KMeans On Each dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import boto3, re, sys, math, json, os, sagemaker, urllib.request\n",
    "from sagemaker import get_execution_role\n",
    "import numpy as np                                \n",
    "import pandas as pd     \n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt                   \n",
    "from IPython.display import Image                 \n",
    "from IPython.display import display               \n",
    "from time import gmtime, strftime                 \n",
    "from sagemaker.predictor import csv_serializer   \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"RNA_matrix_breastCancerOnly.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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     "execution_count": 6,
     "metadata": {},
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   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop([\"file_id\", \"label\"], \"columns\", inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n",
       "    n_clusters=7, n_init=10, n_jobs=1, precompute_distances='auto',\n",
       "    random_state=None, tol=0.0001, verbose=0)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "k_means = KMeans(n_clusters=5)\n",
    "k_means.fit(df) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4], dtype=int32)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results = k_means.labels_\n",
    "np.unique(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"clusterGroup\"] = np.nan\n",
    "dataLength = len(df)\n",
    "for i in range(dataLength):\n",
    "    df.iloc[i, df.columns.get_loc(\"clusterGroup\")] = results[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>ENSG00000183169.6</th>\n",
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       "      <th></th>\n",
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       "      <td>0.145833</td>\n",
       "      <td>783.821181</td>\n",
       "      <td>0.097222</td>\n",
       "      <td>1.460069</td>\n",
       "      <td>2.406250</td>\n",
       "      <td>0.159722</td>\n",
       "      <td>0.039931</td>\n",
       "      <td>0.008681</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>380.815972</td>\n",
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       "      <td>30.225694</td>\n",
       "      <td>0.649306</td>\n",
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       "      <td>0.052083</td>\n",
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       "      <td>35.890625</td>\n",
       "      <td>6.215278</td>\n",
       "      <td>0.032986</td>\n",
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       "      <th>1.0</th>\n",
       "      <td>0.102426</td>\n",
       "      <td>874.142857</td>\n",
       "      <td>0.145553</td>\n",
       "      <td>2.328841</td>\n",
       "      <td>2.514825</td>\n",
       "      <td>0.180593</td>\n",
       "      <td>0.021563</td>\n",
       "      <td>0.002695</td>\n",
       "      <td>0.830189</td>\n",
       "      <td>414.560647</td>\n",
       "      <td>...</td>\n",
       "      <td>35.331536</td>\n",
       "      <td>0.695418</td>\n",
       "      <td>1902.959569</td>\n",
       "      <td>0.172507</td>\n",
       "      <td>0.037736</td>\n",
       "      <td>0.221024</td>\n",
       "      <td>42.194070</td>\n",
       "      <td>7.229111</td>\n",
       "      <td>0.094340</td>\n",
       "      <td>0.010782</td>\n",
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       "      <th>2.0</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>790.571429</td>\n",
       "      <td>0.214286</td>\n",
       "      <td>2.285714</td>\n",
       "      <td>1.071429</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.571429</td>\n",
       "      <td>221.428571</td>\n",
       "      <td>...</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1268.071429</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>63.500000</td>\n",
       "      <td>7.571429</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>0.094203</td>\n",
       "      <td>985.043478</td>\n",
       "      <td>0.065217</td>\n",
       "      <td>1.731884</td>\n",
       "      <td>2.188406</td>\n",
       "      <td>0.239130</td>\n",
       "      <td>0.021739</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.724638</td>\n",
       "      <td>392.891304</td>\n",
       "      <td>...</td>\n",
       "      <td>36.434783</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1847.014493</td>\n",
       "      <td>0.217391</td>\n",
       "      <td>0.181159</td>\n",
       "      <td>0.217391</td>\n",
       "      <td>43.920290</td>\n",
       "      <td>8.181159</td>\n",
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       "      <td>0.007246</td>\n",
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       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>639.750000</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>4.250000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>28.750000</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>1078.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>22.500000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "<p>5 rows × 31919 columns</p>\n",
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      ],
      "text/plain": [
       "              ENSG00000183169.6  ENSG00000100290.2  ENSG00000226765.1  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    0.145833         783.821181           0.097222   \n",
       "1.0                    0.102426         874.142857           0.145553   \n",
       "2.0                    0.000000         790.571429           0.214286   \n",
       "3.0                    0.094203         985.043478           0.065217   \n",
       "4.0                    0.500000         639.750000           1.250000   \n",
       "\n",
       "              ENSG00000241204.1  ENSG00000212135.1  ENSG00000254800.2  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    1.460069           2.406250           0.159722   \n",
       "1.0                    2.328841           2.514825           0.180593   \n",
       "2.0                    2.285714           1.071429           0.142857   \n",
       "3.0                    1.731884           2.188406           0.239130   \n",
       "4.0                    4.250000         517.000000           1.500000   \n",
       "\n",
       "              ENSG00000258516.1  ENSG00000206614.1  ENSG00000265820.1  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    0.039931           0.008681           0.666667   \n",
       "1.0                    0.021563           0.002695           0.830189   \n",
       "2.0                    0.000000           0.000000           0.571429   \n",
       "3.0                    0.021739           0.000000           0.724638   \n",
       "4.0                    0.250000           0.500000          15.000000   \n",
       "\n",
       "              ENSG00000108947.4        ...          ENSG00000243547.1  \\\n",
       "clusterGroup                           ...                              \n",
       "0.0                  380.815972        ...                  30.225694   \n",
       "1.0                  414.560647        ...                  35.331536   \n",
       "2.0                  221.428571        ...                  16.000000   \n",
       "3.0                  392.891304        ...                  36.434783   \n",
       "4.0                  111.000000        ...                  28.750000   \n",
       "\n",
       "              ENSG00000253842.1  ENSG00000125741.4  ENSG00000251610.1  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    0.649306        1802.510417           0.329861   \n",
       "1.0                    0.695418        1902.959569           0.172507   \n",
       "2.0                    0.500000        1268.071429           0.285714   \n",
       "3.0                    0.500000        1847.014493           0.217391   \n",
       "4.0                    4.750000        1078.000000           0.000000   \n",
       "\n",
       "              ENSG00000253413.1  ENSG00000205333.5  ENSG00000259985.1  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    0.052083           0.164931          35.890625   \n",
       "1.0                    0.037736           0.221024          42.194070   \n",
       "2.0                    0.000000           0.071429          63.500000   \n",
       "3.0                    0.181159           0.217391          43.920290   \n",
       "4.0                    0.000000           1.000000          22.500000   \n",
       "\n",
       "              ENSG00000272735.1  ENSG00000238912.1  ENSG00000257787.1  \n",
       "clusterGroup                                                           \n",
       "0.0                    6.215278           0.032986           0.046875  \n",
       "1.0                    7.229111           0.094340           0.010782  \n",
       "2.0                    7.571429           0.000000           0.000000  \n",
       "3.0                    8.181159           0.007246           0.007246  \n",
       "4.0                   25.000000           0.000000           0.000000  \n",
       "\n",
       "[5 rows x 31919 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clusterData = df.groupby([\"clusterGroup\"]).mean()\n",
    "df_clusterData"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_clusterData[\"Count\"] = pd.Series(df.groupby([\"clusterGroup\"]).size())\n",
    "df_clusterData.insert(0, 'Count_', df_clusterData.Count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>clusterGroup</th>\n",
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       "      <th>0.0</th>\n",
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       "      <td>0.145833</td>\n",
       "      <td>783.821181</td>\n",
       "      <td>0.097222</td>\n",
       "      <td>1.460069</td>\n",
       "      <td>2.406250</td>\n",
       "      <td>0.159722</td>\n",
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       "      <td>0.008681</td>\n",
       "      <td>0.666667</td>\n",
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       "      <td>0.649306</td>\n",
       "      <td>1802.510417</td>\n",
       "      <td>0.329861</td>\n",
       "      <td>0.052083</td>\n",
       "      <td>0.164931</td>\n",
       "      <td>35.890625</td>\n",
       "      <td>6.215278</td>\n",
       "      <td>0.032986</td>\n",
       "      <td>0.046875</td>\n",
       "      <td>576</td>\n",
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       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>371</td>\n",
       "      <td>0.102426</td>\n",
       "      <td>874.142857</td>\n",
       "      <td>0.145553</td>\n",
       "      <td>2.328841</td>\n",
       "      <td>2.514825</td>\n",
       "      <td>0.180593</td>\n",
       "      <td>0.021563</td>\n",
       "      <td>0.002695</td>\n",
       "      <td>0.830189</td>\n",
       "      <td>...</td>\n",
       "      <td>0.695418</td>\n",
       "      <td>1902.959569</td>\n",
       "      <td>0.172507</td>\n",
       "      <td>0.037736</td>\n",
       "      <td>0.221024</td>\n",
       "      <td>42.194070</td>\n",
       "      <td>7.229111</td>\n",
       "      <td>0.094340</td>\n",
       "      <td>0.010782</td>\n",
       "      <td>371</td>\n",
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       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>14</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>790.571429</td>\n",
       "      <td>0.214286</td>\n",
       "      <td>2.285714</td>\n",
       "      <td>1.071429</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.571429</td>\n",
       "      <td>...</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1268.071429</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>63.500000</td>\n",
       "      <td>7.571429</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14</td>\n",
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       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>138</td>\n",
       "      <td>0.094203</td>\n",
       "      <td>985.043478</td>\n",
       "      <td>0.065217</td>\n",
       "      <td>1.731884</td>\n",
       "      <td>2.188406</td>\n",
       "      <td>0.239130</td>\n",
       "      <td>0.021739</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.724638</td>\n",
       "      <td>...</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1847.014493</td>\n",
       "      <td>0.217391</td>\n",
       "      <td>0.181159</td>\n",
       "      <td>0.217391</td>\n",
       "      <td>43.920290</td>\n",
       "      <td>8.181159</td>\n",
       "      <td>0.007246</td>\n",
       "      <td>0.007246</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>4</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>639.750000</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>4.250000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>1078.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>22.500000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31921 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Count_  ENSG00000183169.6  ENSG00000100290.2  ENSG00000226765.1  \\\n",
       "clusterGroup                                                                    \n",
       "0.0              576           0.145833         783.821181           0.097222   \n",
       "1.0              371           0.102426         874.142857           0.145553   \n",
       "2.0               14           0.000000         790.571429           0.214286   \n",
       "3.0              138           0.094203         985.043478           0.065217   \n",
       "4.0                4           0.500000         639.750000           1.250000   \n",
       "\n",
       "              ENSG00000241204.1  ENSG00000212135.1  ENSG00000254800.2  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    1.460069           2.406250           0.159722   \n",
       "1.0                    2.328841           2.514825           0.180593   \n",
       "2.0                    2.285714           1.071429           0.142857   \n",
       "3.0                    1.731884           2.188406           0.239130   \n",
       "4.0                    4.250000         517.000000           1.500000   \n",
       "\n",
       "              ENSG00000258516.1  ENSG00000206614.1  ENSG00000265820.1  ...    \\\n",
       "clusterGroup                                                           ...     \n",
       "0.0                    0.039931           0.008681           0.666667  ...     \n",
       "1.0                    0.021563           0.002695           0.830189  ...     \n",
       "2.0                    0.000000           0.000000           0.571429  ...     \n",
       "3.0                    0.021739           0.000000           0.724638  ...     \n",
       "4.0                    0.250000           0.500000          15.000000  ...     \n",
       "\n",
       "              ENSG00000253842.1  ENSG00000125741.4  ENSG00000251610.1  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    0.649306        1802.510417           0.329861   \n",
       "1.0                    0.695418        1902.959569           0.172507   \n",
       "2.0                    0.500000        1268.071429           0.285714   \n",
       "3.0                    0.500000        1847.014493           0.217391   \n",
       "4.0                    4.750000        1078.000000           0.000000   \n",
       "\n",
       "              ENSG00000253413.1  ENSG00000205333.5  ENSG00000259985.1  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    0.052083           0.164931          35.890625   \n",
       "1.0                    0.037736           0.221024          42.194070   \n",
       "2.0                    0.000000           0.071429          63.500000   \n",
       "3.0                    0.181159           0.217391          43.920290   \n",
       "4.0                    0.000000           1.000000          22.500000   \n",
       "\n",
       "              ENSG00000272735.1  ENSG00000238912.1  ENSG00000257787.1  Count  \n",
       "clusterGroup                                                                  \n",
       "0.0                    6.215278           0.032986           0.046875    576  \n",
       "1.0                    7.229111           0.094340           0.010782    371  \n",
       "2.0                    7.571429           0.000000           0.000000     14  \n",
       "3.0                    8.181159           0.007246           0.007246    138  \n",
       "4.0                   25.000000           0.000000           0.000000      4  \n",
       "\n",
       "[5 rows x 31921 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clusterData"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n",
       "    n_clusters=5, n_init=10, n_jobs=1, precompute_distances='auto',\n",
       "    random_state=None, tol=0.0001, verbose=0)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ef = pd.read_csv(\"RNA_matrix_HealthyOnly.csv\")\n",
    "ef.drop([\"file_id\", \"label\"], \"columns\", inplace=True)\n",
    "k_means = KMeans(n_clusters=5)\n",
    "k_means.fit(ef) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 2 3 4]\n"
     ]
    }
   ],
   "source": [
    "resultsHealth = k_means.labels_\n",
    "print(np.unique(resultsHealth))\n",
    "ef[\"clusterGroup\"] = np.nan\n",
    "dataLength = len(ef)\n",
    "for i in range(dataLength):\n",
    "    ef.iloc[i, ef.columns.get_loc(\"clusterGroup\")] = resultsHealth[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Count_</th>\n",
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       "    <tr>\n",
       "      <th>clusterGroup</th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <td>11.298673</td>\n",
       "      <td>0.121681</td>\n",
       "      <td>0.044248</td>\n",
       "      <td>0.212389</td>\n",
       "      <td>0.011062</td>\n",
       "      <td>0.046460</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022124</td>\n",
       "      <td>...</td>\n",
       "      <td>0.466814</td>\n",
       "      <td>1214.238938</td>\n",
       "      <td>0.168142</td>\n",
       "      <td>0.004425</td>\n",
       "      <td>0.139381</td>\n",
       "      <td>26.163717</td>\n",
       "      <td>4.665929</td>\n",
       "      <td>0.004425</td>\n",
       "      <td>0.037611</td>\n",
       "      <td>452</td>\n",
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       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>73</td>\n",
       "      <td>0.342466</td>\n",
       "      <td>79.013699</td>\n",
       "      <td>0.068493</td>\n",
       "      <td>0.054795</td>\n",
       "      <td>0.547945</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.027397</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.041096</td>\n",
       "      <td>...</td>\n",
       "      <td>1.123288</td>\n",
       "      <td>2526.164384</td>\n",
       "      <td>0.027397</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.082192</td>\n",
       "      <td>152.438356</td>\n",
       "      <td>8.931507</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.041096</td>\n",
       "      <td>73</td>\n",
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       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>174</td>\n",
       "      <td>0.270115</td>\n",
       "      <td>36.385057</td>\n",
       "      <td>0.097701</td>\n",
       "      <td>0.040230</td>\n",
       "      <td>0.344828</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.057471</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.034483</td>\n",
       "      <td>...</td>\n",
       "      <td>0.844828</td>\n",
       "      <td>1738.839080</td>\n",
       "      <td>0.091954</td>\n",
       "      <td>0.005747</td>\n",
       "      <td>0.097701</td>\n",
       "      <td>70.574713</td>\n",
       "      <td>5.747126</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022989</td>\n",
       "      <td>174</td>\n",
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       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>30</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>102.800000</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.533333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>1941.500000</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>8.866667</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>30</td>\n",
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       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>470</td>\n",
       "      <td>0.304255</td>\n",
       "      <td>7.597872</td>\n",
       "      <td>0.053191</td>\n",
       "      <td>0.042553</td>\n",
       "      <td>0.227660</td>\n",
       "      <td>0.004255</td>\n",
       "      <td>0.031915</td>\n",
       "      <td>0.002128</td>\n",
       "      <td>0.029787</td>\n",
       "      <td>...</td>\n",
       "      <td>0.608511</td>\n",
       "      <td>890.659574</td>\n",
       "      <td>0.174468</td>\n",
       "      <td>0.012766</td>\n",
       "      <td>0.168085</td>\n",
       "      <td>12.985106</td>\n",
       "      <td>3.255319</td>\n",
       "      <td>0.002128</td>\n",
       "      <td>0.034043</td>\n",
       "      <td>470</td>\n",
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       "</table>\n",
       "<p>5 rows × 31921 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Count_  ENSG00000183169.6  ENSG00000100290.2  ENSG00000226765.1  \\\n",
       "clusterGroup                                                                    \n",
       "0.0              452           0.442478          11.298673           0.121681   \n",
       "1.0               73           0.342466          79.013699           0.068493   \n",
       "2.0              174           0.270115          36.385057           0.097701   \n",
       "3.0               30           0.300000         102.800000           0.033333   \n",
       "4.0              470           0.304255           7.597872           0.053191   \n",
       "\n",
       "              ENSG00000241204.1  ENSG00000212135.1  ENSG00000254800.2  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    0.044248           0.212389           0.011062   \n",
       "1.0                    0.054795           0.547945           0.000000   \n",
       "2.0                    0.040230           0.344828           0.000000   \n",
       "3.0                    0.033333           0.533333           0.000000   \n",
       "4.0                    0.042553           0.227660           0.004255   \n",
       "\n",
       "              ENSG00000258516.1  ENSG00000206614.1  ENSG00000265820.1  ...    \\\n",
       "clusterGroup                                                           ...     \n",
       "0.0                    0.046460           0.000000           0.022124  ...     \n",
       "1.0                    0.027397           0.000000           0.041096  ...     \n",
       "2.0                    0.057471           0.000000           0.034483  ...     \n",
       "3.0                    0.000000           0.000000           0.000000  ...     \n",
       "4.0                    0.031915           0.002128           0.029787  ...     \n",
       "\n",
       "              ENSG00000253842.1  ENSG00000125741.4  ENSG00000251610.1  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    0.466814        1214.238938           0.168142   \n",
       "1.0                    1.123288        2526.164384           0.027397   \n",
       "2.0                    0.844828        1738.839080           0.091954   \n",
       "3.0                    0.966667        1941.500000           0.033333   \n",
       "4.0                    0.608511         890.659574           0.174468   \n",
       "\n",
       "              ENSG00000253413.1  ENSG00000205333.5  ENSG00000259985.1  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    0.004425           0.139381          26.163717   \n",
       "1.0                    0.000000           0.082192         152.438356   \n",
       "2.0                    0.005747           0.097701          70.574713   \n",
       "3.0                    0.000000           0.033333          93.333333   \n",
       "4.0                    0.012766           0.168085          12.985106   \n",
       "\n",
       "              ENSG00000272735.1  ENSG00000238912.1  ENSG00000257787.1  Count  \n",
       "clusterGroup                                                                  \n",
       "0.0                    4.665929           0.004425           0.037611    452  \n",
       "1.0                    8.931507           0.000000           0.041096     73  \n",
       "2.0                    5.747126           0.000000           0.022989    174  \n",
       "3.0                    8.866667           0.000000           0.000000     30  \n",
       "4.0                    3.255319           0.002128           0.034043    470  \n",
       "\n",
       "[5 rows x 31921 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ef_clusterData = ef.groupby([\"clusterGroup\"]).mean()\n",
    "ef_clusterData[\"Count\"] = pd.Series(ef.groupby([\"clusterGroup\"]).size())\n",
    "ef_clusterData.insert(0, 'Count_', ef_clusterData.Count)\n",
    "ef_clusterData"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>clusterGroup</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>0.0</th>\n",
       "      <td>576</td>\n",
       "      <td>0.145833</td>\n",
       "      <td>783.821181</td>\n",
       "      <td>0.097222</td>\n",
       "      <td>1.460069</td>\n",
       "      <td>2.406250</td>\n",
       "      <td>0.159722</td>\n",
       "      <td>0.039931</td>\n",
       "      <td>0.008681</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>0.649306</td>\n",
       "      <td>1802.510417</td>\n",
       "      <td>0.329861</td>\n",
       "      <td>0.052083</td>\n",
       "      <td>0.164931</td>\n",
       "      <td>35.890625</td>\n",
       "      <td>6.215278</td>\n",
       "      <td>0.032986</td>\n",
       "      <td>0.046875</td>\n",
       "      <td>576</td>\n",
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       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>371</td>\n",
       "      <td>0.102426</td>\n",
       "      <td>874.142857</td>\n",
       "      <td>0.145553</td>\n",
       "      <td>2.328841</td>\n",
       "      <td>2.514825</td>\n",
       "      <td>0.180593</td>\n",
       "      <td>0.021563</td>\n",
       "      <td>0.002695</td>\n",
       "      <td>0.830189</td>\n",
       "      <td>...</td>\n",
       "      <td>0.695418</td>\n",
       "      <td>1902.959569</td>\n",
       "      <td>0.172507</td>\n",
       "      <td>0.037736</td>\n",
       "      <td>0.221024</td>\n",
       "      <td>42.194070</td>\n",
       "      <td>7.229111</td>\n",
       "      <td>0.094340</td>\n",
       "      <td>0.010782</td>\n",
       "      <td>371</td>\n",
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       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>14</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>790.571429</td>\n",
       "      <td>0.214286</td>\n",
       "      <td>2.285714</td>\n",
       "      <td>1.071429</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.571429</td>\n",
       "      <td>...</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1268.071429</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>63.500000</td>\n",
       "      <td>7.571429</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14</td>\n",
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       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>138</td>\n",
       "      <td>0.094203</td>\n",
       "      <td>985.043478</td>\n",
       "      <td>0.065217</td>\n",
       "      <td>1.731884</td>\n",
       "      <td>2.188406</td>\n",
       "      <td>0.239130</td>\n",
       "      <td>0.021739</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.724638</td>\n",
       "      <td>...</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1847.014493</td>\n",
       "      <td>0.217391</td>\n",
       "      <td>0.181159</td>\n",
       "      <td>0.217391</td>\n",
       "      <td>43.920290</td>\n",
       "      <td>8.181159</td>\n",
       "      <td>0.007246</td>\n",
       "      <td>0.007246</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>4</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>639.750000</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>4.250000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>1078.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>22.500000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31921 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Count_  ENSG00000183169.6  ENSG00000100290.2  ENSG00000226765.1  \\\n",
       "clusterGroup                                                                    \n",
       "0.0              576           0.145833         783.821181           0.097222   \n",
       "1.0              371           0.102426         874.142857           0.145553   \n",
       "2.0               14           0.000000         790.571429           0.214286   \n",
       "3.0              138           0.094203         985.043478           0.065217   \n",
       "4.0                4           0.500000         639.750000           1.250000   \n",
       "\n",
       "              ENSG00000241204.1  ENSG00000212135.1  ENSG00000254800.2  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    1.460069           2.406250           0.159722   \n",
       "1.0                    2.328841           2.514825           0.180593   \n",
       "2.0                    2.285714           1.071429           0.142857   \n",
       "3.0                    1.731884           2.188406           0.239130   \n",
       "4.0                    4.250000         517.000000           1.500000   \n",
       "\n",
       "              ENSG00000258516.1  ENSG00000206614.1  ENSG00000265820.1  ...    \\\n",
       "clusterGroup                                                           ...     \n",
       "0.0                    0.039931           0.008681           0.666667  ...     \n",
       "1.0                    0.021563           0.002695           0.830189  ...     \n",
       "2.0                    0.000000           0.000000           0.571429  ...     \n",
       "3.0                    0.021739           0.000000           0.724638  ...     \n",
       "4.0                    0.250000           0.500000          15.000000  ...     \n",
       "\n",
       "              ENSG00000253842.1  ENSG00000125741.4  ENSG00000251610.1  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    0.649306        1802.510417           0.329861   \n",
       "1.0                    0.695418        1902.959569           0.172507   \n",
       "2.0                    0.500000        1268.071429           0.285714   \n",
       "3.0                    0.500000        1847.014493           0.217391   \n",
       "4.0                    4.750000        1078.000000           0.000000   \n",
       "\n",
       "              ENSG00000253413.1  ENSG00000205333.5  ENSG00000259985.1  \\\n",
       "clusterGroup                                                            \n",
       "0.0                    0.052083           0.164931          35.890625   \n",
       "1.0                    0.037736           0.221024          42.194070   \n",
       "2.0                    0.000000           0.071429          63.500000   \n",
       "3.0                    0.181159           0.217391          43.920290   \n",
       "4.0                    0.000000           1.000000          22.500000   \n",
       "\n",
       "              ENSG00000272735.1  ENSG00000238912.1  ENSG00000257787.1  Count  \n",
       "clusterGroup                                                                  \n",
       "0.0                    6.215278           0.032986           0.046875    576  \n",
       "1.0                    7.229111           0.094340           0.010782    371  \n",
       "2.0                    7.571429           0.000000           0.000000     14  \n",
       "3.0                    8.181159           0.007246           0.007246    138  \n",
       "4.0                   25.000000           0.000000           0.000000      4  \n",
       "\n",
       "[5 rows x 31921 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clusterData"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>ENSG00000183169.6</th>\n",
       "      <th>ENSG00000100290.2</th>\n",
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       "      <th>count</th>\n",
       "      <td>1103.000000</td>\n",
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       "      <td>1103.000000</td>\n",
       "      <td>1103.000000</td>\n",
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       "      <td>1103.000000</td>\n",
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       "      <td>1103.000000</td>\n",
       "      <td>1103.000000</td>\n",
       "      <td>1103.000000</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.124207</td>\n",
       "      <td>838.940163</td>\n",
       "      <td>0.115141</td>\n",
       "      <td>1.806890</td>\n",
       "      <td>4.264733</td>\n",
       "      <td>0.181324</td>\n",
       "      <td>0.031732</td>\n",
       "      <td>0.007253</td>\n",
       "      <td>0.779692</td>\n",
       "      <td>390.675431</td>\n",
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       "      <td>0.659112</td>\n",
       "      <td>1832.454216</td>\n",
       "      <td>0.261106</td>\n",
       "      <td>0.062557</td>\n",
       "      <td>0.192203</td>\n",
       "      <td>39.317316</td>\n",
       "      <td>6.887579</td>\n",
       "      <td>0.049864</td>\n",
       "      <td>0.029012</td>\n",
       "      <td>0.751587</td>\n",
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       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.791277</td>\n",
       "      <td>742.571856</td>\n",
       "      <td>0.474750</td>\n",
       "      <td>3.586356</td>\n",
       "      <td>59.678880</td>\n",
       "      <td>0.769033</td>\n",
       "      <td>0.329837</td>\n",
       "      <td>0.120276</td>\n",
       "      <td>1.742358</td>\n",
       "      <td>508.336090</td>\n",
       "      <td>...</td>\n",
       "      <td>1.814397</td>\n",
       "      <td>748.780246</td>\n",
       "      <td>3.141953</td>\n",
       "      <td>0.751697</td>\n",
       "      <td>0.814597</td>\n",
       "      <td>45.114725</td>\n",
       "      <td>7.543826</td>\n",
       "      <td>0.794866</td>\n",
       "      <td>0.529589</td>\n",
       "      <td>1.003594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>263.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>347.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>105.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1323.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>648.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>228.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1727.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1098.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>464.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2245.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
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       "      <td>11243.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>1970.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>6600.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>8005.000000</td>\n",
       "      <td>102.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>389.000000</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>4.000000</td>\n",
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       "<p>8 rows × 31920 columns</p>\n",
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      "text/plain": [
       "       ENSG00000183169.6  ENSG00000100290.2  ENSG00000226765.1  \\\n",
       "count        1103.000000        1103.000000        1103.000000   \n",
       "mean            0.124207         838.940163           0.115141   \n",
       "std             0.791277         742.571856           0.474750   \n",
       "min             0.000000           7.000000           0.000000   \n",
       "25%             0.000000         347.000000           0.000000   \n",
       "50%             0.000000         648.000000           0.000000   \n",
       "75%             0.000000        1098.500000           0.000000   \n",
       "max            22.000000       11243.000000           8.000000   \n",
       "\n",
       "       ENSG00000241204.1  ENSG00000212135.1  ENSG00000254800.2  \\\n",
       "count        1103.000000        1103.000000        1103.000000   \n",
       "mean            1.806890           4.264733           0.181324   \n",
       "std             3.586356          59.678880           0.769033   \n",
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       "25%             0.000000           0.000000           0.000000   \n",
       "50%             1.000000           1.000000           0.000000   \n",
       "75%             2.000000           3.000000           0.000000   \n",
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       "\n",
       "       ENSG00000258516.1  ENSG00000206614.1  ENSG00000265820.1  \\\n",
       "count        1103.000000        1103.000000        1103.000000   \n",
       "mean            0.031732           0.007253           0.779692   \n",
       "std             0.329837           0.120276           1.742358   \n",
       "min             0.000000           0.000000           0.000000   \n",
       "25%             0.000000           0.000000           0.000000   \n",
       "50%             0.000000           0.000000           0.000000   \n",
       "75%             0.000000           0.000000           1.000000   \n",
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       "\n",
       "       ENSG00000108947.4      ...       ENSG00000253842.1  ENSG00000125741.4  \\\n",
       "count        1103.000000      ...             1103.000000        1103.000000   \n",
       "mean          390.675431      ...                0.659112        1832.454216   \n",
       "std           508.336090      ...                1.814397         748.780246   \n",
       "min             2.000000      ...                0.000000         263.000000   \n",
       "25%           105.000000      ...                0.000000        1323.000000   \n",
       "50%           228.000000      ...                0.000000        1727.000000   \n",
       "75%           464.500000      ...                1.000000        2245.500000   \n",
       "max          6600.000000      ...               37.000000        8005.000000   \n",
       "\n",
       "       ENSG00000251610.1  ENSG00000253413.1  ENSG00000205333.5  \\\n",
       "count        1103.000000        1103.000000        1103.000000   \n",
       "mean            0.261106           0.062557           0.192203   \n",
       "std             3.141953           0.751697           0.814597   \n",
       "min             0.000000           0.000000           0.000000   \n",
       "25%             0.000000           0.000000           0.000000   \n",
       "50%             0.000000           0.000000           0.000000   \n",
       "75%             0.000000           0.000000           0.000000   \n",
       "max           102.000000          19.000000          18.000000   \n",
       "\n",
       "       ENSG00000259985.1  ENSG00000272735.1  ENSG00000238912.1  \\\n",
       "count        1103.000000        1103.000000        1103.000000   \n",
       "mean           39.317316           6.887579           0.049864   \n",
       "std            45.114725           7.543826           0.794866   \n",
       "min             0.000000           0.000000           0.000000   \n",
       "25%            14.000000           2.000000           0.000000   \n",
       "50%            26.000000           5.000000           0.000000   \n",
       "75%            47.000000           9.000000           0.000000   \n",
       "max           389.000000          83.000000          24.000000   \n",
       "\n",
       "       ENSG00000257787.1  clusterGroup  \n",
       "count        1103.000000   1103.000000  \n",
       "mean            0.029012      0.751587  \n",
       "std             0.529589      1.003594  \n",
       "min             0.000000      0.000000  \n",
       "25%             0.000000      0.000000  \n",
       "50%             0.000000      0.000000  \n",
       "75%             0.000000      1.000000  \n",
       "max            16.000000      4.000000  \n",
       "\n",
       "[8 rows x 31920 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
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       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.353628</td>\n",
       "      <td>19.900751</td>\n",
       "      <td>0.085905</td>\n",
       "      <td>0.043369</td>\n",
       "      <td>0.266055</td>\n",
       "      <td>0.005838</td>\n",
       "      <td>0.040033</td>\n",
       "      <td>0.000834</td>\n",
       "      <td>0.027523</td>\n",
       "      <td>214.728941</td>\n",
       "      <td>...</td>\n",
       "      <td>0.629691</td>\n",
       "      <td>1261.600500</td>\n",
       "      <td>0.147623</td>\n",
       "      <td>0.007506</td>\n",
       "      <td>0.138449</td>\n",
       "      <td>36.811510</td>\n",
       "      <td>4.634696</td>\n",
       "      <td>0.002502</td>\n",
       "      <td>0.033361</td>\n",
       "      <td>1.994162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.997519</td>\n",
       "      <td>38.015518</td>\n",
       "      <td>0.432556</td>\n",
       "      <td>0.248106</td>\n",
       "      <td>0.593600</td>\n",
       "      <td>0.095644</td>\n",
       "      <td>0.277237</td>\n",
       "      <td>0.028880</td>\n",
       "      <td>0.178315</td>\n",
       "      <td>369.571912</td>\n",
       "      <td>...</td>\n",
       "      <td>1.543899</td>\n",
       "      <td>644.044563</td>\n",
       "      <td>0.712909</td>\n",
       "      <td>0.132185</td>\n",
       "      <td>0.512789</td>\n",
       "      <td>50.858797</td>\n",
       "      <td>4.790955</td>\n",
       "      <td>0.049979</td>\n",
       "      <td>0.201550</td>\n",
       "      <td>1.778878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>249.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>797.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1091.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1568.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>491.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3649.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>5278.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>391.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 31920 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ENSG00000183169.6  ENSG00000100290.2  ENSG00000226765.1  \\\n",
       "count        1199.000000        1199.000000        1199.000000   \n",
       "mean            0.353628          19.900751           0.085905   \n",
       "std             0.997519          38.015518           0.432556   \n",
       "min             0.000000           0.000000           0.000000   \n",
       "25%             0.000000           3.000000           0.000000   \n",
       "50%             0.000000           7.000000           0.000000   \n",
       "75%             0.000000          15.000000           0.000000   \n",
       "max            10.000000         491.000000           5.000000   \n",
       "\n",
       "       ENSG00000241204.1  ENSG00000212135.1  ENSG00000254800.2  \\\n",
       "count        1199.000000        1199.000000        1199.000000   \n",
       "mean            0.043369           0.266055           0.005838   \n",
       "std             0.248106           0.593600           0.095644   \n",
       "min             0.000000           0.000000           0.000000   \n",
       "25%             0.000000           0.000000           0.000000   \n",
       "50%             0.000000           0.000000           0.000000   \n",
       "75%             0.000000           0.000000           0.000000   \n",
       "max             2.000000           4.000000           2.000000   \n",
       "\n",
       "       ENSG00000258516.1  ENSG00000206614.1  ENSG00000265820.1  \\\n",
       "count        1199.000000        1199.000000        1199.000000   \n",
       "mean            0.040033           0.000834           0.027523   \n",
       "std             0.277237           0.028880           0.178315   \n",
       "min             0.000000           0.000000           0.000000   \n",
       "25%             0.000000           0.000000           0.000000   \n",
       "50%             0.000000           0.000000           0.000000   \n",
       "75%             0.000000           0.000000           0.000000   \n",
       "max             4.000000           1.000000           2.000000   \n",
       "\n",
       "       ENSG00000108947.4      ...       ENSG00000253842.1  ENSG00000125741.4  \\\n",
       "count        1199.000000      ...             1199.000000        1199.000000   \n",
       "mean          214.728941      ...                0.629691        1261.600500   \n",
       "std           369.571912      ...                1.543899         644.044563   \n",
       "min             0.000000      ...                0.000000         249.000000   \n",
       "25%            28.000000      ...                0.000000         797.500000   \n",
       "50%            80.000000      ...                0.000000        1091.000000   \n",
       "75%           220.000000      ...                0.500000        1568.500000   \n",
       "max          3649.000000      ...               19.000000        5278.000000   \n",
       "\n",
       "       ENSG00000251610.1  ENSG00000253413.1  ENSG00000205333.5  \\\n",
       "count        1199.000000        1199.000000        1199.000000   \n",
       "mean            0.147623           0.007506           0.138449   \n",
       "std             0.712909           0.132185           0.512789   \n",
       "min             0.000000           0.000000           0.000000   \n",
       "25%             0.000000           0.000000           0.000000   \n",
       "50%             0.000000           0.000000           0.000000   \n",
       "75%             0.000000           0.000000           0.000000   \n",
       "max            10.000000           4.000000           4.000000   \n",
       "\n",
       "       ENSG00000259985.1  ENSG00000272735.1  ENSG00000238912.1  \\\n",
       "count        1199.000000        1199.000000        1199.000000   \n",
       "mean           36.811510           4.634696           0.002502   \n",
       "std            50.858797           4.790955           0.049979   \n",
       "min             0.000000           0.000000           0.000000   \n",
       "25%             8.500000           2.000000           0.000000   \n",
       "50%            18.000000           4.000000           0.000000   \n",
       "75%            37.000000           6.000000           0.000000   \n",
       "max           391.000000          39.000000           1.000000   \n",
       "\n",
       "       ENSG00000257787.1  clusterGroup  \n",
       "count        1199.000000   1199.000000  \n",
       "mean            0.033361      1.994162  \n",
       "std             0.201550      1.778878  \n",
       "min             0.000000      0.000000  \n",
       "25%             0.000000      0.000000  \n",
       "50%             0.000000      2.000000  \n",
       "75%             0.000000      4.000000  \n",
       "max             2.000000      4.000000  \n",
       "\n",
       "[8 rows x 31920 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ef.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "GDCmean = df.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ENSG00000183169.6        0.124207\n",
       "ENSG00000100290.2      838.940163\n",
       "ENSG00000226765.1        0.115141\n",
       "ENSG00000241204.1        1.806890\n",
       "ENSG00000212135.1        4.264733\n",
       "ENSG00000254800.2        0.181324\n",
       "ENSG00000258516.1        0.031732\n",
       "ENSG00000206614.1        0.007253\n",
       "ENSG00000265820.1        0.779692\n",
       "ENSG00000108947.4      390.675431\n",
       "ENSG00000255226.1        0.309157\n",
       "ENSG00000230764.1        0.047144\n",
       "ENSG00000251713.1        0.992747\n",
       "ENSG00000220924.4        0.747960\n",
       "ENSG00000231422.2        0.830462\n",
       "ENSG00000263630.1        0.007253\n",
       "ENSG00000260863.1        0.116954\n",
       "ENSG00000264070.1       34.739801\n",
       "ENSG00000229852.2      149.085222\n",
       "ENSG00000233222.2        0.425204\n",
       "ENSG00000264831.1        0.113327\n",
       "ENSG00000249581.2        0.202176\n",
       "ENSG00000253099.1        0.078876\n",
       "ENSG00000271559.1        0.010879\n",
       "ENSG00000202431.1        1.230281\n",
       "ENSG00000201524.1        0.549411\n",
       "ENSG00000227076.1        9.240254\n",
       "ENSG00000228703.1        0.000000\n",
       "ENSG00000205790.1       21.087942\n",
       "ENSG00000228204.2       12.675431\n",
       "                         ...     \n",
       "ENSG00000211768.1        0.542158\n",
       "ENSG00000222069.1        0.410698\n",
       "ENSG00000269419.1        0.256573\n",
       "ENSG00000270225.1        8.451496\n",
       "ENSG00000234617.1        9.074343\n",
       "ENSG00000272915.1        1.114234\n",
       "ENSG00000271606.1        0.019039\n",
       "ENSG00000255380.1        0.016319\n",
       "ENSG00000223086.1        0.814143\n",
       "ENSG00000136149.6      245.893926\n",
       "ENSG00000266593.1        0.009973\n",
       "ENSG00000249386.1        0.023572\n",
       "ENSG00000235932.2        0.005440\n",
       "ENSG00000156886.11      51.693563\n",
       "ENSG00000258809.1        2.271985\n",
       "ENSG00000232034.1        5.215775\n",
       "ENSG00000207992.1        0.009066\n",
       "ENSG00000261455.1      306.716228\n",
       "ENSG00000252505.1        0.011786\n",
       "ENSG00000243547.1       32.533998\n",
       "ENSG00000253842.1        0.659112\n",
       "ENSG00000125741.4     1832.454216\n",
       "ENSG00000251610.1        0.261106\n",
       "ENSG00000253413.1        0.062557\n",
       "ENSG00000205333.5        0.192203\n",
       "ENSG00000259985.1       39.317316\n",
       "ENSG00000272735.1        6.887579\n",
       "ENSG00000238912.1        0.049864\n",
       "ENSG00000257787.1        0.029012\n",
       "clusterGroup             0.751587\n",
       "Length: 31920, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GDCmean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "GTexmean = ef.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ENSG00000183169.6        0.353628\n",
       "ENSG00000100290.2       19.900751\n",
       "ENSG00000226765.1        0.085905\n",
       "ENSG00000241204.1        0.043369\n",
       "ENSG00000212135.1        0.266055\n",
       "ENSG00000254800.2        0.005838\n",
       "ENSG00000258516.1        0.040033\n",
       "ENSG00000206614.1        0.000834\n",
       "ENSG00000265820.1        0.027523\n",
       "ENSG00000108947.4      214.728941\n",
       "ENSG00000255226.1        1.221018\n",
       "ENSG00000230764.1        0.000000\n",
       "ENSG00000251713.1        0.046706\n",
       "ENSG00000220924.4        0.065054\n",
       "ENSG00000231422.2        0.874062\n",
       "ENSG00000263630.1        0.005004\n",
       "ENSG00000260863.1        0.130942\n",
       "ENSG00000264070.1       38.675563\n",
       "ENSG00000229852.2       91.982485\n",
       "ENSG00000233222.2        1.433695\n",
       "ENSG00000264831.1        0.001668\n",
       "ENSG00000249581.2        0.160133\n",
       "ENSG00000253099.1        0.005004\n",
       "ENSG00000271559.1        0.007506\n",
       "ENSG00000202431.1        0.000834\n",
       "ENSG00000201524.1        0.030859\n",
       "ENSG00000227076.1        4.590492\n",
       "ENSG00000228703.1       15.069224\n",
       "ENSG00000205790.1      105.152627\n",
       "ENSG00000228204.2        1.432027\n",
       "                         ...     \n",
       "ENSG00000211768.1        0.125938\n",
       "ENSG00000222069.1        0.355296\n",
       "ENSG00000269419.1        0.034195\n",
       "ENSG00000270225.1        6.028357\n",
       "ENSG00000234617.1       14.515430\n",
       "ENSG00000272915.1        1.366972\n",
       "ENSG00000271606.1        0.000834\n",
       "ENSG00000255380.1        0.003336\n",
       "ENSG00000223086.1        1.293578\n",
       "ENSG00000136149.6      122.059216\n",
       "ENSG00000266593.1        0.000834\n",
       "ENSG00000249386.1        0.012510\n",
       "ENSG00000235932.2        0.000834\n",
       "ENSG00000156886.11      29.784821\n",
       "ENSG00000258809.1        0.341118\n",
       "ENSG00000232034.1        1.803169\n",
       "ENSG00000207992.1        0.000000\n",
       "ENSG00000261455.1      325.731443\n",
       "ENSG00000252505.1        0.025021\n",
       "ENSG00000243547.1       36.737281\n",
       "ENSG00000253842.1        0.629691\n",
       "ENSG00000125741.4     1261.600500\n",
       "ENSG00000251610.1        0.147623\n",
       "ENSG00000253413.1        0.007506\n",
       "ENSG00000205333.5        0.138449\n",
       "ENSG00000259985.1       36.811510\n",
       "ENSG00000272735.1        4.634696\n",
       "ENSG00000238912.1        0.002502\n",
       "ENSG00000257787.1        0.033361\n",
       "clusterGroup             1.994162\n",
       "Length: 31920, dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GTexmean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(GDCmean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "GDCmeanList = GDCmean.tolist()\n",
    "GTexmeanList = GTexmean.tolist()\n",
    "cols = df.columns.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.353628023352794,\n",
       " 19.90075062552127,\n",
       " 0.08590492076730609,\n",
       " 0.043369474562135114,\n",
       " 0.26605504587155965,\n",
       " 0.005838198498748957,\n",
       " 0.040033361134278564,\n",
       " 0.0008340283569641367,\n",
       " 0.027522935779816515,\n",
       " 214.72894078398664,\n",
       " 1.2210175145954962,\n",
       " 0.0,\n",
       " 0.04670558798999166,\n",
       " 0.06505421184320268,\n",
       " 0.8740617180984154,\n",
       " 0.0050041701417848205,\n",
       " 0.13094245204336946,\n",
       " 38.67556296914095,\n",
       " 91.98248540450375,\n",
       " 1.4336947456213511,\n",
       " 0.0016680567139282735,\n",
       " 0.16013344453711426,\n",
       " 0.0050041701417848205,\n",
       " 0.007506255212677231,\n",
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       " 0.03252710592160134,\n",
       " ...]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GTexmeanList"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "76"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "featureColumns = []\n",
    "for i in range(len(GDCmeanList)):\n",
    "    if(abs(GDCmeanList[i] - GTexmeanList[i]) > 10000):\n",
    "        featureColumns.append(cols[i])\n",
    "\n",
    "len(featureColumns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " ...]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "featureColumns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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