0.92, 0.703, 0.0, 0.844, 0.748, 0.594, 0.935, 0.874]\n",
      "8 [28.0, 0.912, 0.964, 0.725, 0.0, 0.926, 0.794, 0.64, 0.992, 0.926]\n",
      "9 [28.0, 0.981, 1.056, 0.779, 0.0, 1.027, 0.894, 0.668, 1.119, 0.948]\n",
      "10 [28.0, 1.111, 1.101, 0.838, 0.0, 1.121, 0.911, 0.745, 1.198, 1.073]\n"
     ]
    }
   ],
   "source": [
    "for i, row in enumerate(csv_df.itertuples()):\n",
    "    if i > 10:\n",
    "        break\n",
    "    print(i, list(row[1:]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[28.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv_df.iloc[0].to_list()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fill-In Gaps in the Data\n",
    "If we take a look at the dataset, we can see that several of the dogs do not have any data past a certain date (they were adopted). I thought that a simple fix for this would be to simply extend the last value of those puppies for all the following rows.\n",
    "\n",
    "In cases where there are missing values in between datapoints, I will fill it with the average of the surrounding values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "csv_df.interpolate(axis=0,inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Images \n",
    "\n",
    "Exercise to test if we can open all the images properly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[PosixPath('images/Tiny.png'),\n",
       " PosixPath('images/Simba.png'),\n",
       " PosixPath('images/Rolo.png'),\n",
       " PosixPath('images/Ragnar.png'),\n",
       " PosixPath('images/Luna.png'),\n",
       " PosixPath('images/Jucumari.png'),\n",
       " PosixPath('images/Emma.png'),\n",
       " PosixPath('images/Black2.png'),\n",
       " PosixPath('images/Black1.png'),\n",
       " PosixPath('images/Big Black.png')]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#list files in directory\n",
    "\n",
    "all_paths = Path('images').glob('**/*')\n",
    "\n",
    "img_files = [f for f in all_paths if f.is_file()]\n",
    "img_files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tiny\n",
      "Simba\n",
      "Rolo\n",
      "Ragnar\n",
      "Luna\n",
      "Jucumari\n",
      "Emma\n",
      "Black2\n",
      "Black1\n",
      "Big Black\n"
     ]
    }
   ],
   "source": [
    "for file in img_files:\n",
    "    print(file.stem)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                           \r"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video src=\"media/jupyter/ImageFromFile@2023-09-11@22-15-10.mp4\" controls autoplay loop style=\"max-width: 75%;\"  >\n",
       "      Your browser does not support the <code>video</code> element.\n",
       "    </video>"
      ],
      "text/plain": [
       "<IPython.core.display.Video object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%manim -qm ImageFromFileTest\n",
    "\n",
    "\n",
    "class ImageFromFileTest(Scene):\n",
    "    def construct(self):\n",
    "\n",
    "        up_images   = Group() \n",
    "        down_images = Group()\n",
    "        images      = Group(up_images, down_images)\n",
    "\n",
    "        for i, file in enumerate(img_files):\n",
    "            img = ImageMobject(file)\n",
    "            img.scale(0.5)\n",
    "            # img.height = 7\n",
    "\n",
    "            if i < len(img_files) // 2:\n",
    "                up_images.add(img)\n",
    "            else:\n",
    "                down_images.add(img)\n",
    "            \n",
    "            \n",
    "        self.play(images.animate.arrange(UP))\n",
    "\n",
    "        self.play(\n",
    "            up_images.animate.arrange(LEFT + UP),\n",
    "            down_images.animate.arrange(LEFT + DOWN)\n",
    "        )\n",
    "\n",
    "        self.wait()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Animated Bar Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                                         \r"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video src=\"media/jupyter/StaticBarChart@2023-09-10@20-50-50.mp4\" controls autoplay loop style=\"max-width: 75%;\"  >\n",
       "      Your browser does not support the <code>video</code> element.\n",
       "    </video>"
      ],
      "text/plain": [
       "<IPython.core.display.Video object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%manim -ql AnimatedBarChart\n",
    "\n",
    "class AnimatedBarChart(Scene):\n",
    "    def construct(self):\n",
    "        self.camera.background_color = WHITE\n",
    "        bar_names = [\n",
    "            'Emma', 'Simba', 'Ragnar', 'Luna', 'Rolo', 'Big Black', \n",
    "            'Jucumari', 'Tiny', 'Black1', 'Black2'\n",
    "        ]\n",
    "        \n",
    "        chart = BarChart(\n",
    "            values = csv_df.iloc[0].to_list(),\n",
    "            bar_names=bar_names,\n",
    "            y_range=[0,40, 5],\n",
    "            y_length=6.5,\n",
    "            x_length=10, \n",
    "            x_axis_config={\n",
    "                \"font_size\":20,\n",
    "                'label_direction':DOWN + RIGHT,\n",
    "                # 'stroke_color' : RED,\n",
    "                # 'font_color' : BLACK,\n",
    "                # 'color':BLACK\n",
    "            },\n",
    "            axis_config = {\n",
    "                'color':BLACK,\n",
    "                # 'label_color':RED,\n",
    "                'tip_shape': StealthTip,\n",
    "            }\n",
    "        )\n",
    "\n",
    "        #==================================\n",
    "        # this section is to set the axis tick color. The best solution I found was the following for loops\n",
    "        # from this reddit post:\n",
    "        # https://www.reddit.com/r/manim/comments/x7iqzp/colors_of_axis_text_for_barchart/\n",
    "\n",
    "        for tick in chart.get_x_axis():\n",
    "            tick.set_color(BLACK)\n",
    "\n",
    "        for tick in chart.get_y_axis():\n",
    "            tick.set_color(BLACK)\n",
    "\n",
    "        #==================================\n",
    "        self.add(chart)\n",
    "        \n",
    "        for i, row in enumerate(csv_df.itertuples()):\n",
    "            weights = list(row[1:])  #first item is the date\n",
    "            if i == 0:\n",
    "                continue\n",
    "            # elif i > 25:  #comment out to render the full animation\n",
    "            #     break\n",
    "            self.play(chart.animate.change_bar_values(weights), rate_func=linear, run_time=0.1)\n",
    "            "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Animated Bar Chart With Images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                                                 \r"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video src=\"media/jupyter/AnimatedBarChartWithImages@2023-09-15@22-11-48.mp4\" controls autoplay loop style=\"max-width: 75%;\"  >\n",
       "      Your browser does not support the <code>video</code> element.\n",
       "    </video>"
      ],
      "text/plain": [
       "<IPython.core.display.Video object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%manim -qk AnimatedBarChartWithImages\n",
    "\n",
    "class AnimatedBarChartWithImages(Scene):\n",
    "    def construct(self):\n",
    "        self.camera.background_color = WHITE\n",
    "\n",
    "        bar_names = csv_df.columns\n",
    "        \n",
    "        chart = BarChart(\n",
    "            values = csv_df.iloc[0].to_list(),\n",
    "            bar_names=bar_names,\n",
    "            y_range=[0,40, 5],\n",
    "            y_length=6.5,\n",
    "            x_length=10, \n",
    "            x_axis_config={\n",
    "                \"font_size\":20,\n",
    "                'label_direction':DOWN,\n",
    "            },\n",
    "            axis_config = {\n",
    "                'color':BLACK,\n",
    "                'tip_shape': StealthTip,\n",
    "            }\n",
    "        )\n",
    "\n",
    "        #==================================\n",
    "        # Load images\n",
    "        img_dic = {}    #the following nested for-loop seems very inefficient, but I'm too tired to think\n",
    "        for puppy_name in bar_names:\n",
    "            for file in img_files:\n",
    "                if puppy_name == file.stem:\n",
    "                    img_dic[puppy_name] = file\n",
    "                    break\n",
    "\n",
    "        # images = Group()\n",
    "        images = []\n",
    "\n",
    "        dic_image_mobjects = {}\n",
    "        for puppy_name, bar in zip(bar_names, chart.bars):\n",
    "            img_path  = img_dic.get(puppy_name)\n",
    "            img       = ImageMobject(img_path)\n",
    "            img.width = chart.bars[0].width\n",
    "            img.next_to(bar, UP)\n",
    "\n",
    "            # images.add(img) \n",
    "            images.append(img)\n",
    "\n",
    "            dic_image_mobjects[puppy_name] = img\n",
    "\n",
    "        # images.add(*_images)\n",
    "\n",
    "        #==================================\n",
    "        # this section is to set the axis tick color. The best solution I found was the following for loops\n",
    "        # from this reddit post:\n",
    "        # https://www.reddit.com/r/manim/comments/x7iqzp/colors_of_axis_text_for_barchart/\n",
    "\n",
    "        for tick in chart.get_x_axis():\n",
    "            tick.set_color(BLACK)\n",
    "\n",
    "        for tick in chart.get_y_axis():\n",
    "            tick.set_color(BLACK)\n",
    "\n",
    "        #==================================\n",
    "        # determine labels for the chart\n",
    "        labels = chart.get_axis_labels(\n",
    "            Tex(\"dogs\", color=BLACK).scale(0.7), Tex(\"weight (kg)\", color=BLACK).scale(0.8)\n",
    "        )\n",
    "        #==================================\n",
    "        self.add(chart, labels)\n",
    "        self.add(*[img.next_to(bar, UP) for img, bar in zip(images, chart.bars)])\n",
    "\n",
    "        date_text = Tex(csv_df.index[0], color=BLUE_E)\n",
    "        date_text.move_to(UP*2 + RIGHT*3)\n",
    "        self.play(Create(date_text))\n",
    "        \n",
    "        for i, row in enumerate(csv_df.itertuples()):\n",
    "            date_str = row[0]\n",
    "            new_date = Tex(date_str, color=BLUE_E)\n",
    "            weights  = list(row[1:])  #first item is the date\n",
    "            \n",
    "            if i == 0:\n",
    "                continue\n",
    "\n",
    "            # elif i > 100:  #comment out to render the full animation\n",
    "            #     break\n",
    "\n",
    "            # elif i > 50:   #four puppies' data stops growing by this point. We could resize the chart to focus only on the remaining ones\n",
    "            #     pass\n",
    "\n",
    "            self.play(\n",
    "                chart.animate.change_bar_values(weights), \n",
    "                *[img.animate.next_to(bar, UP) for img, bar in zip(images, chart.bars)],\n",
    "                date_text.animate.become(new_date, match_center=True, match_height=True,),\n",
    "                rate_func=linear, \n",
    "                run_time=0.2,\n",
    "            )\n",
    "            "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Zoomed-In Animated Bar Chart Race (Work-In-Progress)\n",
    "\n",
    "This scene will be similar to the previous one, except that it will either zoom-in on the bars on the left, or resize the chart to only show the ones that are still moving.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                                              \r"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video src=\"media/jupyter/ZoomedAnimatedBarChartWithImages@2023-09-15@20-01-33.mp4\" controls autoplay loop style=\"max-width: 75%;\"  >\n",
       "      Your browser does not support the <code>video</code> element.\n",
       "    </video>"
      ],
      "text/plain": [
       "<IPython.core.display.Video object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%manim -ql ZoomedAnimatedBarChartWithImages\n",
    "\n",
    "class ZoomedAnimatedBarChartWithImages(MovingCameraScene):\n",
    "    def construct(self):\n",
    "        self.camera.background_color = WHITE\n",
    "\n",
    "        bar_names = csv_df.columns\n",
    "        \n",
    "        chart = BarChart(\n",
    "            values = csv_df.iloc[0].to_list(),\n",
    "            bar_names=bar_names,\n",
    "            y_range=[0,40, 5],\n",
    "            y_length=6.5,\n",
    "            x_length=10, \n",
    "            x_axis_config={\n",
    "                \"font_size\":20,\n",
    "                'label_direction':DOWN,\n",
    "            },\n",
    "            axis_config = {\n",
    "                'color':BLACK,\n",
    "                'tip_shape': StealthTip,\n",
    "            }\n",
    "        )\n",
    "\n",
    "        #==================================\n",
    "        # Load images\n",
    "        img_dic = {}    #the following nested for-loop seems very inefficient, but I'm too tired to think\n",
    "        for puppy_name in bar_names:\n",
    "            for file in img_files:\n",
    "                if puppy_name == file.stem:\n",
    "                    img_dic[puppy_name] = file\n",
    "                    break\n",
    "\n",
    "        # images = Group()\n",
    "        images = []\n",
    "\n",
    "        dic_image_mobjects = {}\n",
    "        for puppy_name, bar in zip(bar_names, chart.bars):\n",
    "            img_path  = img_dic.get(puppy_name)\n",
    "            img       = ImageMobject(img_path)\n",
    "            img.width = chart.bars[0].width\n",
    "            img.next_to(bar, UP)\n",
    "\n",
    "            # images.add(img) \n",
    "            images.append(img)\n",
    "\n",
    "            dic_image_mobjects[puppy_name] = img\n",
    "\n",
    "        # images.add(*_images)\n",
    "\n",
    "        #==================================\n",
    "        # this section is to set the axis tick color. The best solution I found was the following for loops\n",
    "        # from this reddit post:\n",
    "        # https://www.reddit.com/r/manim/comments/x7iqzp/colors_of_axis_text_for_barchart/\n",
    "\n",
    "        for tick in chart.get_x_axis():\n",
    "            tick.set_color(BLACK)\n",
    "\n",
    "        for tick in chart.get_y_axis():\n",
    "            tick.set_color(BLACK)\n",
    "\n",
    "        #==================================\n",
    "        # determine labels for the chart\n",
    "        labels = chart.get_axis_labels(\n",
    "            Tex(\"dogs\", color=BLACK).scale(0.7), Tex(\"weights (kg)\", color=BLACK).scale(0.8)\n",
    "        )\n",
    "\n",
    "\n",
    "        #==================================\n",
    "        # group main bars and axis into a group to zoom to later\n",
    "        zoomed_group = VGroup(chart.bars[:5])  #, chart.get_axes()[1])\n",
    "        # _zoomed_bars = ['Emma', 'Simba', 'Ragnar', 'Luna', 'Rolo',]\n",
    "        # _zoomed_images = images[:len(_zoomed_bars)]\n",
    "\n",
    "        # for name in _zoomed_bars:\n",
    "            \n",
    "\n",
    "        #==================================\n",
    "        #       ANIMATION STARTS HERE\n",
    "        #==================================\n",
    "        self.add(chart, labels)\n",
    "        self.add(*[img.next_to(bar, UP) for img, bar in zip(images, chart.bars)])\n",
    "\n",
    "        date_text = Tex(csv_df.index[0], color=BLUE_E)\n",
    "        date_text.move_to(UP*2 + RIGHT*3)\n",
    "        self.play(Create(date_text))\n",
    "        \n",
    "        for i, row in enumerate(csv_df.itertuples()):\n",
    "            date_str = row[0]\n",
    "            new_date = Tex(date_str, color=BLUE_E)\n",
    "            weights  = list(row[1:])  #first item is the date\n",
    "            \n",
    "            if i == 0:\n",
    "                continue\n",
    "\n",
    "            elif i > 20:  #comment out to render the full animation\n",
    "                break\n",
    "\n",
    "            elif i == 10:   #four puppies' data stop growing by this point. We could resize the chart to focus only on the remaining ones\n",
    "                self.play(\n",
    "                    self.camera.frame.animate.move_to(zoomed_group).set(width=zoomed_group.width*2),\n",
    "                    # self.camera.frame.animate.move_to(zoomed_group).set(width=zoomed_group.height*1.2),\n",
    "                    date_text.animate.move_to(self.camera.frame_center + UR*2),\n",
    "                )\n",
    "                self.play(\n",
    "                    chart.animate.change_bar_values(weights), \n",
    "                    *[img.animate.next_to(bar, UP) for img, bar in zip(images, chart.bars)],\n",
    "                    date_text.animate.become(new_date, match_center=True, match_height=True,),\n",
    "                    rate_func=linear, \n",
    "                    run_time=0.2,\n",
    "                )\n",
    "                \n",
    "            else:\n",
    "                self.play(\n",
    "                    chart.animate.change_bar_values(weights), \n",
    "                    *[img.animate.next_to(bar, UP) for img, bar in zip(images, chart.bars)],\n",
    "                    date_text.animate.become(new_date, match_center=True, match_height=True,),\n",
    "                    rate_func=linear, \n",
    "                    run_time=0.2,\n",
    "                )\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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