testing_cochlea_network.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import requests as r\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>10.0_Mean</th>\n",
       "      <th>10.0_SD</th>\n",
       "      <th>10.0_Avg_diff</th>\n",
       "      <th>10.0_Pval</th>\n",
       "      <th>10.1.0_Mean</th>\n",
       "      <th>10.1.0_SD</th>\n",
       "      <th>10.1.0_Avg_diff</th>\n",
       "      <th>10.1.0_Pval</th>\n",
       "      <th>10.1.1_Mean</th>\n",
       "      <th>...</th>\n",
       "      <th>22.3_Avg_diff</th>\n",
       "      <th>22.3_Pval</th>\n",
       "      <th>24.0_Mean</th>\n",
       "      <th>24.0_SD</th>\n",
       "      <th>24.0_Avg_diff</th>\n",
       "      <th>24.0_Pval</th>\n",
       "      <th>24.1_Mean</th>\n",
       "      <th>24.1_SD</th>\n",
       "      <th>24.1_Avg_diff</th>\n",
       "      <th>24.1_Pval</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apoe</td>\n",
       "      <td>-0.454713</td>\n",
       "      <td>0.449679</td>\n",
       "      <td>-0.891624</td>\n",
       "      <td>2.595464e-35</td>\n",
       "      <td>0.271620</td>\n",
       "      <td>0.903053</td>\n",
       "      <td>0.573273</td>\n",
       "      <td>5.168455e-10</td>\n",
       "      <td>-0.339086</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.39749</td>\n",
       "      <td>7.824495e-12</td>\n",
       "      <td>-0.312228</td>\n",
       "      <td>0.468616</td>\n",
       "      <td>-0.731901</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>-0.137722</td>\n",
       "      <td>0.570408</td>\n",
       "      <td>-0.419621</td>\n",
       "      <td>0.000013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bmp4</td>\n",
       "      <td>-0.358305</td>\n",
       "      <td>0.295937</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.982299</td>\n",
       "      <td>1.615688</td>\n",
       "      <td>2.097418</td>\n",
       "      <td>3.029520e-97</td>\n",
       "      <td>1.373414</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.159035</td>\n",
       "      <td>0.693488</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.168210</td>\n",
       "      <td>0.697095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Npnt</td>\n",
       "      <td>-0.100410</td>\n",
       "      <td>0.644706</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.524796</td>\n",
       "      <td>2.447777</td>\n",
       "      <td>0.781121</td>\n",
       "      <td>4.317224e-17</td>\n",
       "      <td>0.138519</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.061202</td>\n",
       "      <td>0.420073</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.006049</td>\n",
       "      <td>0.649601</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lmo3</td>\n",
       "      <td>-0.103131</td>\n",
       "      <td>0.334746</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.723087</td>\n",
       "      <td>4.423924</td>\n",
       "      <td>1.310493</td>\n",
       "      <td>1.149371e-57</td>\n",
       "      <td>1.298182</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.091927</td>\n",
       "      <td>1.295068</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.094702</td>\n",
       "      <td>0.027537</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hs3st1</td>\n",
       "      <td>-0.185846</td>\n",
       "      <td>0.414893</td>\n",
       "      <td>-0.826899</td>\n",
       "      <td>5.349538e-46</td>\n",
       "      <td>3.594417</td>\n",
       "      <td>1.862352</td>\n",
       "      <td>1.401558</td>\n",
       "      <td>8.687586e-65</td>\n",
       "      <td>2.588052</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.081855</td>\n",
       "      <td>0.626980</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.070822</td>\n",
       "      <td>0.537126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Gata2</td>\n",
       "      <td>-0.140274</td>\n",
       "      <td>0.627782</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.035117</td>\n",
       "      <td>2.805363</td>\n",
       "      <td>1.373971</td>\n",
       "      <td>9.390760e-56</td>\n",
       "      <td>1.957764</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.075350</td>\n",
       "      <td>0.783816</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.125897</td>\n",
       "      <td>1.223989</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Mest</td>\n",
       "      <td>-1.007405</td>\n",
       "      <td>0.603536</td>\n",
       "      <td>-0.367468</td>\n",
       "      <td>4.788085e-20</td>\n",
       "      <td>-0.490894</td>\n",
       "      <td>0.826415</td>\n",
       "      <td>0.411888</td>\n",
       "      <td>1.222823e-05</td>\n",
       "      <td>-0.879991</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.778942</td>\n",
       "      <td>0.698958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.828148</td>\n",
       "      <td>0.747791</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Krt18</td>\n",
       "      <td>0.474788</td>\n",
       "      <td>1.298400</td>\n",
       "      <td>-0.613109</td>\n",
       "      <td>1.670026e-27</td>\n",
       "      <td>1.139663</td>\n",
       "      <td>1.546185</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.085509</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.670491</td>\n",
       "      <td>1.146938</td>\n",
       "      <td>-0.530948</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.623360</td>\n",
       "      <td>1.282659</td>\n",
       "      <td>-0.485152</td>\n",
       "      <td>0.000573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Igfbp4</td>\n",
       "      <td>-0.958780</td>\n",
       "      <td>0.333678</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.293656</td>\n",
       "      <td>0.798151</td>\n",
       "      <td>0.772070</td>\n",
       "      <td>4.570655e-18</td>\n",
       "      <td>-0.629813</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.810867</td>\n",
       "      <td>0.494231</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.792913</td>\n",
       "      <td>0.443284</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Rnd2</td>\n",
       "      <td>0.079147</td>\n",
       "      <td>1.122124</td>\n",
       "      <td>-0.408460</td>\n",
       "      <td>3.507536e-21</td>\n",
       "      <td>2.563297</td>\n",
       "      <td>2.544600</td>\n",
       "      <td>0.776573</td>\n",
       "      <td>4.637550e-22</td>\n",
       "      <td>0.534591</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.020253</td>\n",
       "      <td>0.787430</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.101593</td>\n",
       "      <td>1.151177</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 77 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Unnamed: 0  10.0_Mean   10.0_SD  10.0_Avg_diff     10.0_Pval  10.1.0_Mean  \\\n",
       "0       Apoe  -0.454713  0.449679      -0.891624  2.595464e-35     0.271620   \n",
       "1       Bmp4  -0.358305  0.295937            NaN           NaN     3.982299   \n",
       "2       Npnt  -0.100410  0.644706            NaN           NaN     1.524796   \n",
       "3       Lmo3  -0.103131  0.334746            NaN           NaN     5.723087   \n",
       "4     Hs3st1  -0.185846  0.414893      -0.826899  5.349538e-46     3.594417   \n",
       "5      Gata2  -0.140274  0.627782            NaN           NaN     4.035117   \n",
       "6       Mest  -1.007405  0.603536      -0.367468  4.788085e-20    -0.490894   \n",
       "7      Krt18   0.474788  1.298400      -0.613109  1.670026e-27     1.139663   \n",
       "8     Igfbp4  -0.958780  0.333678            NaN           NaN    -0.293656   \n",
       "9       Rnd2   0.079147  1.122124      -0.408460  3.507536e-21     2.563297   \n",
       "\n",
       "   10.1.0_SD  10.1.0_Avg_diff   10.1.0_Pval  10.1.1_Mean  ...  22.3_Avg_diff  \\\n",
       "0   0.903053         0.573273  5.168455e-10    -0.339086  ...       -0.39749   \n",
       "1   1.615688         2.097418  3.029520e-97     1.373414  ...            NaN   \n",
       "2   2.447777         0.781121  4.317224e-17     0.138519  ...            NaN   \n",
       "3   4.423924         1.310493  1.149371e-57     1.298182  ...            NaN   \n",
       "4   1.862352         1.401558  8.687586e-65     2.588052  ...            NaN   \n",
       "5   2.805363         1.373971  9.390760e-56     1.957764  ...            NaN   \n",
       "6   0.826415         0.411888  1.222823e-05    -0.879991  ...            NaN   \n",
       "7   1.546185              NaN           NaN     2.085509  ...            NaN   \n",
       "8   0.798151         0.772070  4.570655e-18    -0.629813  ...            NaN   \n",
       "9   2.544600         0.776573  4.637550e-22     0.534591  ...            NaN   \n",
       "\n",
       "      22.3_Pval  24.0_Mean   24.0_SD  24.0_Avg_diff  24.0_Pval  24.1_Mean  \\\n",
       "0  7.824495e-12  -0.312228  0.468616      -0.731901   0.000001  -0.137722   \n",
       "1           NaN  -0.159035  0.693488            NaN        NaN  -0.168210   \n",
       "2           NaN  -0.061202  0.420073            NaN        NaN   0.006049   \n",
       "3           NaN   0.091927  1.295068            NaN        NaN  -0.094702   \n",
       "4           NaN  -0.081855  0.626980            NaN        NaN  -0.070822   \n",
       "5           NaN  -0.075350  0.783816            NaN        NaN   0.125897   \n",
       "6           NaN  -0.778942  0.698958            NaN        NaN  -0.828148   \n",
       "7           NaN   0.670491  1.146938      -0.530948   0.000001   0.623360   \n",
       "8           NaN  -0.810867  0.494231            NaN        NaN  -0.792913   \n",
       "9           NaN  -0.020253  0.787430            NaN        NaN   0.101593   \n",
       "\n",
       "    24.1_SD  24.1_Avg_diff  24.1_Pval  \n",
       "0  0.570408      -0.419621   0.000013  \n",
       "1  0.697095            NaN        NaN  \n",
       "2  0.649601            NaN        NaN  \n",
       "3  0.027537            NaN        NaN  \n",
       "4  0.537126            NaN        NaN  \n",
       "5  1.223989            NaN        NaN  \n",
       "6  0.747791            NaN        NaN  \n",
       "7  1.282659      -0.485152   0.000573  \n",
       "8  0.443284            NaN        NaN  \n",
       "9  1.151177            NaN        NaN  \n",
       "\n",
       "[10 rows x 77 columns]"
      ]
     },
     "execution_count": 300,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def load_data(filepath,sheet):\n",
    "    #df = pd.read_excel(open(filepath,'rb'),sheet_name=sheet)\n",
    "    df = pd.read_excel(filepath,sheet_name=sheet)\n",
    "    \n",
    "    return df\n",
    "\n",
    "df = load_data('published-data/development-of-the-mouse-and-human-cochlea-at-single-cell-resolution/media-2.xlsx',\n",
    "               'epi_data_matrix')\n",
    "\n",
    "# Rename the first column to something useful\n",
    "df.rename(columns={'Unnamed: 0':'Gene'},inplace=True)\n",
    "\n",
    "# Display the first 10 rows\n",
    "df.head(10) # or tail(10) will show the bottom 3   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', '10.0_Mean', '10.0_SD', '10.0_Avg_diff', '10.0_Pval',\n",
       "       '10.1.0_Mean', '10.1.0_SD', '10.1.0_Avg_diff', '10.1.0_Pval',\n",
       "       '10.1.1_Mean', '10.1.1_SD', '10.1.1_Avg_diff', '10.1.1_Pval',\n",
       "       '10.1.2_Mean', '10.1.2_SD', '10.1.2_Avg_diff', '10.1.2_Pval',\n",
       "       '10.1.3_Mean', '10.1.3_SD', '10.1.3_Avg_diff', '10.1.3_Pval',\n",
       "       '10.2.0_Mean', '10.2.0_SD', '10.2.0_Avg_diff', '10.2.0_Pval',\n",
       "       '10.2.1_Mean', '10.2.1_SD', '10.2.1_Avg_diff', '10.2.1_Pval',\n",
       "       '10.3.0_Mean', '10.3.0_SD', '10.3.0_Avg_diff', '10.3.0_Pval',\n",
       "       '10.3.1_Mean', '10.3.1_SD', '10.3.1_Avg_diff', '10.3.1_Pval',\n",
       "       '10.3.2_Mean', '10.3.2_SD', '10.3.2_Avg_diff', '10.3.2_Pval',\n",
       "       '10.4_Mean', '10.4_SD', '10.4_Avg_diff', '10.4_Pval', '10.5_Mean',\n",
       "       '10.5_SD', '10.5_Avg_diff', '10.5_Pval', '22.0_Mean', '22.0_SD',\n",
       "       '22.0_Avg_diff', '22.0_Pval', '22.1_Mean', '22.1_SD', '22.1_Avg_diff',\n",
       "       '22.1_Pval', '22.2.0_Mean', '22.2.0_SD', '22.2.0_Avg_diff',\n",
       "       '22.2.0_Pval', '22.2.1_Mean', '22.2.1_SD', '22.2.1_Avg_diff',\n",
       "       '22.2.1_Pval', '22.3_Mean', '22.3_SD', '22.3_Avg_diff', '22.3_Pval',\n",
       "       '24.0_Mean', '24.0_SD', '24.0_Avg_diff', '24.0_Pval', '24.1_Mean',\n",
       "       '24.1_SD', '24.1_Avg_diff', '24.1_Pval'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 301,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Isolate groups making up the cochlea floor\n",
    "# Use list comprehension to join suffix to groups\n",
    "suffix = '_Avg_diff'\n",
    "all_groups = ['10.1.1','10.1.2','10.1.3','10.2.0','10.2.1','10.3.0','10.3.1',\\\n",
    "             '10.3.2','10.4','10.5','22.0','22.1','22.2.0','22.2.1','22.3',\\\n",
    "             '24.0','24.1']\n",
    "early_groups = ['24.0','24.1','10.0','10.1.0','10.1.1','10.4','10.2.1','10.3.0']\n",
    "cycling_groups = ['10.0','24.0','24.1']\n",
    "\n",
    "all_diffs = [group + suffix for group in all_groups]\n",
    "early_diffs = [group + suffix for group in early_groups]\n",
    "cycling_diffs = [group + suffix for group in cycling_groups]\n",
    "\n",
    "# Rename the first column to something useful\n",
    "df.rename(columns={'Unnamed: 0':'Gene'},inplace=True)\n",
    "# From Figure 3, select the clusters in the floor corresponding to earliest timepoints\n",
    "\n",
    "# Get just the columns we're interested (average differential expression)\n",
    "cols = all_diffs\n",
    "cols.insert(0,'Gene')\n",
    "df_alldiffs = df[cols]\n",
    "\n",
    "cols = early_diffs\n",
    "cols.insert(0,'Gene')\n",
    "df_earlydiffs = df[cols]\n",
    "\n",
    "cols = cycling_diffs\n",
    "cols.insert(0,'Gene')\n",
    "df_cyclingdiffs = df[cols]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Gene',\n",
       " 'Gene',\n",
       " '10.1.1_Avg_diff',\n",
       " '10.1.2_Avg_diff',\n",
       " '10.1.3_Avg_diff',\n",
       " '10.2.0_Avg_diff',\n",
       " '10.2.1_Avg_diff',\n",
       " '10.3.0_Avg_diff',\n",
       " '10.3.1_Avg_diff',\n",
       " '10.3.2_Avg_diff',\n",
       " '10.4_Avg_diff',\n",
       " '10.5_Avg_diff',\n",
       " '22.0_Avg_diff',\n",
       " '22.1_Avg_diff',\n",
       " '22.2.0_Avg_diff',\n",
       " '22.2.1_Avg_diff',\n",
       " '22.3_Avg_diff',\n",
       " '24.0_Avg_diff',\n",
       " '24.1_Avg_diff']"
      ]
     },
     "execution_count": 304,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = ['Gene'] + all_diffs\n",
    "cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "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>Gene</th>\n",
       "      <th>10.0_Mean</th>\n",
       "      <th>10.0_SD</th>\n",
       "      <th>10.0_Avg_diff</th>\n",
       "      <th>10.0_Pval</th>\n",
       "      <th>10.1.0_Mean</th>\n",
       "      <th>10.1.0_SD</th>\n",
       "      <th>10.1.0_Avg_diff</th>\n",
       "      <th>10.1.0_Pval</th>\n",
       "      <th>10.1.1_Mean</th>\n",
       "      <th>...</th>\n",
       "      <th>22.3_Avg_diff</th>\n",
       "      <th>22.3_Pval</th>\n",
       "      <th>24.0_Mean</th>\n",
       "      <th>24.0_SD</th>\n",
       "      <th>24.0_Avg_diff</th>\n",
       "      <th>24.0_Pval</th>\n",
       "      <th>24.1_Mean</th>\n",
       "      <th>24.1_SD</th>\n",
       "      <th>24.1_Avg_diff</th>\n",
       "      <th>24.1_Pval</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Rtn1</td>\n",
       "      <td>0.779853</td>\n",
       "      <td>1.599731</td>\n",
       "      <td>-0.330532</td>\n",
       "      <td>1.046929e-12</td>\n",
       "      <td>3.382121</td>\n",
       "      <td>2.034614</td>\n",
       "      <td>1.053746</td>\n",
       "      <td>1.229286e-35</td>\n",
       "      <td>1.667089</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.738557</td>\n",
       "      <td>7.882425e-09</td>\n",
       "      <td>0.996735</td>\n",
       "      <td>1.744327</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.750157</td>\n",
       "      <td>1.434931</td>\n",
       "      <td>-0.312817</td>\n",
       "      <td>0.000357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Cpz</td>\n",
       "      <td>0.334683</td>\n",
       "      <td>1.364319</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.756940</td>\n",
       "      <td>2.215950</td>\n",
       "      <td>0.532780</td>\n",
       "      <td>6.073441e-11</td>\n",
       "      <td>1.078223</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.118854</td>\n",
       "      <td>0.796596</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.249826</td>\n",
       "      <td>1.107035</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>App</td>\n",
       "      <td>-0.120403</td>\n",
       "      <td>1.018377</td>\n",
       "      <td>-0.499723</td>\n",
       "      <td>1.002941e-37</td>\n",
       "      <td>1.143971</td>\n",
       "      <td>0.987538</td>\n",
       "      <td>0.659077</td>\n",
       "      <td>1.273815e-19</td>\n",
       "      <td>1.061755</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.023743</td>\n",
       "      <td>0.903855</td>\n",
       "      <td>-0.416079</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.303569</td>\n",
       "      <td>0.947741</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 77 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Gene  10.0_Mean   10.0_SD  10.0_Avg_diff     10.0_Pval  10.1.0_Mean  \\\n",
       "10  Rtn1   0.779853  1.599731      -0.330532  1.046929e-12     3.382121   \n",
       "20   Cpz   0.334683  1.364319            NaN           NaN     1.756940   \n",
       "30   App  -0.120403  1.018377      -0.499723  1.002941e-37     1.143971   \n",
       "\n",
       "    10.1.0_SD  10.1.0_Avg_diff   10.1.0_Pval  10.1.1_Mean  ...  22.3_Avg_diff  \\\n",
       "10   2.034614         1.053746  1.229286e-35     1.667089  ...      -0.738557   \n",
       "20   2.215950         0.532780  6.073441e-11     1.078223  ...            NaN   \n",
       "30   0.987538         0.659077  1.273815e-19     1.061755  ...            NaN   \n",
       "\n",
       "       22.3_Pval  24.0_Mean   24.0_SD  24.0_Avg_diff  24.0_Pval  24.1_Mean  \\\n",
       "10  7.882425e-09   0.996735  1.744327            NaN        NaN   0.750157   \n",
       "20           NaN   0.118854  0.796596            NaN        NaN   0.249826   \n",
       "30           NaN   0.023743  0.903855      -0.416079   0.000004   0.303569   \n",
       "\n",
       "     24.1_SD  24.1_Avg_diff  24.1_Pval  \n",
       "10  1.434931      -0.312817   0.000357  \n",
       "20  1.107035            NaN        NaN  \n",
       "30  0.947741            NaN        NaN  \n",
       "\n",
       "[3 rows x 77 columns]"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Access rows by their indices (0-based)\n",
    "df.iloc[[10,20,30]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.17216622965145"
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Access data by coordinates\n",
    "df.iloc[10,10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello\n"
     ]
    }
   ],
   "source": [
    "# Access the data row by row\n",
    "for idx, gene in df.iterrows():\n",
    "   print(idx,gene[early_groups])\n",
    "    \n",
    "print('hello')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       -0.731901\n",
       "7       -0.530948\n",
       "12       -0.27087\n",
       "15      -0.417623\n",
       "17      -0.634002\n",
       "           ...   \n",
       "27641    0.293224\n",
       "27651    0.262168\n",
       "27653    0.636619\n",
       "27852     0.36567\n",
       "27890   -0.291143\n",
       "Name: 24.0_Avg_diff, Length: 636, dtype: object"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find data based on textual information\n",
    "#df.loc[df['24.0_Avg_diff'] == 'Text I\\'m interested in']\n",
    "df2 = df[early_groups].fillna('missing')\n",
    "df3 = df2.loc[df2['24.0_Avg_diff'] != 'missing']\n",
    "df3['24.0_Avg_diff']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\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>Unnamed: 0</th>\n",
       "      <th>10.0_Mean</th>\n",
       "      <th>10.0_SD</th>\n",
       "      <th>10.0_Avg_diff</th>\n",
       "      <th>10.0_Pval</th>\n",
       "      <th>10.1.0_Mean</th>\n",
       "      <th>10.1.0_SD</th>\n",
       "      <th>10.1.0_Avg_diff</th>\n",
       "      <th>10.1.0_Pval</th>\n",
       "      <th>10.1.1_Mean</th>\n",
       "      <th>...</th>\n",
       "      <th>22.3_Pval</th>\n",
       "      <th>24.0_Mean</th>\n",
       "      <th>24.0_SD</th>\n",
       "      <th>24.0_Avg_diff</th>\n",
       "      <th>24.0_Pval</th>\n",
       "      <th>24.1_Mean</th>\n",
       "      <th>24.1_SD</th>\n",
       "      <th>24.1_Avg_diff</th>\n",
       "      <th>24.1_Pval</th>\n",
       "      <th>new column</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ccnd1</td>\n",
       "      <td>0.369192</td>\n",
       "      <td>1.321405</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.693116</td>\n",
       "      <td>1.363071</td>\n",
       "      <td>0.265211</td>\n",
       "      <td>1.706978e-02</td>\n",
       "      <td>1.252291</td>\n",
       "      <td>...</td>\n",
       "      <td>3.156399e-10</td>\n",
       "      <td>0.943219</td>\n",
       "      <td>1.354246</td>\n",
       "      <td>0.509836</td>\n",
       "      <td>4.503701e-06</td>\n",
       "      <td>1.548763</td>\n",
       "      <td>1.060747</td>\n",
       "      <td>0.807446</td>\n",
       "      <td>2.364306e-20</td>\n",
       "      <td>2.338468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ptp4a2</td>\n",
       "      <td>0.025979</td>\n",
       "      <td>1.087775</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.533614</td>\n",
       "      <td>1.266070</td>\n",
       "      <td>0.411101</td>\n",
       "      <td>2.933181e-08</td>\n",
       "      <td>0.338547</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.428795</td>\n",
       "      <td>1.157104</td>\n",
       "      <td>0.255234</td>\n",
       "      <td>1.284547e-02</td>\n",
       "      <td>0.084073</td>\n",
       "      <td>1.038042</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.210785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Akr1b3</td>\n",
       "      <td>-0.044302</td>\n",
       "      <td>1.032380</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.284036</td>\n",
       "      <td>1.186561</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.231145</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.356064</td>\n",
       "      <td>1.153120</td>\n",
       "      <td>0.261191</td>\n",
       "      <td>8.231169e-03</td>\n",
       "      <td>0.075269</td>\n",
       "      <td>1.023164</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.470597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mrpl51</td>\n",
       "      <td>0.002811</td>\n",
       "      <td>1.107426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.283433</td>\n",
       "      <td>0.938012</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.073600</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.424925</td>\n",
       "      <td>1.086524</td>\n",
       "      <td>0.346588</td>\n",
       "      <td>6.715937e-05</td>\n",
       "      <td>0.210272</td>\n",
       "      <td>1.111419</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.654578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Cbx3</td>\n",
       "      <td>0.048444</td>\n",
       "      <td>1.077367</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.038278</td>\n",
       "      <td>1.067017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.038545</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.436001</td>\n",
       "      <td>1.235148</td>\n",
       "      <td>0.489286</td>\n",
       "      <td>3.162485e-06</td>\n",
       "      <td>0.410696</td>\n",
       "      <td>1.195591</td>\n",
       "      <td>0.442889</td>\n",
       "      <td>8.690963e-05</td>\n",
       "      <td>1.028739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>Kif20b</td>\n",
       "      <td>-0.223696</td>\n",
       "      <td>0.530864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.153480</td>\n",
       "      <td>0.670156</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.241614</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.653342</td>\n",
       "      <td>2.065411</td>\n",
       "      <td>0.945851</td>\n",
       "      <td>5.917169e-42</td>\n",
       "      <td>0.334125</td>\n",
       "      <td>1.367477</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.516675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>Rpp30</td>\n",
       "      <td>-0.073529</td>\n",
       "      <td>0.976803</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.083442</td>\n",
       "      <td>1.115204</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.035083</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.415085</td>\n",
       "      <td>1.453267</td>\n",
       "      <td>0.293224</td>\n",
       "      <td>6.298890e-04</td>\n",
       "      <td>0.286694</td>\n",
       "      <td>1.313942</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.198646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408</th>\n",
       "      <td>2019-03-05 00:00:00</td>\n",
       "      <td>0.150185</td>\n",
       "      <td>1.178914</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.078095</td>\n",
       "      <td>1.097935</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.013348</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.561594</td>\n",
       "      <td>1.147275</td>\n",
       "      <td>0.262168</td>\n",
       "      <td>2.796793e-03</td>\n",
       "      <td>0.269163</td>\n",
       "      <td>1.128335</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.176031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>409</th>\n",
       "      <td>Kif11</td>\n",
       "      <td>-0.223416</td>\n",
       "      <td>0.220172</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.190114</td>\n",
       "      <td>0.441262</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.227029</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.188096</td>\n",
       "      <td>2.322292</td>\n",
       "      <td>0.636619</td>\n",
       "      <td>2.724313e-29</td>\n",
       "      <td>0.237476</td>\n",
       "      <td>1.323907</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.251147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>Acsl5</td>\n",
       "      <td>0.337262</td>\n",
       "      <td>1.583403</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.130103</td>\n",
       "      <td>0.667195</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.157150</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.201685</td>\n",
       "      <td>2.169808</td>\n",
       "      <td>0.365670</td>\n",
       "      <td>4.787458e-06</td>\n",
       "      <td>0.469143</td>\n",
       "      <td>1.590630</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.537092</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>411 rows × 78 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Unnamed: 0  10.0_Mean   10.0_SD  10.0_Avg_diff  10.0_Pval  \\\n",
       "0                  Ccnd1   0.369192  1.321405            NaN        NaN   \n",
       "1                 Ptp4a2   0.025979  1.087775            NaN        NaN   \n",
       "2                 Akr1b3  -0.044302  1.032380            NaN        NaN   \n",
       "3                 Mrpl51   0.002811  1.107426            NaN        NaN   \n",
       "4                   Cbx3   0.048444  1.077367            NaN        NaN   \n",
       "..                   ...        ...       ...            ...        ...   \n",
       "406               Kif20b  -0.223696  0.530864            NaN        NaN   \n",
       "407                Rpp30  -0.073529  0.976803            NaN        NaN   \n",
       "408  2019-03-05 00:00:00   0.150185  1.178914            NaN        NaN   \n",
       "409                Kif11  -0.223416  0.220172            NaN        NaN   \n",
       "410                Acsl5   0.337262  1.583403            NaN        NaN   \n",
       "\n",
       "     10.1.0_Mean  10.1.0_SD  10.1.0_Avg_diff   10.1.0_Pval  10.1.1_Mean  ...  \\\n",
       "0       0.693116   1.363071         0.265211  1.706978e-02     1.252291  ...   \n",
       "1       0.533614   1.266070         0.411101  2.933181e-08     0.338547  ...   \n",
       "2       0.284036   1.186561              NaN           NaN    -0.231145  ...   \n",
       "3      -0.283433   0.938012              NaN           NaN    -0.073600  ...   \n",
       "4      -0.038278   1.067017              NaN           NaN    -0.038545  ...   \n",
       "..           ...        ...              ...           ...          ...  ...   \n",
       "406    -0.153480   0.670156              NaN           NaN    -0.241614  ...   \n",
       "407     0.083442   1.115204              NaN           NaN     0.035083  ...   \n",
       "408     0.078095   1.097935              NaN           NaN    -0.013348  ...   \n",
       "409    -0.190114   0.441262              NaN           NaN    -0.227029  ...   \n",
       "410    -0.130103   0.667195              NaN           NaN    -0.157150  ...   \n",
       "\n",
       "        22.3_Pval  24.0_Mean   24.0_SD  24.0_Avg_diff     24.0_Pval  \\\n",
       "0    3.156399e-10   0.943219  1.354246       0.509836  4.503701e-06   \n",
       "1             NaN   0.428795  1.157104       0.255234  1.284547e-02   \n",
       "2             NaN   0.356064  1.153120       0.261191  8.231169e-03   \n",
       "3             NaN   0.424925  1.086524       0.346588  6.715937e-05   \n",
       "4             NaN   0.436001  1.235148       0.489286  3.162485e-06   \n",
       "..            ...        ...       ...            ...           ...   \n",
       "406           NaN   1.653342  2.065411       0.945851  5.917169e-42   \n",
       "407           NaN   0.415085  1.453267       0.293224  6.298890e-04   \n",
       "408           NaN   0.561594  1.147275       0.262168  2.796793e-03   \n",
       "409           NaN   1.188096  2.322292       0.636619  2.724313e-29   \n",
       "410           NaN   1.201685  2.169808       0.365670  4.787458e-06   \n",
       "\n",
       "     24.1_Mean   24.1_SD  24.1_Avg_diff     24.1_Pval  new column  \n",
       "0     1.548763  1.060747       0.807446  2.364306e-20    2.338468  \n",
       "1     0.084073  1.038042            NaN           NaN    2.210785  \n",
       "2     0.075269  1.023164            NaN           NaN    1.470597  \n",
       "3     0.210272  1.111419            NaN           NaN    0.654578  \n",
       "4     0.410696  1.195591       0.442889  8.690963e-05    1.028739  \n",
       "..         ...       ...            ...           ...         ...  \n",
       "406   0.334125  1.367477            NaN           NaN    0.516675  \n",
       "407   0.286694  1.313942            NaN           NaN    1.198646  \n",
       "408   0.269163  1.128335            NaN           NaN    1.176031  \n",
       "409   0.237476  1.323907            NaN           NaN    0.251147  \n",
       "410   0.469143  1.590630            NaN           NaN    0.537092  \n",
       "\n",
       "[411 rows x 78 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filtering\n",
    "#df.loc[(df['Field1'] == 'something') & (df['Field2'] == 'somethine_else')]\n",
    "new_df = df.loc[df['24.0_Avg_diff'] > 0]\n",
    "# But the index values for the filtered data are the same as the original.\n",
    "# Let's make a new dataframe that has reset indices\n",
    "new_df.reset_index(,inplace=True) # inplace so we don't have to make a new variable\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'24.0_Avg_diff'"
      ]
     },
     "execution_count": 274,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "early_diffs[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>index</th>\n",
       "      <th>Gene</th>\n",
       "      <th>24.0_Avg_diff</th>\n",
       "      <th>24.1_Avg_diff</th>\n",
       "      <th>10.0_Avg_diff</th>\n",
       "      <th>10.1.0_Avg_diff</th>\n",
       "      <th>10.1.1_Avg_diff</th>\n",
       "      <th>10.4_Avg_diff</th>\n",
       "      <th>10.2.1_Avg_diff</th>\n",
       "      <th>10.3.0_Avg_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Apoe</td>\n",
       "      <td>-0.731901</td>\n",
       "      <td>-0.419621</td>\n",
       "      <td>-0.891624</td>\n",
       "      <td>0.573273</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.458542</td>\n",
       "      <td>-0.764717</td>\n",
       "      <td>-0.746512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7</td>\n",
       "      <td>Krt18</td>\n",
       "      <td>-0.530948</td>\n",
       "      <td>-0.485152</td>\n",
       "      <td>-0.613109</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.499787</td>\n",
       "      <td>0.411182</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.755791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12</td>\n",
       "      <td>Tpbg</td>\n",
       "      <td>-0.270870</td>\n",
       "      <td>-0.337939</td>\n",
       "      <td>-0.264440</td>\n",
       "      <td>0.474989</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.440207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15</td>\n",
       "      <td>Mgst1</td>\n",
       "      <td>-0.417623</td>\n",
       "      <td>-0.491978</td>\n",
       "      <td>-0.285080</td>\n",
       "      <td>0.628995</td>\n",
       "      <td>0.500010</td>\n",
       "      <td>-0.392868</td>\n",
       "      <td>-0.263534</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17</td>\n",
       "      <td>Krt8</td>\n",
       "      <td>-0.634002</td>\n",
       "      <td>-0.855731</td>\n",
       "      <td>-0.853618</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.512157</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.674847</td>\n",
       "      <td>-0.525818</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>631</th>\n",
       "      <td>27641</td>\n",
       "      <td>Rpp30</td>\n",
       "      <td>0.293224</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",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>632</th>\n",
       "      <td>27651</td>\n",
       "      <td>2019-03-05 00:00:00</td>\n",
       "      <td>0.262168</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",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>633</th>\n",
       "      <td>27653</td>\n",
       "      <td>Kif11</td>\n",
       "      <td>0.636619</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",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>634</th>\n",
       "      <td>27852</td>\n",
       "      <td>Acsl5</td>\n",
       "      <td>0.365670</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",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>635</th>\n",
       "      <td>27890</td>\n",
       "      <td>Rps12-ps3</td>\n",
       "      <td>-0.291143</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",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>636 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index                 Gene  24.0_Avg_diff  24.1_Avg_diff  10.0_Avg_diff  \\\n",
       "0        0                 Apoe      -0.731901      -0.419621      -0.891624   \n",
       "1        7                Krt18      -0.530948      -0.485152      -0.613109   \n",
       "2       12                 Tpbg      -0.270870      -0.337939      -0.264440   \n",
       "3       15                Mgst1      -0.417623      -0.491978      -0.285080   \n",
       "4       17                 Krt8      -0.634002      -0.855731      -0.853618   \n",
       "..     ...                  ...            ...            ...            ...   \n",
       "631  27641                Rpp30       0.293224            NaN            NaN   \n",
       "632  27651  2019-03-05 00:00:00       0.262168            NaN            NaN   \n",
       "633  27653                Kif11       0.636619            NaN            NaN   \n",
       "634  27852                Acsl5       0.365670            NaN            NaN   \n",
       "635  27890            Rps12-ps3      -0.291143            NaN            NaN   \n",
       "\n",
       "     10.1.0_Avg_diff  10.1.1_Avg_diff  10.4_Avg_diff  10.2.1_Avg_diff  \\\n",
       "0           0.573273              NaN      -0.458542        -0.764717   \n",
       "1                NaN         0.499787       0.411182              NaN   \n",
       "2           0.474989              NaN            NaN              NaN   \n",
       "3           0.628995         0.500010      -0.392868        -0.263534   \n",
       "4                NaN         0.512157            NaN        -0.674847   \n",
       "..               ...              ...            ...              ...   \n",
       "631              NaN              NaN            NaN              NaN   \n",
       "632              NaN              NaN            NaN              NaN   \n",
       "633              NaN              NaN            NaN              NaN   \n",
       "634              NaN              NaN            NaN              NaN   \n",
       "635              NaN              NaN            NaN              NaN   \n",
       "\n",
       "     10.3.0_Avg_diff  \n",
       "0          -0.746512  \n",
       "1          -0.755791  \n",
       "2          -0.440207  \n",
       "3                NaN  \n",
       "4          -0.525818  \n",
       "..               ...  \n",
       "631              NaN  \n",
       "632              NaN  \n",
       "633              NaN  \n",
       "634              NaN  \n",
       "635              NaN  \n",
       "\n",
       "[636 rows x 10 columns]"
      ]
     },
     "execution_count": 275,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter null values for a specific group\n",
    "df_earlydiffs.loc[~df_earlydiffs[early_diffs[1]].isnull()].reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\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>index</th>\n",
       "      <th>Gene</th>\n",
       "      <th>24.0_Avg_diff</th>\n",
       "      <th>24.1_Avg_diff</th>\n",
       "      <th>10.0_Avg_diff</th>\n",
       "      <th>10.1.0_Avg_diff</th>\n",
       "      <th>10.1.1_Avg_diff</th>\n",
       "      <th>10.4_Avg_diff</th>\n",
       "      <th>10.2.1_Avg_diff</th>\n",
       "      <th>10.3.0_Avg_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Bmp4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.097418</td>\n",
       "      <td>0.597864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>Hs3st1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.826899</td>\n",
       "      <td>1.401558</td>\n",
       "      <td>0.989634</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.35871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>Gata2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.373971</td>\n",
       "      <td>0.538055</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Lmo3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.310493</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": [
       "   index    Gene  24.0_Avg_diff  24.1_Avg_diff  10.0_Avg_diff  \\\n",
       "0      1    Bmp4            NaN            NaN            NaN   \n",
       "1      4  Hs3st1            NaN            NaN      -0.826899   \n",
       "2      5   Gata2            NaN            NaN            NaN   \n",
       "3      3    Lmo3            NaN            NaN            NaN   \n",
       "\n",
       "   10.1.0_Avg_diff  10.1.1_Avg_diff  10.4_Avg_diff  10.2.1_Avg_diff  \\\n",
       "0         2.097418         0.597864            NaN              NaN   \n",
       "1         1.401558         0.989634            NaN              NaN   \n",
       "2         1.373971         0.538055            NaN              NaN   \n",
       "3         1.310493              NaN            NaN              NaN   \n",
       "\n",
       "   10.3.0_Avg_diff  \n",
       "0              NaN  \n",
       "1          0.35871  \n",
       "2              NaN  \n",
       "3              NaN  "
      ]
     },
     "execution_count": 276,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter and sort high expressing genes for a specific group\n",
    "df_earlydiffs.loc[df_earlydiffs[early_diffs[4]] > 1.3].\\\n",
    "sort_values(by=[early_diffs[4]],ascending=False)\\\n",
    ".reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gene</th>\n",
       "      <th>24.0_Avg_diff</th>\n",
       "      <th>24.1_Avg_diff</th>\n",
       "      <th>10.0_Avg_diff</th>\n",
       "      <th>10.1.0_Avg_diff</th>\n",
       "      <th>10.1.1_Avg_diff</th>\n",
       "      <th>10.4_Avg_diff</th>\n",
       "      <th>10.2.1_Avg_diff</th>\n",
       "      <th>10.3.0_Avg_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24734</th>\n",
       "      <td>Dll1</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Gene  24.0_Avg_diff  24.1_Avg_diff  10.0_Avg_diff  10.1.0_Avg_diff  \\\n",
       "24734  Dll1            NaN            NaN            NaN              NaN   \n",
       "\n",
       "       10.1.1_Avg_diff  10.4_Avg_diff  10.2.1_Avg_diff  10.3.0_Avg_diff  \n",
       "24734              NaN            NaN              NaN              NaN  "
      ]
     },
     "execution_count": 277,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find data for a specific gene\n",
    "df_earlydiffs.loc[df_earlydiffs['Gene'] == 'Dll1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [
    {
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       "      <td>NaN</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",
       "      <td>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20098</th>\n",
       "      <td>Fgf11</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",
       "      <td>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21787</th>\n",
       "      <td>Fgfr4</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",
       "      <td>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22255</th>\n",
       "      <td>Fgf10</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.535836</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.366954</td>\n",
       "      <td>0.473394</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24183</th>\n",
       "      <td>Fgf12</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",
       "      <td>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24676</th>\n",
       "      <td>Fgfr1op</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",
       "      <td>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26849</th>\n",
       "      <td>Fgf1</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",
       "      <td>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27647</th>\n",
       "      <td>Fgfbp3</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",
       "      <td>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27779</th>\n",
       "      <td>Fgf8</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",
       "      <td>NaN</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",
       "      <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": [
       "           Gene  10.1.1_Avg_diff  10.1.2_Avg_diff  10.1.3_Avg_diff  \\\n",
       "268       Fgfr2              NaN         0.251343              NaN   \n",
       "3906       Fgf7              NaN              NaN              NaN   \n",
       "5147      Fgf13              NaN              NaN              NaN   \n",
       "5443      Fgf16              NaN              NaN              NaN   \n",
       "6002     Fgf2os              NaN              NaN              NaN   \n",
       "6003       Fgf2              NaN              NaN              NaN   \n",
       "9179      Fgfr3              NaN              NaN              NaN   \n",
       "9289     Fgfbp1              NaN              NaN              NaN   \n",
       "9678       Fgf5              NaN              NaN              NaN   \n",
       "9814     Fgfrl1              NaN              NaN              NaN   \n",
       "11811      Fgf6              NaN              NaN              NaN   \n",
       "11812     Fgf23              NaN              NaN              NaN   \n",
       "12064  Fgfr1op2              NaN              NaN        -0.393303   \n",
       "13157     Fgf21              NaN              NaN              NaN   \n",
       "14522      Fgf3              NaN              NaN              NaN   \n",
       "14523      Fgf4              NaN              NaN              NaN   \n",
       "14525     Fgf15              NaN              NaN              NaN   \n",
       "15083     Fgf22              NaN              NaN              NaN   \n",
       "15942     Fgfr1              NaN              NaN              NaN   \n",
       "16025     Fgf20              NaN              NaN              NaN   \n",
       "17597      Fgf9              NaN              NaN              NaN   \n",
       "17753     Fgf17              NaN              NaN              NaN   \n",
       "17907     Fgf14              NaN              NaN              NaN   \n",
       "19573     Fgf18              NaN              NaN              NaN   \n",
       "20098     Fgf11              NaN              NaN              NaN   \n",
       "21787     Fgfr4              NaN              NaN              NaN   \n",
       "22255     Fgf10              NaN              NaN              NaN   \n",
       "24183     Fgf12              NaN              NaN              NaN   \n",
       "24676   Fgfr1op              NaN              NaN              NaN   \n",
       "26849      Fgf1              NaN              NaN              NaN   \n",
       "27647    Fgfbp3              NaN              NaN              NaN   \n",
       "27779      Fgf8              NaN              NaN              NaN   \n",
       "\n",
       "       10.2.0_Avg_diff  10.2.1_Avg_diff  10.3.0_Avg_diff  10.3.1_Avg_diff  \\\n",
       "268                NaN              NaN              NaN              NaN   \n",
       "3906               NaN              NaN              NaN              NaN   \n",
       "5147               NaN              NaN              NaN              NaN   \n",
       "5443               NaN              NaN              NaN              NaN   \n",
       "6002               NaN              NaN              NaN              NaN   \n",
       "6003               NaN              NaN              NaN              NaN   \n",
       "9179               NaN              NaN              NaN         1.210905   \n",
       "9289               NaN              NaN              NaN              NaN   \n",
       "9678               NaN              NaN              NaN              NaN   \n",
       "9814               NaN              NaN              NaN         0.350199   \n",
       "11811              NaN              NaN              NaN              NaN   \n",
       "11812              NaN              NaN              NaN              NaN   \n",
       "12064              NaN              NaN              NaN              NaN   \n",
       "13157              NaN              NaN              NaN              NaN   \n",
       "14522              NaN              NaN              NaN         0.479940   \n",
       "14523              NaN              NaN              NaN              NaN   \n",
       "14525              NaN              NaN              NaN              NaN   \n",
       "15083              NaN              NaN              NaN              NaN   \n",
       "15942         0.279341              NaN              NaN         0.422623   \n",
       "16025              NaN              NaN         0.691805              NaN   \n",
       "17597              NaN              NaN              NaN              NaN   \n",
       "17753              NaN              NaN              NaN              NaN   \n",
       "17907              NaN              NaN              NaN              NaN   \n",
       "19573              NaN              NaN              NaN              NaN   \n",
       "20098              NaN              NaN              NaN              NaN   \n",
       "21787              NaN              NaN              NaN              NaN   \n",
       "22255              NaN              NaN              NaN              NaN   \n",
       "24183              NaN              NaN              NaN              NaN   \n",
       "24676              NaN              NaN              NaN              NaN   \n",
       "26849              NaN              NaN              NaN              NaN   \n",
       "27647              NaN              NaN              NaN              NaN   \n",
       "27779              NaN              NaN              NaN              NaN   \n",
       "\n",
       "       10.3.2_Avg_diff  10.4_Avg_diff  10.5_Avg_diff  22.0_Avg_diff  \\\n",
       "268                NaN            NaN            NaN            NaN   \n",
       "3906               NaN            NaN            NaN            NaN   \n",
       "5147               NaN            NaN            NaN            NaN   \n",
       "5443               NaN            NaN            NaN            NaN   \n",
       "6002               NaN            NaN            NaN            NaN   \n",
       "6003               NaN            NaN            NaN            NaN   \n",
       "9179          1.361608            NaN            NaN            NaN   \n",
       "9289               NaN            NaN            NaN            NaN   \n",
       "9678               NaN            NaN            NaN            NaN   \n",
       "9814               NaN            NaN            NaN            NaN   \n",
       "11811              NaN            NaN            NaN            NaN   \n",
       "11812              NaN            NaN            NaN            NaN   \n",
       "12064              NaN            NaN            NaN            NaN   \n",
       "13157              NaN            NaN            NaN            NaN   \n",
       "14522         0.564508            NaN       1.235103            NaN   \n",
       "14523              NaN            NaN            NaN            NaN   \n",
       "14525              NaN            NaN            NaN            NaN   \n",
       "15083              NaN            NaN            NaN            NaN   \n",
       "15942              NaN            NaN            NaN       0.293705   \n",
       "16025              NaN            NaN       0.437560            NaN   \n",
       "17597              NaN            NaN            NaN            NaN   \n",
       "17753              NaN            NaN            NaN            NaN   \n",
       "17907              NaN            NaN            NaN            NaN   \n",
       "19573              NaN            NaN            NaN            NaN   \n",
       "20098              NaN            NaN            NaN            NaN   \n",
       "21787              NaN            NaN            NaN            NaN   \n",
       "22255              NaN            NaN       0.535836            NaN   \n",
       "24183              NaN            NaN            NaN            NaN   \n",
       "24676              NaN            NaN            NaN            NaN   \n",
       "26849              NaN            NaN            NaN            NaN   \n",
       "27647              NaN            NaN            NaN            NaN   \n",
       "27779              NaN            NaN            NaN            NaN   \n",
       "\n",
       "       22.1_Avg_diff  22.2.0_Avg_diff  22.2.1_Avg_diff  22.3_Avg_diff  \\\n",
       "268              NaN              NaN              NaN            NaN   \n",
       "3906             NaN              NaN              NaN            NaN   \n",
       "5147             NaN              NaN              NaN            NaN   \n",
       "5443             NaN              NaN              NaN            NaN   \n",
       "6002             NaN              NaN              NaN            NaN   \n",
       "6003             NaN              NaN              NaN            NaN   \n",
       "9179             NaN              NaN              NaN            NaN   \n",
       "9289             NaN              NaN              NaN            NaN   \n",
       "9678             NaN              NaN              NaN            NaN   \n",
       "9814             NaN              NaN         0.343652            NaN   \n",
       "11811            NaN              NaN              NaN            NaN   \n",
       "11812            NaN              NaN              NaN            NaN   \n",
       "12064            NaN              NaN              NaN            NaN   \n",
       "13157            NaN              NaN              NaN            NaN   \n",
       "14522            NaN              NaN              NaN            NaN   \n",
       "14523            NaN              NaN              NaN            NaN   \n",
       "14525            NaN              NaN              NaN            NaN   \n",
       "15083            NaN              NaN              NaN            NaN   \n",
       "15942            NaN              NaN              NaN       0.277941   \n",
       "16025            NaN              NaN              NaN            NaN   \n",
       "17597            NaN              NaN              NaN            NaN   \n",
       "17753            NaN              NaN              NaN            NaN   \n",
       "17907            NaN              NaN              NaN            NaN   \n",
       "19573            NaN              NaN              NaN            NaN   \n",
       "20098            NaN              NaN              NaN            NaN   \n",
       "21787            NaN              NaN              NaN            NaN   \n",
       "22255            NaN         0.366954         0.473394            NaN   \n",
       "24183            NaN              NaN              NaN            NaN   \n",
       "24676            NaN              NaN              NaN            NaN   \n",
       "26849            NaN              NaN              NaN            NaN   \n",
       "27647            NaN              NaN              NaN            NaN   \n",
       "27779            NaN              NaN              NaN            NaN   \n",
       "\n",
       "       24.0_Avg_diff  24.1_Avg_diff  \n",
       "268              NaN            NaN  \n",
       "3906             NaN            NaN  \n",
       "5147             NaN            NaN  \n",
       "5443             NaN            NaN  \n",
       "6002             NaN            NaN  \n",
       "6003             NaN            NaN  \n",
       "9179             NaN            NaN  \n",
       "9289             NaN            NaN  \n",
       "9678             NaN            NaN  \n",
       "9814             NaN            NaN  \n",
       "11811            NaN            NaN  \n",
       "11812            NaN            NaN  \n",
       "12064            NaN            NaN  \n",
       "13157            NaN            NaN  \n",
       "14522            NaN            NaN  \n",
       "14523            NaN            NaN  \n",
       "14525            NaN            NaN  \n",
       "15083            NaN            NaN  \n",
       "15942            NaN            NaN  \n",
       "16025            NaN            NaN  \n",
       "17597            NaN            NaN  \n",
       "17753            NaN            NaN  \n",
       "17907            NaN            NaN  \n",
       "19573            NaN            NaN  \n",
       "20098            NaN            NaN  \n",
       "21787            NaN            NaN  \n",
       "22255            NaN            NaN  \n",
       "24183            NaN            NaN  \n",
       "24676            NaN            NaN  \n",
       "26849            NaN            NaN  \n",
       "27647            NaN            NaN  \n",
       "27779            NaN            NaN  "
      ]
     },
     "execution_count": 297,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find data for a gene family (e.g. all Bmps or all Wnts)\n",
    "df_alldiffs.loc[df_alldiffs['Gene'].str.contains('Fgf',na=False)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3800      True\n",
       "24734     True\n",
       "12724     True\n",
       "27997    False\n",
       "9324     False\n",
       "         ...  \n",
       "23933      NaN\n",
       "24087      NaN\n",
       "25141      NaN\n",
       "26937      NaN\n",
       "27651      NaN\n",
       "Name: Gene, Length: 27998, dtype: object"
      ]
     },
     "execution_count": 279,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_earlydiffs[early_diffs[0]].str.contains('Dll').sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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