libd_explore.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "spots = pd.read_csv('Data/spatialLIBD/spatialLIBD_spot_counts.csv', header = 0, index_col = 0, sep =',')\n",
    "st = pd.read_csv('Data/spatialLIBD/spatialLIBD_spot_st.csv')\n",
    "gene_meta = pd.read_csv('Data/spatialLIBD/gene_meta.csv')\n",
    "cell_type = pd.read_csv('Data/spatialLIBD/RowDataTable1.csv')\n",
    "csr = pd.read_csv('Data/spatialLIBD/spatialLIBD_csr_counts.csv', index_col=0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sample_id</th>\n",
       "      <th>Cluster</th>\n",
       "      <th>sum_umi</th>\n",
       "      <th>sum_gene</th>\n",
       "      <th>subject</th>\n",
       "      <th>position</th>\n",
       "      <th>replicate</th>\n",
       "      <th>subject_position</th>\n",
       "      <th>discard</th>\n",
       "      <th>key</th>\n",
       "      <th>...</th>\n",
       "      <th>SpatialDE_UMAP_spatial</th>\n",
       "      <th>SpatialDE_pool_UMAP_spatial</th>\n",
       "      <th>HVG_UMAP_spatial</th>\n",
       "      <th>pseudobulk_UMAP_spatial</th>\n",
       "      <th>markers_UMAP_spatial</th>\n",
       "      <th>spatialLIBD</th>\n",
       "      <th>ManualAnnotation</th>\n",
       "      <th>in_tissue</th>\n",
       "      <th>array_row</th>\n",
       "      <th>array_col</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAACAACGAATAGTTC-1</th>\n",
       "      <td>151507</td>\n",
       "      <td>6</td>\n",
       "      <td>948</td>\n",
       "      <td>727</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Br5292_pos0</td>\n",
       "      <td>False</td>\n",
       "      <td>151507_AAACAACGAATAGTTC-1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>L1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACAAGTATCTCCCA-1</th>\n",
       "      <td>151507</td>\n",
       "      <td>3</td>\n",
       "      <td>4261</td>\n",
       "      <td>2170</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Br5292_pos0</td>\n",
       "      <td>False</td>\n",
       "      <td>151507_AAACAAGTATCTCCCA-1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>L3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>50</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACAATCTACTAGCA-1</th>\n",
       "      <td>151507</td>\n",
       "      <td>2</td>\n",
       "      <td>1969</td>\n",
       "      <td>1093</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Br5292_pos0</td>\n",
       "      <td>False</td>\n",
       "      <td>151507_AAACAATCTACTAGCA-1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>L1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>3</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACACCAATAACTGC-1</th>\n",
       "      <td>151507</td>\n",
       "      <td>5</td>\n",
       "      <td>3368</td>\n",
       "      <td>1896</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Br5292_pos0</td>\n",
       "      <td>False</td>\n",
       "      <td>151507_AAACACCAATAACTGC-1</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>WM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>59</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACAGCTTTCAGAAG-1</th>\n",
       "      <td>151507</td>\n",
       "      <td>1</td>\n",
       "      <td>2981</td>\n",
       "      <td>1620</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Br5292_pos0</td>\n",
       "      <td>False</td>\n",
       "      <td>151507_AAACAGCTTTCAGAAG-1</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>L6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>43</td>\n",
       "      <td>9</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>TTGTTGTGTGTCAAGA-1.11</th>\n",
       "      <td>151676</td>\n",
       "      <td>5</td>\n",
       "      <td>2880</td>\n",
       "      <td>1638</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>300</td>\n",
       "      <td>2</td>\n",
       "      <td>Br8100_pos300</td>\n",
       "      <td>False</td>\n",
       "      <td>151676_TTGTTGTGTGTCAAGA-1</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>L6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>31</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTCACATCCAGG-1.11</th>\n",
       "      <td>151676</td>\n",
       "      <td>2</td>\n",
       "      <td>2640</td>\n",
       "      <td>1526</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>300</td>\n",
       "      <td>2</td>\n",
       "      <td>Br8100_pos300</td>\n",
       "      <td>False</td>\n",
       "      <td>151676_TTGTTTCACATCCAGG-1</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>WM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>58</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTCATTAGTCTA-1.11</th>\n",
       "      <td>151676</td>\n",
       "      <td>2</td>\n",
       "      <td>2063</td>\n",
       "      <td>1279</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>300</td>\n",
       "      <td>2</td>\n",
       "      <td>Br8100_pos300</td>\n",
       "      <td>False</td>\n",
       "      <td>151676_TTGTTTCATTAGTCTA-1</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>WM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>60</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTCCATACAACT-1.11</th>\n",
       "      <td>151676</td>\n",
       "      <td>7</td>\n",
       "      <td>1031</td>\n",
       "      <td>748</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>300</td>\n",
       "      <td>2</td>\n",
       "      <td>Br8100_pos300</td>\n",
       "      <td>False</td>\n",
       "      <td>151676_TTGTTTCCATACAACT-1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>L6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>45</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTGTGTAAATTC-1.10</th>\n",
       "      <td>151676</td>\n",
       "      <td>1</td>\n",
       "      <td>2625</td>\n",
       "      <td>1392</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>300</td>\n",
       "      <td>2</td>\n",
       "      <td>Br8100_pos300</td>\n",
       "      <td>False</td>\n",
       "      <td>151676_TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>L1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>7</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>47681 rows × 69 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       sample_id  Cluster  sum_umi  sum_gene subject  \\\n",
       "AAACAACGAATAGTTC-1        151507        6      948       727  Br5292   \n",
       "AAACAAGTATCTCCCA-1        151507        3     4261      2170  Br5292   \n",
       "AAACAATCTACTAGCA-1        151507        2     1969      1093  Br5292   \n",
       "AAACACCAATAACTGC-1        151507        5     3368      1896  Br5292   \n",
       "AAACAGCTTTCAGAAG-1        151507        1     2981      1620  Br5292   \n",
       "...                          ...      ...      ...       ...     ...   \n",
       "TTGTTGTGTGTCAAGA-1.11     151676        5     2880      1638  Br8100   \n",
       "TTGTTTCACATCCAGG-1.11     151676        2     2640      1526  Br8100   \n",
       "TTGTTTCATTAGTCTA-1.11     151676        2     2063      1279  Br8100   \n",
       "TTGTTTCCATACAACT-1.11     151676        7     1031       748  Br8100   \n",
       "TTGTTTGTGTAAATTC-1.10     151676        1     2625      1392  Br8100   \n",
       "\n",
       "                       position  replicate subject_position  discard  \\\n",
       "AAACAACGAATAGTTC-1            0          1      Br5292_pos0    False   \n",
       "AAACAAGTATCTCCCA-1            0          1      Br5292_pos0    False   \n",
       "AAACAATCTACTAGCA-1            0          1      Br5292_pos0    False   \n",
       "AAACACCAATAACTGC-1            0          1      Br5292_pos0    False   \n",
       "AAACAGCTTTCAGAAG-1            0          1      Br5292_pos0    False   \n",
       "...                         ...        ...              ...      ...   \n",
       "TTGTTGTGTGTCAAGA-1.11       300          2    Br8100_pos300    False   \n",
       "TTGTTTCACATCCAGG-1.11       300          2    Br8100_pos300    False   \n",
       "TTGTTTCATTAGTCTA-1.11       300          2    Br8100_pos300    False   \n",
       "TTGTTTCCATACAACT-1.11       300          2    Br8100_pos300    False   \n",
       "TTGTTTGTGTAAATTC-1.10       300          2    Br8100_pos300    False   \n",
       "\n",
       "                                             key  ...  SpatialDE_UMAP_spatial  \\\n",
       "AAACAACGAATAGTTC-1     151507_AAACAACGAATAGTTC-1  ...                       1   \n",
       "AAACAAGTATCTCCCA-1     151507_AAACAAGTATCTCCCA-1  ...                       2   \n",
       "AAACAATCTACTAGCA-1     151507_AAACAATCTACTAGCA-1  ...                       2   \n",
       "AAACACCAATAACTGC-1     151507_AAACACCAATAACTGC-1  ...                       7   \n",
       "AAACAGCTTTCAGAAG-1     151507_AAACAGCTTTCAGAAG-1  ...                       8   \n",
       "...                                          ...  ...                     ...   \n",
       "TTGTTGTGTGTCAAGA-1.11  151676_TTGTTGTGTGTCAAGA-1  ...                       6   \n",
       "TTGTTTCACATCCAGG-1.11  151676_TTGTTTCACATCCAGG-1  ...                       5   \n",
       "TTGTTTCATTAGTCTA-1.11  151676_TTGTTTCATTAGTCTA-1  ...                       5   \n",
       "TTGTTTCCATACAACT-1.11  151676_TTGTTTCCATACAACT-1  ...                       2   \n",
       "TTGTTTGTGTAAATTC-1.10  151676_TTGTTTGTGTAAATTC-1  ...                       1   \n",
       "\n",
       "                       SpatialDE_pool_UMAP_spatial  HVG_UMAP_spatial  \\\n",
       "AAACAACGAATAGTTC-1                               1                 1   \n",
       "AAACAAGTATCTCCCA-1                               2                 1   \n",
       "AAACAATCTACTAGCA-1                               1                 4   \n",
       "AAACACCAATAACTGC-1                               8                 7   \n",
       "AAACAGCTTTCAGAAG-1                               2                 8   \n",
       "...                                            ...               ...   \n",
       "TTGTTGTGTGTCAAGA-1.11                            1                 4   \n",
       "TTGTTTCACATCCAGG-1.11                            5                 5   \n",
       "TTGTTTCATTAGTCTA-1.11                            5                 8   \n",
       "TTGTTTCCATACAACT-1.11                            3                 2   \n",
       "TTGTTTGTGTAAATTC-1.10                            2                 1   \n",
       "\n",
       "                       pseudobulk_UMAP_spatial  markers_UMAP_spatial  \\\n",
       "AAACAACGAATAGTTC-1                           1                     1   \n",
       "AAACAAGTATCTCCCA-1                           2                     1   \n",
       "AAACAATCTACTAGCA-1                           1                     6   \n",
       "AAACACCAATAACTGC-1                           8                     1   \n",
       "AAACAGCTTTCAGAAG-1                           1                     1   \n",
       "...                                        ...                   ...   \n",
       "TTGTTGTGTGTCAAGA-1.11                        1                     1   \n",
       "TTGTTTCACATCCAGG-1.11                        8                     1   \n",
       "TTGTTTCATTAGTCTA-1.11                        1                     1   \n",
       "TTGTTTCCATACAACT-1.11                        4                     7   \n",
       "TTGTTTGTGTAAATTC-1.10                        2                     5   \n",
       "\n",
       "                       spatialLIBD  ManualAnnotation  in_tissue  array_row  \\\n",
       "AAACAACGAATAGTTC-1              L1               NaN       True          0   \n",
       "AAACAAGTATCTCCCA-1              L3               NaN       True         50   \n",
       "AAACAATCTACTAGCA-1              L1               NaN       True          3   \n",
       "AAACACCAATAACTGC-1              WM               NaN       True         59   \n",
       "AAACAGCTTTCAGAAG-1              L6               NaN       True         43   \n",
       "...                            ...               ...        ...        ...   \n",
       "TTGTTGTGTGTCAAGA-1.11           L6               NaN       True         31   \n",
       "TTGTTTCACATCCAGG-1.11           WM               NaN       True         58   \n",
       "TTGTTTCATTAGTCTA-1.11           WM               NaN       True         60   \n",
       "TTGTTTCCATACAACT-1.11           L6               NaN       True         45   \n",
       "TTGTTTGTGTAAATTC-1.10           L1               NaN       True          7   \n",
       "\n",
       "                       array_col  \n",
       "AAACAACGAATAGTTC-1            16  \n",
       "AAACAAGTATCTCCCA-1           102  \n",
       "AAACAATCTACTAGCA-1            43  \n",
       "AAACACCAATAACTGC-1            19  \n",
       "AAACAGCTTTCAGAAG-1             9  \n",
       "...                          ...  \n",
       "TTGTTGTGTGTCAAGA-1.11         77  \n",
       "TTGTTTCACATCCAGG-1.11         42  \n",
       "TTGTTTCATTAGTCTA-1.11         30  \n",
       "TTGTTTCCATACAACT-1.11         27  \n",
       "TTGTTTGTGTAAATTC-1.10         51  \n",
       "\n",
       "[47681 rows x 69 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(47681, 69)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spots.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['sample_id', 'Cluster', 'sum_umi', 'sum_gene', 'subject', 'position',\n",
       "       'replicate', 'subject_position', 'discard', 'key', 'cell_count',\n",
       "       'SNN_k50_k4', 'SNN_k50_k5', 'SNN_k50_k6', 'SNN_k50_k7', 'SNN_k50_k8',\n",
       "       'SNN_k50_k9', 'SNN_k50_k10', 'SNN_k50_k11', 'SNN_k50_k12',\n",
       "       'SNN_k50_k13', 'SNN_k50_k14', 'SNN_k50_k15', 'SNN_k50_k16',\n",
       "       'SNN_k50_k17', 'SNN_k50_k18', 'SNN_k50_k19', 'SNN_k50_k20',\n",
       "       'SNN_k50_k21', 'SNN_k50_k22', 'SNN_k50_k23', 'SNN_k50_k24',\n",
       "       'SNN_k50_k25', 'SNN_k50_k26', 'SNN_k50_k27', 'SNN_k50_k28',\n",
       "       'GraphBased', 'Maynard', 'Martinowich', 'layer_guess',\n",
       "       'layer_guess_reordered', 'layer_guess_reordered_short', 'expr_chrM',\n",
       "       'expr_chrM_ratio', 'SpatialDE_PCA', 'SpatialDE_pool_PCA', 'HVG_PCA',\n",
       "       'pseudobulk_PCA', 'markers_PCA', 'SpatialDE_UMAP',\n",
       "       'SpatialDE_pool_UMAP', 'HVG_UMAP', 'pseudobulk_UMAP', 'markers_UMAP',\n",
       "       'SpatialDE_PCA_spatial', 'SpatialDE_pool_PCA_spatial',\n",
       "       'HVG_PCA_spatial', 'pseudobulk_PCA_spatial', 'markers_PCA_spatial',\n",
       "       'SpatialDE_UMAP_spatial', 'SpatialDE_pool_UMAP_spatial',\n",
       "       'HVG_UMAP_spatial', 'pseudobulk_UMAP_spatial', 'markers_UMAP_spatial',\n",
       "       'spatialLIBD', 'ManualAnnotation', 'in_tissue', 'array_row',\n",
       "       'array_col'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spots.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 12 samples in dataset\n",
    "len(np.unique(spots.loc(axis=1)['sample_id'].values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Br5292', 'Br5595', 'Br8100'], dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# taken from 3 patients\n",
    "np.unique(spots.loc(axis=1)['subject'].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>spot</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAACAACGAATAGTTC-1</td>\n",
       "      <td>3276</td>\n",
       "      <td>2514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AAACAAGTATCTCCCA-1</td>\n",
       "      <td>9178</td>\n",
       "      <td>8520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAACAATCTACTAGCA-1</td>\n",
       "      <td>5133</td>\n",
       "      <td>2878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAACACCAATAACTGC-1</td>\n",
       "      <td>3462</td>\n",
       "      <td>9581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AAACAGCTTTCAGAAG-1</td>\n",
       "      <td>2779</td>\n",
       "      <td>7663</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 spot     X     Y\n",
       "0  AAACAACGAATAGTTC-1  3276  2514\n",
       "1  AAACAAGTATCTCCCA-1  9178  8520\n",
       "2  AAACAATCTACTAGCA-1  5133  2878\n",
       "3  AAACACCAATAACTGC-1  3462  9581\n",
       "4  AAACAGCTTTCAGAAG-1  2779  7663"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# rename st column names\n",
    "st.columns = [\"spot\", \"X\", \"Y\"]\n",
    "st.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "47681 4941\n"
     ]
    }
   ],
   "source": [
    "print(len(st[['spot']].values), len(np.unique(st[['spot']].values)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([151507, 151508, 151509, 151510, 151669, 151670, 151671, 151672,\n",
       "       151673, 151674, 151675, 151676])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(spots[['sample_id']].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "47681 47681\n"
     ]
    }
   ],
   "source": [
    "print(len(st), len(spots))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>sample_id</th>\n",
       "      <th>key</th>\n",
       "      <th>subject</th>\n",
       "      <th>replicate</th>\n",
       "      <th>Cluster</th>\n",
       "      <th>sum_umi</th>\n",
       "      <th>sum_gene</th>\n",
       "      <th>cell_count</th>\n",
       "      <th>in_tissue</th>\n",
       "      <th>spatialLIBD</th>\n",
       "      <th>array_col</th>\n",
       "      <th>array_row</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAACAACGAATAGTTC-1</th>\n",
       "      <td>151507</td>\n",
       "      <td>151507_AAACAACGAATAGTTC-1</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>948</td>\n",
       "      <td>727</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>L1</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACAAGTATCTCCCA-1</th>\n",
       "      <td>151507</td>\n",
       "      <td>151507_AAACAAGTATCTCCCA-1</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4261</td>\n",
       "      <td>2170</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>L3</td>\n",
       "      <td>102</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACAATCTACTAGCA-1</th>\n",
       "      <td>151507</td>\n",
       "      <td>151507_AAACAATCTACTAGCA-1</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1969</td>\n",
       "      <td>1093</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>L1</td>\n",
       "      <td>43</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACACCAATAACTGC-1</th>\n",
       "      <td>151507</td>\n",
       "      <td>151507_AAACACCAATAACTGC-1</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3368</td>\n",
       "      <td>1896</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "      <td>WM</td>\n",
       "      <td>19</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACAGCTTTCAGAAG-1</th>\n",
       "      <td>151507</td>\n",
       "      <td>151507_AAACAGCTTTCAGAAG-1</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2981</td>\n",
       "      <td>1620</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>L6</td>\n",
       "      <td>9</td>\n",
       "      <td>43</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTGTGTGTCAAGA-1.11</th>\n",
       "      <td>151676</td>\n",
       "      <td>151676_TTGTTGTGTGTCAAGA-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2880</td>\n",
       "      <td>1638</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>L6</td>\n",
       "      <td>77</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTCACATCCAGG-1.11</th>\n",
       "      <td>151676</td>\n",
       "      <td>151676_TTGTTTCACATCCAGG-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2640</td>\n",
       "      <td>1526</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "      <td>WM</td>\n",
       "      <td>42</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTCATTAGTCTA-1.11</th>\n",
       "      <td>151676</td>\n",
       "      <td>151676_TTGTTTCATTAGTCTA-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2063</td>\n",
       "      <td>1279</td>\n",
       "      <td>9</td>\n",
       "      <td>True</td>\n",
       "      <td>WM</td>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTCCATACAACT-1.11</th>\n",
       "      <td>151676</td>\n",
       "      <td>151676_TTGTTTCCATACAACT-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>1031</td>\n",
       "      <td>748</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>L6</td>\n",
       "      <td>27</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTGTGTAAATTC-1.10</th>\n",
       "      <td>151676</td>\n",
       "      <td>151676_TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2625</td>\n",
       "      <td>1392</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>L1</td>\n",
       "      <td>51</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>47681 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       sample_id                        key subject  \\\n",
       "AAACAACGAATAGTTC-1        151507  151507_AAACAACGAATAGTTC-1  Br5292   \n",
       "AAACAAGTATCTCCCA-1        151507  151507_AAACAAGTATCTCCCA-1  Br5292   \n",
       "AAACAATCTACTAGCA-1        151507  151507_AAACAATCTACTAGCA-1  Br5292   \n",
       "AAACACCAATAACTGC-1        151507  151507_AAACACCAATAACTGC-1  Br5292   \n",
       "AAACAGCTTTCAGAAG-1        151507  151507_AAACAGCTTTCAGAAG-1  Br5292   \n",
       "...                          ...                        ...     ...   \n",
       "TTGTTGTGTGTCAAGA-1.11     151676  151676_TTGTTGTGTGTCAAGA-1  Br8100   \n",
       "TTGTTTCACATCCAGG-1.11     151676  151676_TTGTTTCACATCCAGG-1  Br8100   \n",
       "TTGTTTCATTAGTCTA-1.11     151676  151676_TTGTTTCATTAGTCTA-1  Br8100   \n",
       "TTGTTTCCATACAACT-1.11     151676  151676_TTGTTTCCATACAACT-1  Br8100   \n",
       "TTGTTTGTGTAAATTC-1.10     151676  151676_TTGTTTGTGTAAATTC-1  Br8100   \n",
       "\n",
       "                       replicate  Cluster  sum_umi  sum_gene  cell_count  \\\n",
       "AAACAACGAATAGTTC-1             1        6      948       727           0   \n",
       "AAACAAGTATCTCCCA-1             1        3     4261      2170           3   \n",
       "AAACAATCTACTAGCA-1             1        2     1969      1093           2   \n",
       "AAACACCAATAACTGC-1             1        5     3368      1896           5   \n",
       "AAACAGCTTTCAGAAG-1             1        1     2981      1620           3   \n",
       "...                          ...      ...      ...       ...         ...   \n",
       "TTGTTGTGTGTCAAGA-1.11          2        5     2880      1638           1   \n",
       "TTGTTTCACATCCAGG-1.11          2        2     2640      1526           6   \n",
       "TTGTTTCATTAGTCTA-1.11          2        2     2063      1279           9   \n",
       "TTGTTTCCATACAACT-1.11          2        7     1031       748           2   \n",
       "TTGTTTGTGTAAATTC-1.10          2        1     2625      1392           0   \n",
       "\n",
       "                       in_tissue spatialLIBD  array_col  array_row  \n",
       "AAACAACGAATAGTTC-1          True          L1         16          0  \n",
       "AAACAAGTATCTCCCA-1          True          L3        102         50  \n",
       "AAACAATCTACTAGCA-1          True          L1         43          3  \n",
       "AAACACCAATAACTGC-1          True          WM         19         59  \n",
       "AAACAGCTTTCAGAAG-1          True          L6          9         43  \n",
       "...                          ...         ...        ...        ...  \n",
       "TTGTTGTGTGTCAAGA-1.11       True          L6         77         31  \n",
       "TTGTTTCACATCCAGG-1.11       True          WM         42         58  \n",
       "TTGTTTCATTAGTCTA-1.11       True          WM         30         60  \n",
       "TTGTTTCCATACAACT-1.11       True          L6         27         45  \n",
       "TTGTTTGTGTAAATTC-1.10       True          L1         51          7  \n",
       "\n",
       "[47681 rows x 12 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select specific cols only\n",
    "spot = spots[['sample_id', 'key', 'subject', 'replicate', 'Cluster', 'sum_umi', 'sum_gene', 'cell_count', 'in_tissue','spatialLIBD', 'array_col', 'array_row']]\n",
    "spot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>spot</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>index</th>\n",
       "      <th>sample_id</th>\n",
       "      <th>key</th>\n",
       "      <th>subject</th>\n",
       "      <th>replicate</th>\n",
       "      <th>Cluster</th>\n",
       "      <th>sum_umi</th>\n",
       "      <th>sum_gene</th>\n",
       "      <th>cell_count</th>\n",
       "      <th>in_tissue</th>\n",
       "      <th>spatialLIBD</th>\n",
       "      <th>array_col</th>\n",
       "      <th>array_row</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAACAACGAATAGTTC-1</td>\n",
       "      <td>3276</td>\n",
       "      <td>2514</td>\n",
       "      <td>AAACAACGAATAGTTC-1</td>\n",
       "      <td>151507</td>\n",
       "      <td>151507_AAACAACGAATAGTTC-1</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>948</td>\n",
       "      <td>727</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>L1</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AAACAAGTATCTCCCA-1</td>\n",
       "      <td>9178</td>\n",
       "      <td>8520</td>\n",
       "      <td>AAACAAGTATCTCCCA-1</td>\n",
       "      <td>151507</td>\n",
       "      <td>151507_AAACAAGTATCTCCCA-1</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4261</td>\n",
       "      <td>2170</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>L3</td>\n",
       "      <td>102</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAACAATCTACTAGCA-1</td>\n",
       "      <td>5133</td>\n",
       "      <td>2878</td>\n",
       "      <td>AAACAATCTACTAGCA-1</td>\n",
       "      <td>151507</td>\n",
       "      <td>151507_AAACAATCTACTAGCA-1</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1969</td>\n",
       "      <td>1093</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>L1</td>\n",
       "      <td>43</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAACACCAATAACTGC-1</td>\n",
       "      <td>3462</td>\n",
       "      <td>9581</td>\n",
       "      <td>AAACACCAATAACTGC-1</td>\n",
       "      <td>151507</td>\n",
       "      <td>151507_AAACACCAATAACTGC-1</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3368</td>\n",
       "      <td>1896</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "      <td>WM</td>\n",
       "      <td>19</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AAACAGCTTTCAGAAG-1</td>\n",
       "      <td>2779</td>\n",
       "      <td>7663</td>\n",
       "      <td>AAACAGCTTTCAGAAG-1</td>\n",
       "      <td>151507</td>\n",
       "      <td>151507_AAACAGCTTTCAGAAG-1</td>\n",
       "      <td>Br5292</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2981</td>\n",
       "      <td>1620</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>L6</td>\n",
       "      <td>9</td>\n",
       "      <td>43</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47676</th>\n",
       "      <td>TTGTTGTGTGTCAAGA-1</td>\n",
       "      <td>7946</td>\n",
       "      <td>6378</td>\n",
       "      <td>TTGTTGTGTGTCAAGA-1.11</td>\n",
       "      <td>151676</td>\n",
       "      <td>151676_TTGTTGTGTGTCAAGA-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2880</td>\n",
       "      <td>1638</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>L6</td>\n",
       "      <td>77</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47677</th>\n",
       "      <td>TTGTTTCACATCCAGG-1</td>\n",
       "      <td>5512</td>\n",
       "      <td>9594</td>\n",
       "      <td>TTGTTTCACATCCAGG-1.11</td>\n",
       "      <td>151676</td>\n",
       "      <td>151676_TTGTTTCACATCCAGG-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2640</td>\n",
       "      <td>1526</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "      <td>WM</td>\n",
       "      <td>42</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47678</th>\n",
       "      <td>TTGTTTCATTAGTCTA-1</td>\n",
       "      <td>4684</td>\n",
       "      <td>9827</td>\n",
       "      <td>TTGTTTCATTAGTCTA-1.11</td>\n",
       "      <td>151676</td>\n",
       "      <td>151676_TTGTTTCATTAGTCTA-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2063</td>\n",
       "      <td>1279</td>\n",
       "      <td>9</td>\n",
       "      <td>True</td>\n",
       "      <td>WM</td>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47679</th>\n",
       "      <td>TTGTTTCCATACAACT-1</td>\n",
       "      <td>4491</td>\n",
       "      <td>8029</td>\n",
       "      <td>TTGTTTCCATACAACT-1.11</td>\n",
       "      <td>151676</td>\n",
       "      <td>151676_TTGTTTCCATACAACT-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>1031</td>\n",
       "      <td>748</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>L6</td>\n",
       "      <td>27</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47680</th>\n",
       "      <td>TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>6177</td>\n",
       "      <td>3489</td>\n",
       "      <td>TTGTTTGTGTAAATTC-1.10</td>\n",
       "      <td>151676</td>\n",
       "      <td>151676_TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2625</td>\n",
       "      <td>1392</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>L1</td>\n",
       "      <td>51</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>47681 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     spot     X     Y                  index  sample_id  \\\n",
       "0      AAACAACGAATAGTTC-1  3276  2514     AAACAACGAATAGTTC-1     151507   \n",
       "1      AAACAAGTATCTCCCA-1  9178  8520     AAACAAGTATCTCCCA-1     151507   \n",
       "2      AAACAATCTACTAGCA-1  5133  2878     AAACAATCTACTAGCA-1     151507   \n",
       "3      AAACACCAATAACTGC-1  3462  9581     AAACACCAATAACTGC-1     151507   \n",
       "4      AAACAGCTTTCAGAAG-1  2779  7663     AAACAGCTTTCAGAAG-1     151507   \n",
       "...                   ...   ...   ...                    ...        ...   \n",
       "47676  TTGTTGTGTGTCAAGA-1  7946  6378  TTGTTGTGTGTCAAGA-1.11     151676   \n",
       "47677  TTGTTTCACATCCAGG-1  5512  9594  TTGTTTCACATCCAGG-1.11     151676   \n",
       "47678  TTGTTTCATTAGTCTA-1  4684  9827  TTGTTTCATTAGTCTA-1.11     151676   \n",
       "47679  TTGTTTCCATACAACT-1  4491  8029  TTGTTTCCATACAACT-1.11     151676   \n",
       "47680  TTGTTTGTGTAAATTC-1  6177  3489  TTGTTTGTGTAAATTC-1.10     151676   \n",
       "\n",
       "                             key subject  replicate  Cluster  sum_umi  \\\n",
       "0      151507_AAACAACGAATAGTTC-1  Br5292          1        6      948   \n",
       "1      151507_AAACAAGTATCTCCCA-1  Br5292          1        3     4261   \n",
       "2      151507_AAACAATCTACTAGCA-1  Br5292          1        2     1969   \n",
       "3      151507_AAACACCAATAACTGC-1  Br5292          1        5     3368   \n",
       "4      151507_AAACAGCTTTCAGAAG-1  Br5292          1        1     2981   \n",
       "...                          ...     ...        ...      ...      ...   \n",
       "47676  151676_TTGTTGTGTGTCAAGA-1  Br8100          2        5     2880   \n",
       "47677  151676_TTGTTTCACATCCAGG-1  Br8100          2        2     2640   \n",
       "47678  151676_TTGTTTCATTAGTCTA-1  Br8100          2        2     2063   \n",
       "47679  151676_TTGTTTCCATACAACT-1  Br8100          2        7     1031   \n",
       "47680  151676_TTGTTTGTGTAAATTC-1  Br8100          2        1     2625   \n",
       "\n",
       "       sum_gene  cell_count  in_tissue spatialLIBD  array_col  array_row  \n",
       "0           727           0       True          L1         16          0  \n",
       "1          2170           3       True          L3        102         50  \n",
       "2          1093           2       True          L1         43          3  \n",
       "3          1896           5       True          WM         19         59  \n",
       "4          1620           3       True          L6          9         43  \n",
       "...         ...         ...        ...         ...        ...        ...  \n",
       "47676      1638           1       True          L6         77         31  \n",
       "47677      1526           6       True          WM         42         58  \n",
       "47678      1279           9       True          WM         30         60  \n",
       "47679       748           2       True          L6         27         45  \n",
       "47680      1392           0       True          L1         51          7  \n",
       "\n",
       "[47681 rows x 16 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# merge spot and st info -- merging based on index... no other specifying info in st:S, seems okay?\n",
    "spot_meta = st.join(spot.reset_index())\n",
    "spot_meta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([151507, 151508, 151509, 151510, 151669, 151670, 151671, 151672,\n",
       "       151673, 151674, 151675, 151676])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(spot_meta[['sample_id']].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_cell_layers(df):\n",
    "    \n",
    "    layer_idx = df[\"spatialLIBD\"].unique()\n",
    "    \n",
    "    fig, ax = plt.subplots(nrows = 1, ncols = 12, figsize = (50,12))\n",
    "    samples = df[\"sample_id\"].unique()\n",
    "    \n",
    "    for idx, sample in enumerate(samples):\n",
    "        cells_of_samples = df[df[\"sample_id\"] == sample]\n",
    "        for index in layer_idx:\n",
    "            cells_of_layer = cells_of_samples[cells_of_samples[\"spatialLIBD\"] == index]\n",
    "            ax[idx].scatter(-cells_of_layer[\"Y\"], cells_of_layer[\"X\"], label = index)\n",
    "    plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 3600x864 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_cell_layers(spot_meta) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>Unnamed: 0</th>\n",
       "      <th>ID</th>\n",
       "      <th>gene_biotype</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>propNucleiExprs</th>\n",
       "      <th>propExprsIn.Astro</th>\n",
       "      <th>propExprsIn.Excit_A</th>\n",
       "      <th>propExprsIn.Excit_B</th>\n",
       "      <th>propExprsIn.Excit_C</th>\n",
       "      <th>propExprsIn.Excit_D</th>\n",
       "      <th>...</th>\n",
       "      <th>propExprsIn.Inhib_C</th>\n",
       "      <th>propExprsIn.Inhib_D</th>\n",
       "      <th>propExprsIn.Inhib_E</th>\n",
       "      <th>propExprsIn.Inhib_F</th>\n",
       "      <th>propExprsIn.Macrophage</th>\n",
       "      <th>propExprsIn.Micro</th>\n",
       "      <th>propExprsIn.Mural</th>\n",
       "      <th>propExprsIn.Oligo</th>\n",
       "      <th>propExprsIn.OPC</th>\n",
       "      <th>propExprsIn.Tcell</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MIR1302-2HG</td>\n",
       "      <td>ENSG00000243485</td>\n",
       "      <td>lincRNA</td>\n",
       "      <td>MIR1302-2HG</td>\n",
       "      <td>0.000179</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001294</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002740</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FAM138A</td>\n",
       "      <td>ENSG00000237613</td>\n",
       "      <td>lincRNA</td>\n",
       "      <td>FAM138A</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OR4F5</td>\n",
       "      <td>ENSG00000186092</td>\n",
       "      <td>protein_coding</td>\n",
       "      <td>OR4F5</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AL627309.1</td>\n",
       "      <td>ENSG00000238009</td>\n",
       "      <td>lincRNA</td>\n",
       "      <td>AL627309.1</td>\n",
       "      <td>0.095876</td>\n",
       "      <td>0.033248</td>\n",
       "      <td>0.240076</td>\n",
       "      <td>0.124191</td>\n",
       "      <td>0.282443</td>\n",
       "      <td>0.212121</td>\n",
       "      <td>...</td>\n",
       "      <td>0.158904</td>\n",
       "      <td>0.196126</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.046392</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04473</td>\n",
       "      <td>0.031469</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AL627309.3</td>\n",
       "      <td>ENSG00000239945</td>\n",
       "      <td>lincRNA</td>\n",
       "      <td>AL627309.3</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0               ID    gene_biotype       Symbol  propNucleiExprs  \\\n",
       "0  MIR1302-2HG  ENSG00000243485         lincRNA  MIR1302-2HG         0.000179   \n",
       "1      FAM138A  ENSG00000237613         lincRNA      FAM138A         0.000000   \n",
       "2        OR4F5  ENSG00000186092  protein_coding        OR4F5         0.000000   \n",
       "3   AL627309.1  ENSG00000238009         lincRNA   AL627309.1         0.095876   \n",
       "4   AL627309.3  ENSG00000239945         lincRNA   AL627309.3         0.000000   \n",
       "\n",
       "   propExprsIn.Astro  propExprsIn.Excit_A  propExprsIn.Excit_B  \\\n",
       "0           0.000000             0.000000             0.001294   \n",
       "1           0.000000             0.000000             0.000000   \n",
       "2           0.000000             0.000000             0.000000   \n",
       "3           0.033248             0.240076             0.124191   \n",
       "4           0.000000             0.000000             0.000000   \n",
       "\n",
       "   propExprsIn.Excit_C  propExprsIn.Excit_D  ...  propExprsIn.Inhib_C  \\\n",
       "0             0.000000             0.000000  ...             0.002740   \n",
       "1             0.000000             0.000000  ...             0.000000   \n",
       "2             0.000000             0.000000  ...             0.000000   \n",
       "3             0.282443             0.212121  ...             0.158904   \n",
       "4             0.000000             0.000000  ...             0.000000   \n",
       "\n",
       "   propExprsIn.Inhib_D  propExprsIn.Inhib_E  propExprsIn.Inhib_F  \\\n",
       "0             0.000000             0.000000                0.000   \n",
       "1             0.000000             0.000000                0.000   \n",
       "2             0.000000             0.000000                0.000   \n",
       "3             0.196126             0.142857                0.125   \n",
       "4             0.000000             0.000000                0.000   \n",
       "\n",
       "   propExprsIn.Macrophage  propExprsIn.Micro  propExprsIn.Mural  \\\n",
       "0                     0.0           0.000000                0.0   \n",
       "1                     0.0           0.000000                0.0   \n",
       "2                     0.0           0.000000                0.0   \n",
       "3                     0.0           0.046392                0.0   \n",
       "4                     0.0           0.000000                0.0   \n",
       "\n",
       "   propExprsIn.Oligo  propExprsIn.OPC  propExprsIn.Tcell  \n",
       "0            0.00000         0.000000                0.0  \n",
       "1            0.00000         0.000000                0.0  \n",
       "2            0.00000         0.000000                0.0  \n",
       "3            0.04473         0.031469                0.0  \n",
       "4            0.00000         0.000000                0.0  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cell_type.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(33538, 21)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cell_type.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "cell_type = cell_type.drop(['Unnamed: 0', 'gene_biotype', \"Symbol\"], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>spot</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ENSG00000187608</td>\n",
       "      <td>AAACAACGAATAGTTC-1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ENSG00000132906</td>\n",
       "      <td>AAACAACGAATAGTTC-1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ENSG00000116786</td>\n",
       "      <td>AAACAACGAATAGTTC-1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ENSG00000162545</td>\n",
       "      <td>AAACAACGAATAGTTC-1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ENSG00000142669</td>\n",
       "      <td>AAACAACGAATAGTTC-1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82659003</th>\n",
       "      <td>ENSG00000212907</td>\n",
       "      <td>TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82659004</th>\n",
       "      <td>ENSG00000198886</td>\n",
       "      <td>TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82659005</th>\n",
       "      <td>ENSG00000198786</td>\n",
       "      <td>TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82659006</th>\n",
       "      <td>ENSG00000198695</td>\n",
       "      <td>TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82659007</th>\n",
       "      <td>ENSG00000198727</td>\n",
       "      <td>TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>82659007 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     gene                spot  count\n",
       "1         ENSG00000187608  AAACAACGAATAGTTC-1      1\n",
       "2         ENSG00000132906  AAACAACGAATAGTTC-1      1\n",
       "3         ENSG00000116786  AAACAACGAATAGTTC-1      1\n",
       "4         ENSG00000162545  AAACAACGAATAGTTC-1      1\n",
       "5         ENSG00000142669  AAACAACGAATAGTTC-1      2\n",
       "...                   ...                 ...    ...\n",
       "82659003  ENSG00000212907  TTGTTTGTGTAAATTC-1      2\n",
       "82659004  ENSG00000198886  TTGTTTGTGTAAATTC-1     72\n",
       "82659005  ENSG00000198786  TTGTTTGTGTAAATTC-1      7\n",
       "82659006  ENSG00000198695  TTGTTTGTGTAAATTC-1      1\n",
       "82659007  ENSG00000198727  TTGTTTGTGTAAATTC-1     51\n",
       "\n",
       "[82659007 rows x 3 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4941"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(np.unique(csr[['spot']].values)) # problem: data only for sample_ID 151673 ! explore with just this for now... need to get rest of data once i'm back in mtl to extract on pc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>gene</th>\n",
       "      <th>spot</th>\n",
       "      <th>ENSG00000000003</th>\n",
       "      <th>ENSG00000000005</th>\n",
       "      <th>ENSG00000000419</th>\n",
       "      <th>ENSG00000000457</th>\n",
       "      <th>ENSG00000000460</th>\n",
       "      <th>ENSG00000000938</th>\n",
       "      <th>ENSG00000000971</th>\n",
       "      <th>ENSG00000001036</th>\n",
       "      <th>ENSG00000001084</th>\n",
       "      <th>...</th>\n",
       "      <th>ENSG00000285444</th>\n",
       "      <th>ENSG00000285447</th>\n",
       "      <th>ENSG00000285454</th>\n",
       "      <th>ENSG00000285458</th>\n",
       "      <th>ENSG00000285473</th>\n",
       "      <th>ENSG00000285476</th>\n",
       "      <th>ENSG00000285480</th>\n",
       "      <th>ENSG00000285486</th>\n",
       "      <th>ENSG00000285492</th>\n",
       "      <th>ENSG00000285509</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAACAACGAATAGTTC-1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AAACAAGTATCTCCCA-1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAACAATCTACTAGCA-1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAACACCAATAACTGC-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AAACAGAGCGACTCCT-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25616 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "gene                spot  ENSG00000000003  ENSG00000000005  ENSG00000000419  \\\n",
       "0     AAACAACGAATAGTTC-1              0.0              0.0              0.0   \n",
       "1     AAACAAGTATCTCCCA-1              0.0              0.0              1.0   \n",
       "2     AAACAATCTACTAGCA-1              0.0              0.0              1.0   \n",
       "3     AAACACCAATAACTGC-1              1.0              0.0              1.8   \n",
       "4     AAACAGAGCGACTCCT-1              1.0              0.0              1.0   \n",
       "\n",
       "gene  ENSG00000000457  ENSG00000000460  ENSG00000000938  ENSG00000000971  \\\n",
       "0                 0.0              0.0              0.0              0.0   \n",
       "1                 0.0              0.0              0.0              1.0   \n",
       "2                 0.0              0.0              0.0              0.0   \n",
       "3                 1.0              0.0              0.0              0.0   \n",
       "4                 1.0              0.0              0.0              0.0   \n",
       "\n",
       "gene  ENSG00000001036  ENSG00000001084  ...  ENSG00000285444  ENSG00000285447  \\\n",
       "0                 0.0              0.0  ...              0.0              0.0   \n",
       "1                 1.0              1.0  ...              0.0              0.0   \n",
       "2                 0.0              0.0  ...              0.0              0.0   \n",
       "3                 1.0              2.0  ...              0.0              1.0   \n",
       "4                 0.0              0.0  ...              0.0              1.0   \n",
       "\n",
       "gene  ENSG00000285454  ENSG00000285458  ENSG00000285473  ENSG00000285476  \\\n",
       "0                 0.0              0.0              0.0              0.0   \n",
       "1                 0.0              0.0              0.0              0.0   \n",
       "2                 0.0              0.0              0.0              0.0   \n",
       "3                 0.0              0.0              0.0              0.0   \n",
       "4                 0.0              0.0              0.0              0.0   \n",
       "\n",
       "gene  ENSG00000285480  ENSG00000285486  ENSG00000285492  ENSG00000285509  \n",
       "0                 0.0              0.0              0.0              0.0  \n",
       "1                 0.0              0.0              0.0              0.0  \n",
       "2                 0.0              0.0              0.0              0.0  \n",
       "3                 0.0              0.0              0.0              0.0  \n",
       "4                 0.0              0.0              0.0              0.0  \n",
       "\n",
       "[5 rows x 25616 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wide = csr.pivot_table(index = \"spot\", columns = \"gene\", values = \"count\")\n",
    "wide = wide.fillna(0)\n",
    "counts_df = wide.reset_index()\n",
    "counts_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4941, 25616)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sample_id    int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spot_meta[['sample_id']].dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>spot</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>index</th>\n",
       "      <th>sample_id</th>\n",
       "      <th>key</th>\n",
       "      <th>subject</th>\n",
       "      <th>replicate</th>\n",
       "      <th>Cluster</th>\n",
       "      <th>sum_umi</th>\n",
       "      <th>sum_gene</th>\n",
       "      <th>cell_count</th>\n",
       "      <th>in_tissue</th>\n",
       "      <th>spatialLIBD</th>\n",
       "      <th>array_col</th>\n",
       "      <th>array_row</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>33317</th>\n",
       "      <td>AAACAAGTATCTCCCA-1</td>\n",
       "      <td>9791</td>\n",
       "      <td>8468</td>\n",
       "      <td>AAACAAGTATCTCCCA-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_AAACAAGTATCTCCCA-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>8458</td>\n",
       "      <td>3586</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "      <td>L3</td>\n",
       "      <td>102</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33318</th>\n",
       "      <td>AAACAATCTACTAGCA-1</td>\n",
       "      <td>5769</td>\n",
       "      <td>2807</td>\n",
       "      <td>AAACAATCTACTAGCA-1.3</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_AAACAATCTACTAGCA-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1667</td>\n",
       "      <td>1150</td>\n",
       "      <td>16</td>\n",
       "      <td>True</td>\n",
       "      <td>L1</td>\n",
       "      <td>43</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33319</th>\n",
       "      <td>AAACACCAATAACTGC-1</td>\n",
       "      <td>4068</td>\n",
       "      <td>9505</td>\n",
       "      <td>AAACACCAATAACTGC-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_AAACACCAATAACTGC-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3769</td>\n",
       "      <td>1960</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "      <td>WM</td>\n",
       "      <td>19</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33320</th>\n",
       "      <td>AAACAGAGCGACTCCT-1</td>\n",
       "      <td>9271</td>\n",
       "      <td>4151</td>\n",
       "      <td>AAACAGAGCGACTCCT-1.7</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_AAACAGAGCGACTCCT-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>5433</td>\n",
       "      <td>2424</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>L3</td>\n",
       "      <td>94</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33321</th>\n",
       "      <td>AAACAGCTTTCAGAAG-1</td>\n",
       "      <td>3393</td>\n",
       "      <td>7583</td>\n",
       "      <td>AAACAGCTTTCAGAAG-1.7</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_AAACAGCTTTCAGAAG-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4278</td>\n",
       "      <td>2264</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>L5</td>\n",
       "      <td>9</td>\n",
       "      <td>43</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36951</th>\n",
       "      <td>TTGTTTCACATCCAGG-1</td>\n",
       "      <td>5653</td>\n",
       "      <td>9396</td>\n",
       "      <td>TTGTTTCACATCCAGG-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_TTGTTTCACATCCAGG-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>4324</td>\n",
       "      <td>2170</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>WM</td>\n",
       "      <td>42</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36952</th>\n",
       "      <td>TTGTTTCATTAGTCTA-1</td>\n",
       "      <td>4825</td>\n",
       "      <td>9630</td>\n",
       "      <td>TTGTTTCATTAGTCTA-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_TTGTTTCATTAGTCTA-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>2761</td>\n",
       "      <td>1560</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>WM</td>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36953</th>\n",
       "      <td>TTGTTTCCATACAACT-1</td>\n",
       "      <td>4631</td>\n",
       "      <td>7831</td>\n",
       "      <td>TTGTTTCCATACAACT-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_TTGTTTCCATACAACT-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>2322</td>\n",
       "      <td>1343</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>L6</td>\n",
       "      <td>27</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36954</th>\n",
       "      <td>TTGTTTGTATTACACG-1</td>\n",
       "      <td>5571</td>\n",
       "      <td>11193</td>\n",
       "      <td>TTGTTTGTATTACACG-1.4</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_TTGTTTGTATTACACG-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>2331</td>\n",
       "      <td>1420</td>\n",
       "      <td>16</td>\n",
       "      <td>True</td>\n",
       "      <td>WM</td>\n",
       "      <td>41</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36955</th>\n",
       "      <td>TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>6317</td>\n",
       "      <td>3291</td>\n",
       "      <td>TTGTTTGTGTAAATTC-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>6281</td>\n",
       "      <td>2927</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "      <td>L2</td>\n",
       "      <td>51</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3639 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     spot     X      Y                 index  sample_id  \\\n",
       "33317  AAACAAGTATCTCCCA-1  9791   8468  AAACAAGTATCTCCCA-1.8     151673   \n",
       "33318  AAACAATCTACTAGCA-1  5769   2807  AAACAATCTACTAGCA-1.3     151673   \n",
       "33319  AAACACCAATAACTGC-1  4068   9505  AAACACCAATAACTGC-1.8     151673   \n",
       "33320  AAACAGAGCGACTCCT-1  9271   4151  AAACAGAGCGACTCCT-1.7     151673   \n",
       "33321  AAACAGCTTTCAGAAG-1  3393   7583  AAACAGCTTTCAGAAG-1.7     151673   \n",
       "...                   ...   ...    ...                   ...        ...   \n",
       "36951  TTGTTTCACATCCAGG-1  5653   9396  TTGTTTCACATCCAGG-1.8     151673   \n",
       "36952  TTGTTTCATTAGTCTA-1  4825   9630  TTGTTTCATTAGTCTA-1.8     151673   \n",
       "36953  TTGTTTCCATACAACT-1  4631   7831  TTGTTTCCATACAACT-1.8     151673   \n",
       "36954  TTGTTTGTATTACACG-1  5571  11193  TTGTTTGTATTACACG-1.4     151673   \n",
       "36955  TTGTTTGTGTAAATTC-1  6317   3291  TTGTTTGTGTAAATTC-1.8     151673   \n",
       "\n",
       "                             key subject  replicate  Cluster  sum_umi  \\\n",
       "33317  151673_AAACAAGTATCTCCCA-1  Br8100          1        7     8458   \n",
       "33318  151673_AAACAATCTACTAGCA-1  Br8100          1        4     1667   \n",
       "33319  151673_AAACACCAATAACTGC-1  Br8100          1        8     3769   \n",
       "33320  151673_AAACAGAGCGACTCCT-1  Br8100          1        6     5433   \n",
       "33321  151673_AAACAGCTTTCAGAAG-1  Br8100          1        3     4278   \n",
       "...                          ...     ...        ...      ...      ...   \n",
       "36951  151673_TTGTTTCACATCCAGG-1  Br8100          1        8     4324   \n",
       "36952  151673_TTGTTTCATTAGTCTA-1  Br8100          1        8     2761   \n",
       "36953  151673_TTGTTTCCATACAACT-1  Br8100          1        6     2322   \n",
       "36954  151673_TTGTTTGTATTACACG-1  Br8100          1        6     2331   \n",
       "36955  151673_TTGTTTGTGTAAATTC-1  Br8100          1        7     6281   \n",
       "\n",
       "       sum_gene  cell_count  in_tissue spatialLIBD  array_col  array_row  \n",
       "33317      3586           6       True          L3        102         50  \n",
       "33318      1150          16       True          L1         43          3  \n",
       "33319      1960           5       True          WM         19         59  \n",
       "33320      2424           2       True          L3         94         14  \n",
       "33321      2264           4       True          L5          9         43  \n",
       "...         ...         ...        ...         ...        ...        ...  \n",
       "36951      2170           3       True          WM         42         58  \n",
       "36952      1560           4       True          WM         30         60  \n",
       "36953      1343           3       True          L6         27         45  \n",
       "36954      1420          16       True          WM         41         73  \n",
       "36955      2927           5       True          L2         51          7  \n",
       "\n",
       "[3639 rows x 16 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# working with sampleID 151673 only, for now\n",
    "dlpfc = spot_meta[spot_meta['sample_id'] == 151673]\n",
    "dlpfc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>spot</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>index</th>\n",
       "      <th>sample_id</th>\n",
       "      <th>key</th>\n",
       "      <th>subject</th>\n",
       "      <th>replicate</th>\n",
       "      <th>Cluster</th>\n",
       "      <th>sum_umi</th>\n",
       "      <th>...</th>\n",
       "      <th>ENSG00000285444</th>\n",
       "      <th>ENSG00000285447</th>\n",
       "      <th>ENSG00000285454</th>\n",
       "      <th>ENSG00000285458</th>\n",
       "      <th>ENSG00000285473</th>\n",
       "      <th>ENSG00000285476</th>\n",
       "      <th>ENSG00000285480</th>\n",
       "      <th>ENSG00000285486</th>\n",
       "      <th>ENSG00000285492</th>\n",
       "      <th>ENSG00000285509</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAACAAGTATCTCCCA-1</td>\n",
       "      <td>9791</td>\n",
       "      <td>8468</td>\n",
       "      <td>AAACAAGTATCTCCCA-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_AAACAAGTATCTCCCA-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>8458</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AAACAATCTACTAGCA-1</td>\n",
       "      <td>5769</td>\n",
       "      <td>2807</td>\n",
       "      <td>AAACAATCTACTAGCA-1.3</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_AAACAATCTACTAGCA-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1667</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAACACCAATAACTGC-1</td>\n",
       "      <td>4068</td>\n",
       "      <td>9505</td>\n",
       "      <td>AAACACCAATAACTGC-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_AAACACCAATAACTGC-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3769</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAACAGAGCGACTCCT-1</td>\n",
       "      <td>9271</td>\n",
       "      <td>4151</td>\n",
       "      <td>AAACAGAGCGACTCCT-1.7</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_AAACAGAGCGACTCCT-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>5433</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AAACAGCTTTCAGAAG-1</td>\n",
       "      <td>3393</td>\n",
       "      <td>7583</td>\n",
       "      <td>AAACAGCTTTCAGAAG-1.7</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_AAACAGCTTTCAGAAG-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4278</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>3634</th>\n",
       "      <td>TTGTTTCACATCCAGG-1</td>\n",
       "      <td>5653</td>\n",
       "      <td>9396</td>\n",
       "      <td>TTGTTTCACATCCAGG-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_TTGTTTCACATCCAGG-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>4324</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3635</th>\n",
       "      <td>TTGTTTCATTAGTCTA-1</td>\n",
       "      <td>4825</td>\n",
       "      <td>9630</td>\n",
       "      <td>TTGTTTCATTAGTCTA-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_TTGTTTCATTAGTCTA-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>2761</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3636</th>\n",
       "      <td>TTGTTTCCATACAACT-1</td>\n",
       "      <td>4631</td>\n",
       "      <td>7831</td>\n",
       "      <td>TTGTTTCCATACAACT-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_TTGTTTCCATACAACT-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>2322</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3637</th>\n",
       "      <td>TTGTTTGTATTACACG-1</td>\n",
       "      <td>5571</td>\n",
       "      <td>11193</td>\n",
       "      <td>TTGTTTGTATTACACG-1.4</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_TTGTTTGTATTACACG-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>2331</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3638</th>\n",
       "      <td>TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>6317</td>\n",
       "      <td>3291</td>\n",
       "      <td>TTGTTTGTGTAAATTC-1.8</td>\n",
       "      <td>151673</td>\n",
       "      <td>151673_TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>Br8100</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>6281</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3639 rows × 25631 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    spot     X      Y                 index  sample_id  \\\n",
       "0     AAACAAGTATCTCCCA-1  9791   8468  AAACAAGTATCTCCCA-1.8     151673   \n",
       "1     AAACAATCTACTAGCA-1  5769   2807  AAACAATCTACTAGCA-1.3     151673   \n",
       "2     AAACACCAATAACTGC-1  4068   9505  AAACACCAATAACTGC-1.8     151673   \n",
       "3     AAACAGAGCGACTCCT-1  9271   4151  AAACAGAGCGACTCCT-1.7     151673   \n",
       "4     AAACAGCTTTCAGAAG-1  3393   7583  AAACAGCTTTCAGAAG-1.7     151673   \n",
       "...                  ...   ...    ...                   ...        ...   \n",
       "3634  TTGTTTCACATCCAGG-1  5653   9396  TTGTTTCACATCCAGG-1.8     151673   \n",
       "3635  TTGTTTCATTAGTCTA-1  4825   9630  TTGTTTCATTAGTCTA-1.8     151673   \n",
       "3636  TTGTTTCCATACAACT-1  4631   7831  TTGTTTCCATACAACT-1.8     151673   \n",
       "3637  TTGTTTGTATTACACG-1  5571  11193  TTGTTTGTATTACACG-1.4     151673   \n",
       "3638  TTGTTTGTGTAAATTC-1  6317   3291  TTGTTTGTGTAAATTC-1.8     151673   \n",
       "\n",
       "                            key subject  replicate  Cluster  sum_umi  ...  \\\n",
       "0     151673_AAACAAGTATCTCCCA-1  Br8100          1        7     8458  ...   \n",
       "1     151673_AAACAATCTACTAGCA-1  Br8100          1        4     1667  ...   \n",
       "2     151673_AAACACCAATAACTGC-1  Br8100          1        8     3769  ...   \n",
       "3     151673_AAACAGAGCGACTCCT-1  Br8100          1        6     5433  ...   \n",
       "4     151673_AAACAGCTTTCAGAAG-1  Br8100          1        3     4278  ...   \n",
       "...                         ...     ...        ...      ...      ...  ...   \n",
       "3634  151673_TTGTTTCACATCCAGG-1  Br8100          1        8     4324  ...   \n",
       "3635  151673_TTGTTTCATTAGTCTA-1  Br8100          1        8     2761  ...   \n",
       "3636  151673_TTGTTTCCATACAACT-1  Br8100          1        6     2322  ...   \n",
       "3637  151673_TTGTTTGTATTACACG-1  Br8100          1        6     2331  ...   \n",
       "3638  151673_TTGTTTGTGTAAATTC-1  Br8100          1        7     6281  ...   \n",
       "\n",
       "      ENSG00000285444  ENSG00000285447  ENSG00000285454 ENSG00000285458  \\\n",
       "0                 0.0              0.0              0.0             0.0   \n",
       "1                 0.0              0.0              0.0             0.0   \n",
       "2                 0.0              1.0              0.0             0.0   \n",
       "3                 0.0              1.0              0.0             0.0   \n",
       "4                 0.0              0.0              0.0             0.0   \n",
       "...               ...              ...              ...             ...   \n",
       "3634              0.0              0.0              0.0             0.0   \n",
       "3635              0.0              0.0              0.0             0.0   \n",
       "3636              0.0              0.0              0.0             0.0   \n",
       "3637              0.0              0.0              0.0             0.0   \n",
       "3638              0.0              1.0              0.0             0.0   \n",
       "\n",
       "      ENSG00000285473  ENSG00000285476  ENSG00000285480  ENSG00000285486  \\\n",
       "0                 0.0              0.0              0.0              0.0   \n",
       "1                 0.0              0.0              0.0              0.0   \n",
       "2                 0.0              0.0              0.0              0.0   \n",
       "3                 0.0              0.0              0.0              0.0   \n",
       "4                 0.0              0.0              0.0              0.0   \n",
       "...               ...              ...              ...              ...   \n",
       "3634              0.0              1.0              0.0              0.0   \n",
       "3635              0.0              0.0              0.0              0.0   \n",
       "3636              0.0              0.0              0.0              0.0   \n",
       "3637              0.0              0.0              0.0              0.0   \n",
       "3638              0.0              2.0              0.0              0.0   \n",
       "\n",
       "      ENSG00000285492  ENSG00000285509  \n",
       "0                 0.0              0.0  \n",
       "1                 0.0              0.0  \n",
       "2                 0.0              0.0  \n",
       "3                 0.0              0.0  \n",
       "4                 0.0              0.0  \n",
       "...               ...              ...  \n",
       "3634              0.0              0.0  \n",
       "3635              0.0              0.0  \n",
       "3636              0.0              0.0  \n",
       "3637              0.0              0.0  \n",
       "3638              0.0              0.0  \n",
       "\n",
       "[3639 rows x 25631 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp = dlpfc.merge(counts_df, left_on='spot', right_on='spot')\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['spot', 'X', 'Y', 'index', 'sample_id', 'key', 'subject', 'replicate',\n",
       "       'Cluster', 'sum_umi',\n",
       "       ...\n",
       "       'ENSG00000285444', 'ENSG00000285447', 'ENSG00000285454',\n",
       "       'ENSG00000285458', 'ENSG00000285473', 'ENSG00000285476',\n",
       "       'ENSG00000285480', 'ENSG00000285486', 'ENSG00000285492',\n",
       "       'ENSG00000285509'],\n",
       "      dtype='object', length=25631)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>spot</th>\n",
       "      <th>ENSG00000000003</th>\n",
       "      <th>ENSG00000000005</th>\n",
       "      <th>ENSG00000000419</th>\n",
       "      <th>ENSG00000000457</th>\n",
       "      <th>ENSG00000000460</th>\n",
       "      <th>ENSG00000000938</th>\n",
       "      <th>ENSG00000000971</th>\n",
       "      <th>ENSG00000001036</th>\n",
       "      <th>ENSG00000001084</th>\n",
       "      <th>...</th>\n",
       "      <th>ENSG00000285444</th>\n",
       "      <th>ENSG00000285447</th>\n",
       "      <th>ENSG00000285454</th>\n",
       "      <th>ENSG00000285458</th>\n",
       "      <th>ENSG00000285473</th>\n",
       "      <th>ENSG00000285476</th>\n",
       "      <th>ENSG00000285480</th>\n",
       "      <th>ENSG00000285486</th>\n",
       "      <th>ENSG00000285492</th>\n",
       "      <th>ENSG00000285509</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAACAAGTATCTCCCA-1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AAACAATCTACTAGCA-1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAACACCAATAACTGC-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAACAGAGCGACTCCT-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AAACAGCTTTCAGAAG-1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>3634</th>\n",
       "      <td>TTGTTTCACATCCAGG-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3635</th>\n",
       "      <td>TTGTTTCATTAGTCTA-1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3636</th>\n",
       "      <td>TTGTTTCCATACAACT-1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3637</th>\n",
       "      <td>TTGTTTGTATTACACG-1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3638</th>\n",
       "      <td>TTGTTTGTGTAAATTC-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3639 rows × 25616 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    spot  ENSG00000000003  ENSG00000000005  ENSG00000000419  \\\n",
       "0     AAACAAGTATCTCCCA-1              0.0              0.0              1.0   \n",
       "1     AAACAATCTACTAGCA-1              0.0              0.0              1.0   \n",
       "2     AAACACCAATAACTGC-1              1.0              0.0              1.8   \n",
       "3     AAACAGAGCGACTCCT-1              1.0              0.0              1.0   \n",
       "4     AAACAGCTTTCAGAAG-1              0.0              0.0              0.0   \n",
       "...                  ...              ...              ...              ...   \n",
       "3634  TTGTTTCACATCCAGG-1              1.0              0.0              0.0   \n",
       "3635  TTGTTTCATTAGTCTA-1              0.0              0.0              0.0   \n",
       "3636  TTGTTTCCATACAACT-1              0.0              0.0              1.0   \n",
       "3637  TTGTTTGTATTACACG-1              0.0              0.0              0.0   \n",
       "3638  TTGTTTGTGTAAATTC-1              1.0              0.0              0.0   \n",
       "\n",
       "      ENSG00000000457  ENSG00000000460  ENSG00000000938  ENSG00000000971  \\\n",
       "0                 0.0              0.0              0.0              1.0   \n",
       "1                 0.0              0.0              0.0              0.0   \n",
       "2                 1.0              0.0              0.0              0.0   \n",
       "3                 1.0              0.0              0.0              0.0   \n",
       "4                 0.0              0.0              0.0              0.0   \n",
       "...               ...              ...              ...              ...   \n",
       "3634              0.0              0.0              0.0              0.0   \n",
       "3635              0.0              0.0              0.0              0.0   \n",
       "3636              0.0              0.0              0.0              0.0   \n",
       "3637              0.0              0.0              0.0              0.0   \n",
       "3638              0.0              0.0              0.0              0.0   \n",
       "\n",
       "      ENSG00000001036  ENSG00000001084  ...  ENSG00000285444  ENSG00000285447  \\\n",
       "0                 1.0              1.0  ...              0.0              0.0   \n",
       "1                 0.0              0.0  ...              0.0              0.0   \n",
       "2                 1.0              2.0  ...              0.0              1.0   \n",
       "3                 0.0              0.0  ...              0.0              1.0   \n",
       "4                 0.0              1.0  ...              0.0              0.0   \n",
       "...               ...              ...  ...              ...              ...   \n",
       "3634              0.0              0.0  ...              0.0              0.0   \n",
       "3635              1.0              1.0  ...              0.0              0.0   \n",
       "3636              0.0              1.0  ...              0.0              0.0   \n",
       "3637              0.0              0.0  ...              0.0              0.0   \n",
       "3638              0.0              1.0  ...              0.0              1.0   \n",
       "\n",
       "      ENSG00000285454  ENSG00000285458  ENSG00000285473  ENSG00000285476  \\\n",
       "0                 0.0              0.0              0.0              0.0   \n",
       "1                 0.0              0.0              0.0              0.0   \n",
       "2                 0.0              0.0              0.0              0.0   \n",
       "3                 0.0              0.0              0.0              0.0   \n",
       "4                 0.0              0.0              0.0              0.0   \n",
       "...               ...              ...              ...              ...   \n",
       "3634              0.0              0.0              0.0              1.0   \n",
       "3635              0.0              0.0              0.0              0.0   \n",
       "3636              0.0              0.0              0.0              0.0   \n",
       "3637              0.0              0.0              0.0              0.0   \n",
       "3638              0.0              0.0              0.0              2.0   \n",
       "\n",
       "      ENSG00000285480  ENSG00000285486  ENSG00000285492  ENSG00000285509  \n",
       "0                 0.0              0.0              0.0              0.0  \n",
       "1                 0.0              0.0              0.0              0.0  \n",
       "2                 0.0              0.0              0.0              0.0  \n",
       "3                 0.0              0.0              0.0              0.0  \n",
       "4                 0.0              0.0              0.0              0.0  \n",
       "...               ...              ...              ...              ...  \n",
       "3634              0.0              0.0              0.0              0.0  \n",
       "3635              0.0              0.0              0.0              0.0  \n",
       "3636              0.0              0.0              0.0              0.0  \n",
       "3637              0.0              0.0              0.0              0.0  \n",
       "3638              0.0              0.0              0.0              0.0  \n",
       "\n",
       "[3639 rows x 25616 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp = temp.drop(['index', 'X', 'Y', 'spatialLIBD', 'sample_id', 'key', 'subject', 'replicate', 'Cluster', 'sum_umi', 'sum_gene', 'cell_count', 'array_col', 'array_row', 'in_tissue'], axis=1)\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>ID</th>\n",
       "      <th>propNucleiExprs</th>\n",
       "      <th>propExprsIn.Astro</th>\n",
       "      <th>propExprsIn.Excit_A</th>\n",
       "      <th>propExprsIn.Excit_B</th>\n",
       "      <th>propExprsIn.Excit_C</th>\n",
       "      <th>propExprsIn.Excit_D</th>\n",
       "      <th>propExprsIn.Excit_E</th>\n",
       "      <th>propExprsIn.Excit_F</th>\n",
       "      <th>propExprsIn.Inhib_A</th>\n",
       "      <th>...</th>\n",
       "      <th>propExprsIn.Inhib_C</th>\n",
       "      <th>propExprsIn.Inhib_D</th>\n",
       "      <th>propExprsIn.Inhib_E</th>\n",
       "      <th>propExprsIn.Inhib_F</th>\n",
       "      <th>propExprsIn.Macrophage</th>\n",
       "      <th>propExprsIn.Micro</th>\n",
       "      <th>propExprsIn.Mural</th>\n",
       "      <th>propExprsIn.Oligo</th>\n",
       "      <th>propExprsIn.OPC</th>\n",
       "      <th>propExprsIn.Tcell</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ENSG00000243485</td>\n",
       "      <td>0.000179</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001294</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>0.002740</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ENSG00000237613</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ENSG00000186092</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ENSG00000238009</td>\n",
       "      <td>0.095876</td>\n",
       "      <td>0.033248</td>\n",
       "      <td>0.240076</td>\n",
       "      <td>0.124191</td>\n",
       "      <td>0.282443</td>\n",
       "      <td>0.212121</td>\n",
       "      <td>0.320856</td>\n",
       "      <td>0.288066</td>\n",
       "      <td>0.111111</td>\n",
       "      <td>...</td>\n",
       "      <td>0.158904</td>\n",
       "      <td>0.196126</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.046392</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04473</td>\n",
       "      <td>0.031469</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ENSG00000239945</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</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>33533</th>\n",
       "      <td>ENSG00000277856</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33534</th>\n",
       "      <td>ENSG00000275063</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33535</th>\n",
       "      <td>ENSG00000271254</td>\n",
       "      <td>0.066149</td>\n",
       "      <td>0.051151</td>\n",
       "      <td>0.086957</td>\n",
       "      <td>0.082794</td>\n",
       "      <td>0.131679</td>\n",
       "      <td>0.045455</td>\n",
       "      <td>0.139037</td>\n",
       "      <td>0.135802</td>\n",
       "      <td>0.099099</td>\n",
       "      <td>...</td>\n",
       "      <td>0.115068</td>\n",
       "      <td>0.181598</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.033505</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.03758</td>\n",
       "      <td>0.064685</td>\n",
       "      <td>0.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33536</th>\n",
       "      <td>ENSG00000277475</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33537</th>\n",
       "      <td>ENSG00000268674</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>33538 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    ID  propNucleiExprs  propExprsIn.Astro  \\\n",
       "0      ENSG00000243485         0.000179           0.000000   \n",
       "1      ENSG00000237613         0.000000           0.000000   \n",
       "2      ENSG00000186092         0.000000           0.000000   \n",
       "3      ENSG00000238009         0.095876           0.033248   \n",
       "4      ENSG00000239945         0.000000           0.000000   \n",
       "...                ...              ...                ...   \n",
       "33533  ENSG00000277856         0.000000           0.000000   \n",
       "33534  ENSG00000275063         0.000000           0.000000   \n",
       "33535  ENSG00000271254         0.066149           0.051151   \n",
       "33536  ENSG00000277475         0.000000           0.000000   \n",
       "33537  ENSG00000268674         0.000000           0.000000   \n",
       "\n",
       "       propExprsIn.Excit_A  propExprsIn.Excit_B  propExprsIn.Excit_C  \\\n",
       "0                 0.000000             0.001294             0.000000   \n",
       "1                 0.000000             0.000000             0.000000   \n",
       "2                 0.000000             0.000000             0.000000   \n",
       "3                 0.240076             0.124191             0.282443   \n",
       "4                 0.000000             0.000000             0.000000   \n",
       "...                    ...                  ...                  ...   \n",
       "33533             0.000000             0.000000             0.000000   \n",
       "33534             0.000000             0.000000             0.000000   \n",
       "33535             0.086957             0.082794             0.131679   \n",
       "33536             0.000000             0.000000             0.000000   \n",
       "33537             0.000000             0.000000             0.000000   \n",
       "\n",
       "       propExprsIn.Excit_D  propExprsIn.Excit_E  propExprsIn.Excit_F  \\\n",
       "0                 0.000000             0.000000             0.000000   \n",
       "1                 0.000000             0.000000             0.000000   \n",
       "2                 0.000000             0.000000             0.000000   \n",
       "3                 0.212121             0.320856             0.288066   \n",
       "4                 0.000000             0.000000             0.000000   \n",
       "...                    ...                  ...                  ...   \n",
       "33533             0.000000             0.000000             0.000000   \n",
       "33534             0.000000             0.000000             0.000000   \n",
       "33535             0.045455             0.139037             0.135802   \n",
       "33536             0.000000             0.000000             0.000000   \n",
       "33537             0.000000             0.000000             0.000000   \n",
       "\n",
       "       propExprsIn.Inhib_A  ...  propExprsIn.Inhib_C  propExprsIn.Inhib_D  \\\n",
       "0                 0.000000  ...             0.002740             0.000000   \n",
       "1                 0.000000  ...             0.000000             0.000000   \n",
       "2                 0.000000  ...             0.000000             0.000000   \n",
       "3                 0.111111  ...             0.158904             0.196126   \n",
       "4                 0.000000  ...             0.000000             0.000000   \n",
       "...                    ...  ...                  ...                  ...   \n",
       "33533             0.000000  ...             0.000000             0.000000   \n",
       "33534             0.000000  ...             0.000000             0.000000   \n",
       "33535             0.099099  ...             0.115068             0.181598   \n",
       "33536             0.000000  ...             0.000000             0.000000   \n",
       "33537             0.000000  ...             0.000000             0.000000   \n",
       "\n",
       "       propExprsIn.Inhib_E  propExprsIn.Inhib_F  propExprsIn.Macrophage  \\\n",
       "0                 0.000000                0.000                     0.0   \n",
       "1                 0.000000                0.000                     0.0   \n",
       "2                 0.000000                0.000                     0.0   \n",
       "3                 0.142857                0.125                     0.0   \n",
       "4                 0.000000                0.000                     0.0   \n",
       "...                    ...                  ...                     ...   \n",
       "33533             0.000000                0.000                     0.0   \n",
       "33534             0.000000                0.000                     0.0   \n",
       "33535             0.000000                0.125                     0.0   \n",
       "33536             0.000000                0.000                     0.0   \n",
       "33537             0.000000                0.000                     0.0   \n",
       "\n",
       "       propExprsIn.Micro  propExprsIn.Mural  propExprsIn.Oligo  \\\n",
       "0               0.000000                0.0            0.00000   \n",
       "1               0.000000                0.0            0.00000   \n",
       "2               0.000000                0.0            0.00000   \n",
       "3               0.046392                0.0            0.04473   \n",
       "4               0.000000                0.0            0.00000   \n",
       "...                  ...                ...                ...   \n",
       "33533           0.000000                0.0            0.00000   \n",
       "33534           0.000000                0.0            0.00000   \n",
       "33535           0.033505                0.0            0.03758   \n",
       "33536           0.000000                0.0            0.00000   \n",
       "33537           0.000000                0.0            0.00000   \n",
       "\n",
       "       propExprsIn.OPC  propExprsIn.Tcell  \n",
       "0             0.000000           0.000000  \n",
       "1             0.000000           0.000000  \n",
       "2             0.000000           0.000000  \n",
       "3             0.031469           0.000000  \n",
       "4             0.000000           0.000000  \n",
       "...                ...                ...  \n",
       "33533         0.000000           0.000000  \n",
       "33534         0.000000           0.000000  \n",
       "33535         0.064685           0.111111  \n",
       "33536         0.000000           0.000000  \n",
       "33537         0.000000           0.000000  \n",
       "\n",
       "[33538 rows x 21 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cell_type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>ID</th>\n",
       "      <th>propNucleiExprs</th>\n",
       "      <th>propExprsIn.Astro</th>\n",
       "      <th>propExprsIn.Excit_A</th>\n",
       "      <th>propExprsIn.Excit_B</th>\n",
       "      <th>propExprsIn.Excit_C</th>\n",
       "      <th>propExprsIn.Excit_D</th>\n",
       "      <th>propExprsIn.Excit_E</th>\n",
       "      <th>propExprsIn.Excit_F</th>\n",
       "      <th>propExprsIn.Inhib_A</th>\n",
       "      <th>...</th>\n",
       "      <th>propExprsIn.Inhib_C</th>\n",
       "      <th>propExprsIn.Inhib_D</th>\n",
       "      <th>propExprsIn.Inhib_E</th>\n",
       "      <th>propExprsIn.Inhib_F</th>\n",
       "      <th>propExprsIn.Macrophage</th>\n",
       "      <th>propExprsIn.Micro</th>\n",
       "      <th>propExprsIn.Mural</th>\n",
       "      <th>propExprsIn.Oligo</th>\n",
       "      <th>propExprsIn.OPC</th>\n",
       "      <th>propExprsIn.Tcell</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ENSG00000243485</td>\n",
       "      <td>0.000179</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001294</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>0.002740</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</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>3</th>\n",
       "      <td>ENSG00000238009</td>\n",
       "      <td>0.095876</td>\n",
       "      <td>0.033248</td>\n",
       "      <td>0.240076</td>\n",
       "      <td>0.124191</td>\n",
       "      <td>0.282443</td>\n",
       "      <td>0.212121</td>\n",
       "      <td>0.320856</td>\n",
       "      <td>0.288066</td>\n",
       "      <td>0.111111</td>\n",
       "      <td>...</td>\n",
       "      <td>0.158904</td>\n",
       "      <td>0.196126</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.046392</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.044730</td>\n",
       "      <td>0.031469</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>ENSG00000229905</td>\n",
       "      <td>0.000446</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.007576</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002740</td>\n",
       "      <td>0.002421</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000183</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>ENSG00000237491</td>\n",
       "      <td>0.336011</td>\n",
       "      <td>0.116368</td>\n",
       "      <td>0.799622</td>\n",
       "      <td>0.667529</td>\n",
       "      <td>0.830153</td>\n",
       "      <td>0.840909</td>\n",
       "      <td>0.828877</td>\n",
       "      <td>0.757202</td>\n",
       "      <td>0.450450</td>\n",
       "      <td>...</td>\n",
       "      <td>0.545205</td>\n",
       "      <td>0.554479</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>0.750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.139175</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.155454</td>\n",
       "      <td>0.234266</td>\n",
       "      <td>0.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ENSG00000177757</td>\n",
       "      <td>0.001250</td>\n",
       "      <td>0.001279</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003881</td>\n",
       "      <td>0.001908</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004115</td>\n",
       "      <td>0.003003</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002740</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000550</td>\n",
       "      <td>0.003497</td>\n",
       "      <td>0.000000</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>33527</th>\n",
       "      <td>ENSG00000278817</td>\n",
       "      <td>0.023567</td>\n",
       "      <td>0.019182</td>\n",
       "      <td>0.056711</td>\n",
       "      <td>0.063389</td>\n",
       "      <td>0.076336</td>\n",
       "      <td>0.113636</td>\n",
       "      <td>0.080214</td>\n",
       "      <td>0.032922</td>\n",
       "      <td>0.048048</td>\n",
       "      <td>...</td>\n",
       "      <td>0.021918</td>\n",
       "      <td>0.031477</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002577</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005316</td>\n",
       "      <td>0.019231</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33528</th>\n",
       "      <td>ENSG00000277196</td>\n",
       "      <td>0.010712</td>\n",
       "      <td>0.121483</td>\n",
       "      <td>0.001890</td>\n",
       "      <td>0.002587</td>\n",
       "      <td>0.003817</td>\n",
       "      <td>0.007576</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.012346</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.005479</td>\n",
       "      <td>0.002421</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002577</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001283</td>\n",
       "      <td>0.008741</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33530</th>\n",
       "      <td>ENSG00000278384</td>\n",
       "      <td>0.041064</td>\n",
       "      <td>0.033248</td>\n",
       "      <td>0.083176</td>\n",
       "      <td>0.090556</td>\n",
       "      <td>0.097328</td>\n",
       "      <td>0.045455</td>\n",
       "      <td>0.053476</td>\n",
       "      <td>0.049383</td>\n",
       "      <td>0.036036</td>\n",
       "      <td>...</td>\n",
       "      <td>0.032877</td>\n",
       "      <td>0.021792</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.033505</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.027681</td>\n",
       "      <td>0.040210</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33535</th>\n",
       "      <td>ENSG00000271254</td>\n",
       "      <td>0.066149</td>\n",
       "      <td>0.051151</td>\n",
       "      <td>0.086957</td>\n",
       "      <td>0.082794</td>\n",
       "      <td>0.131679</td>\n",
       "      <td>0.045455</td>\n",
       "      <td>0.139037</td>\n",
       "      <td>0.135802</td>\n",
       "      <td>0.099099</td>\n",
       "      <td>...</td>\n",
       "      <td>0.115068</td>\n",
       "      <td>0.181598</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.033505</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.037580</td>\n",
       "      <td>0.064685</td>\n",
       "      <td>0.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33537</th>\n",
       "      <td>ENSG00000268674</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</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",
       "  </tbody>\n",
       "</table>\n",
       "<p>25615 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    ID  propNucleiExprs  propExprsIn.Astro  \\\n",
       "0      ENSG00000243485         0.000179           0.000000   \n",
       "3      ENSG00000238009         0.095876           0.033248   \n",
       "11     ENSG00000229905         0.000446           0.000000   \n",
       "12     ENSG00000237491         0.336011           0.116368   \n",
       "13     ENSG00000177757         0.001250           0.001279   \n",
       "...                ...              ...                ...   \n",
       "33527  ENSG00000278817         0.023567           0.019182   \n",
       "33528  ENSG00000277196         0.010712           0.121483   \n",
       "33530  ENSG00000278384         0.041064           0.033248   \n",
       "33535  ENSG00000271254         0.066149           0.051151   \n",
       "33537  ENSG00000268674         0.000000           0.000000   \n",
       "\n",
       "       propExprsIn.Excit_A  propExprsIn.Excit_B  propExprsIn.Excit_C  \\\n",
       "0                 0.000000             0.001294             0.000000   \n",
       "3                 0.240076             0.124191             0.282443   \n",
       "11                0.000000             0.000000             0.000000   \n",
       "12                0.799622             0.667529             0.830153   \n",
       "13                0.000000             0.003881             0.001908   \n",
       "...                    ...                  ...                  ...   \n",
       "33527             0.056711             0.063389             0.076336   \n",
       "33528             0.001890             0.002587             0.003817   \n",
       "33530             0.083176             0.090556             0.097328   \n",
       "33535             0.086957             0.082794             0.131679   \n",
       "33537             0.000000             0.000000             0.000000   \n",
       "\n",
       "       propExprsIn.Excit_D  propExprsIn.Excit_E  propExprsIn.Excit_F  \\\n",
       "0                 0.000000             0.000000             0.000000   \n",
       "3                 0.212121             0.320856             0.288066   \n",
       "11                0.007576             0.000000             0.000000   \n",
       "12                0.840909             0.828877             0.757202   \n",
       "13                0.000000             0.000000             0.004115   \n",
       "...                    ...                  ...                  ...   \n",
       "33527             0.113636             0.080214             0.032922   \n",
       "33528             0.007576             0.000000             0.012346   \n",
       "33530             0.045455             0.053476             0.049383   \n",
       "33535             0.045455             0.139037             0.135802   \n",
       "33537             0.000000             0.000000             0.000000   \n",
       "\n",
       "       propExprsIn.Inhib_A  ...  propExprsIn.Inhib_C  propExprsIn.Inhib_D  \\\n",
       "0                 0.000000  ...             0.002740             0.000000   \n",
       "3                 0.111111  ...             0.158904             0.196126   \n",
       "11                0.000000  ...             0.002740             0.002421   \n",
       "12                0.450450  ...             0.545205             0.554479   \n",
       "13                0.003003  ...             0.002740             0.000000   \n",
       "...                    ...  ...                  ...                  ...   \n",
       "33527             0.048048  ...             0.021918             0.031477   \n",
       "33528             0.000000  ...             0.005479             0.002421   \n",
       "33530             0.036036  ...             0.032877             0.021792   \n",
       "33535             0.099099  ...             0.115068             0.181598   \n",
       "33537             0.000000  ...             0.000000             0.000000   \n",
       "\n",
       "       propExprsIn.Inhib_E  propExprsIn.Inhib_F  propExprsIn.Macrophage  \\\n",
       "0                 0.000000                0.000                     0.0   \n",
       "3                 0.142857                0.125                     0.0   \n",
       "11                0.000000                0.000                     0.0   \n",
       "12                0.285714                0.750                     0.0   \n",
       "13                0.000000                0.000                     0.0   \n",
       "...                    ...                  ...                     ...   \n",
       "33527             0.000000                0.125                     0.0   \n",
       "33528             0.000000                0.000                     0.0   \n",
       "33530             0.000000                0.000                     0.0   \n",
       "33535             0.000000                0.125                     0.0   \n",
       "33537             0.000000                0.000                     0.0   \n",
       "\n",
       "       propExprsIn.Micro  propExprsIn.Mural  propExprsIn.Oligo  \\\n",
       "0               0.000000           0.000000           0.000000   \n",
       "3               0.046392           0.000000           0.044730   \n",
       "11              0.000000           0.000000           0.000183   \n",
       "12              0.139175           0.166667           0.155454   \n",
       "13              0.000000           0.000000           0.000550   \n",
       "...                  ...                ...                ...   \n",
       "33527           0.002577           0.000000           0.005316   \n",
       "33528           0.002577           0.000000           0.001283   \n",
       "33530           0.033505           0.000000           0.027681   \n",
       "33535           0.033505           0.000000           0.037580   \n",
       "33537           0.000000           0.000000           0.000000   \n",
       "\n",
       "       propExprsIn.OPC  propExprsIn.Tcell  \n",
       "0             0.000000           0.000000  \n",
       "3             0.031469           0.000000  \n",
       "11            0.000000           0.000000  \n",
       "12            0.234266           0.111111  \n",
       "13            0.003497           0.000000  \n",
       "...                ...                ...  \n",
       "33527         0.019231           0.000000  \n",
       "33528         0.008741           0.000000  \n",
       "33530         0.040210           0.000000  \n",
       "33535         0.064685           0.111111  \n",
       "33537         0.000000           0.000000  \n",
       "\n",
       "[25615 rows x 21 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "same_genes = cell_type[cell_type['ID'].isin(temp.columns[1:])]\n",
    "same_genes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>propNucleiExprs</th>\n",
       "      <th>propExprsIn.Astro</th>\n",
       "      <th>propExprsIn.Excit_A</th>\n",
       "      <th>propExprsIn.Excit_B</th>\n",
       "      <th>propExprsIn.Excit_C</th>\n",
       "      <th>propExprsIn.Excit_D</th>\n",
       "      <th>propExprsIn.Excit_E</th>\n",
       "      <th>propExprsIn.Excit_F</th>\n",
       "      <th>propExprsIn.Inhib_A</th>\n",
       "      <th>propExprsIn.Inhib_B</th>\n",
       "      <th>propExprsIn.Inhib_C</th>\n",
       "      <th>propExprsIn.Inhib_D</th>\n",
       "      <th>propExprsIn.Inhib_E</th>\n",
       "      <th>propExprsIn.Inhib_F</th>\n",
       "      <th>propExprsIn.Macrophage</th>\n",
       "      <th>propExprsIn.Micro</th>\n",
       "      <th>propExprsIn.Mural</th>\n",
       "      <th>propExprsIn.Oligo</th>\n",
       "      <th>propExprsIn.OPC</th>\n",
       "      <th>propExprsIn.Tcell</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spot</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAACAAGTATCTCCCA-1</th>\n",
       "      <td>3872.346630</td>\n",
       "      <td>2642.832007</td>\n",
       "      <td>7018.911621</td>\n",
       "      <td>6087.503842</td>\n",
       "      <td>7506.812222</td>\n",
       "      <td>6752.147272</td>\n",
       "      <td>7453.208674</td>\n",
       "      <td>6731.041330</td>\n",
       "      <td>5552.417505</td>\n",
       "      <td>4956.741282</td>\n",
       "      <td>5846.716693</td>\n",
       "      <td>6382.812088</td>\n",
       "      <td>4917.816656</td>\n",
       "      <td>5353.395509</td>\n",
       "      <td>1684.973860</td>\n",
       "      <td>1923.925501</td>\n",
       "      <td>2023.325058</td>\n",
       "      <td>2454.525595</td>\n",
       "      <td>3299.786482</td>\n",
       "      <td>1672.598649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACAATCTACTAGCA-1</th>\n",
       "      <td>1818.123814</td>\n",
       "      <td>1257.411637</td>\n",
       "      <td>3262.992943</td>\n",
       "      <td>2865.913023</td>\n",
       "      <td>3488.866031</td>\n",
       "      <td>3140.902020</td>\n",
       "      <td>3446.643939</td>\n",
       "      <td>3112.962894</td>\n",
       "      <td>2608.151451</td>\n",
       "      <td>2318.360793</td>\n",
       "      <td>2741.565479</td>\n",
       "      <td>2950.656416</td>\n",
       "      <td>2318.057143</td>\n",
       "      <td>2527.045833</td>\n",
       "      <td>793.358333</td>\n",
       "      <td>894.193686</td>\n",
       "      <td>962.107407</td>\n",
       "      <td>1165.344714</td>\n",
       "      <td>1547.183159</td>\n",
       "      <td>798.601852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACACCAATAACTGC-1</th>\n",
       "      <td>3325.648112</td>\n",
       "      <td>2228.864291</td>\n",
       "      <td>5708.383927</td>\n",
       "      <td>4957.663402</td>\n",
       "      <td>6122.907038</td>\n",
       "      <td>5479.680616</td>\n",
       "      <td>6046.942483</td>\n",
       "      <td>5471.124464</td>\n",
       "      <td>4531.935516</td>\n",
       "      <td>4041.553366</td>\n",
       "      <td>4800.901274</td>\n",
       "      <td>5186.062748</td>\n",
       "      <td>4012.194939</td>\n",
       "      <td>4388.179879</td>\n",
       "      <td>1468.233175</td>\n",
       "      <td>1664.116295</td>\n",
       "      <td>1741.998814</td>\n",
       "      <td>2320.187604</td>\n",
       "      <td>2804.326459</td>\n",
       "      <td>1463.306574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACAGAGCGACTCCT-1</th>\n",
       "      <td>3231.553315</td>\n",
       "      <td>2220.716078</td>\n",
       "      <td>5847.601985</td>\n",
       "      <td>5098.481981</td>\n",
       "      <td>6279.206862</td>\n",
       "      <td>5637.303738</td>\n",
       "      <td>6215.024012</td>\n",
       "      <td>5600.976607</td>\n",
       "      <td>4615.366777</td>\n",
       "      <td>4131.385009</td>\n",
       "      <td>4876.602139</td>\n",
       "      <td>5300.246256</td>\n",
       "      <td>4080.374052</td>\n",
       "      <td>4480.050460</td>\n",
       "      <td>1405.433120</td>\n",
       "      <td>1608.437888</td>\n",
       "      <td>1693.026609</td>\n",
       "      <td>2046.515528</td>\n",
       "      <td>2762.711550</td>\n",
       "      <td>1392.287101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACAGCTTTCAGAAG-1</th>\n",
       "      <td>2954.688495</td>\n",
       "      <td>1985.757572</td>\n",
       "      <td>5314.943103</td>\n",
       "      <td>4610.970168</td>\n",
       "      <td>5678.369534</td>\n",
       "      <td>5112.134491</td>\n",
       "      <td>5640.653788</td>\n",
       "      <td>5082.219769</td>\n",
       "      <td>4191.696644</td>\n",
       "      <td>3750.608790</td>\n",
       "      <td>4426.383089</td>\n",
       "      <td>4796.091605</td>\n",
       "      <td>3723.956689</td>\n",
       "      <td>4057.896627</td>\n",
       "      <td>1286.904444</td>\n",
       "      <td>1467.826020</td>\n",
       "      <td>1548.469004</td>\n",
       "      <td>1911.830945</td>\n",
       "      <td>2491.305207</td>\n",
       "      <td>1304.882672</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTCACATCCAGG-1</th>\n",
       "      <td>2963.818965</td>\n",
       "      <td>1975.380996</td>\n",
       "      <td>5141.776059</td>\n",
       "      <td>4485.981556</td>\n",
       "      <td>5527.048329</td>\n",
       "      <td>4944.449145</td>\n",
       "      <td>5446.545983</td>\n",
       "      <td>4921.510032</td>\n",
       "      <td>4058.464220</td>\n",
       "      <td>3618.277533</td>\n",
       "      <td>4302.711878</td>\n",
       "      <td>4631.947917</td>\n",
       "      <td>3585.413461</td>\n",
       "      <td>3942.228301</td>\n",
       "      <td>1296.488506</td>\n",
       "      <td>1452.350151</td>\n",
       "      <td>1541.044194</td>\n",
       "      <td>2040.716375</td>\n",
       "      <td>2487.350923</td>\n",
       "      <td>1293.606790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTCATTAGTCTA-1</th>\n",
       "      <td>2897.385575</td>\n",
       "      <td>1948.256883</td>\n",
       "      <td>5010.352741</td>\n",
       "      <td>4368.898614</td>\n",
       "      <td>5379.258556</td>\n",
       "      <td>4811.213498</td>\n",
       "      <td>5294.060329</td>\n",
       "      <td>4796.372077</td>\n",
       "      <td>3970.254937</td>\n",
       "      <td>3541.809843</td>\n",
       "      <td>4211.807344</td>\n",
       "      <td>4520.510734</td>\n",
       "      <td>3518.326211</td>\n",
       "      <td>3864.749301</td>\n",
       "      <td>1268.268070</td>\n",
       "      <td>1432.922554</td>\n",
       "      <td>1519.411410</td>\n",
       "      <td>1997.743298</td>\n",
       "      <td>2449.287342</td>\n",
       "      <td>1270.021673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTCCATACAACT-1</th>\n",
       "      <td>2730.221024</td>\n",
       "      <td>1863.334562</td>\n",
       "      <td>4913.836828</td>\n",
       "      <td>4277.107642</td>\n",
       "      <td>5262.788398</td>\n",
       "      <td>4719.008967</td>\n",
       "      <td>5197.383556</td>\n",
       "      <td>4714.841247</td>\n",
       "      <td>3890.629976</td>\n",
       "      <td>3483.946618</td>\n",
       "      <td>4120.010604</td>\n",
       "      <td>4458.125474</td>\n",
       "      <td>3441.950304</td>\n",
       "      <td>3807.219242</td>\n",
       "      <td>1187.807799</td>\n",
       "      <td>1346.798273</td>\n",
       "      <td>1431.025419</td>\n",
       "      <td>1749.750488</td>\n",
       "      <td>2325.950771</td>\n",
       "      <td>1175.253255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTGTATTACACG-1</th>\n",
       "      <td>1600.858072</td>\n",
       "      <td>1079.394340</td>\n",
       "      <td>2743.651031</td>\n",
       "      <td>2400.304901</td>\n",
       "      <td>2934.994929</td>\n",
       "      <td>2631.636075</td>\n",
       "      <td>2904.499758</td>\n",
       "      <td>2622.340956</td>\n",
       "      <td>2187.528228</td>\n",
       "      <td>1932.161181</td>\n",
       "      <td>2304.647926</td>\n",
       "      <td>2458.942183</td>\n",
       "      <td>1937.636735</td>\n",
       "      <td>2088.381250</td>\n",
       "      <td>706.827143</td>\n",
       "      <td>789.574945</td>\n",
       "      <td>823.868386</td>\n",
       "      <td>1123.185409</td>\n",
       "      <td>1332.032959</td>\n",
       "      <td>711.623545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TTGTTTGTGTAAATTC-1</th>\n",
       "      <td>3058.467861</td>\n",
       "      <td>2097.783679</td>\n",
       "      <td>5521.746582</td>\n",
       "      <td>4834.560383</td>\n",
       "      <td>5931.706050</td>\n",
       "      <td>5319.323149</td>\n",
       "      <td>5846.211453</td>\n",
       "      <td>5282.896818</td>\n",
       "      <td>4372.079833</td>\n",
       "      <td>3903.581565</td>\n",
       "      <td>4615.173912</td>\n",
       "      <td>4988.719660</td>\n",
       "      <td>3867.089502</td>\n",
       "      <td>4255.891004</td>\n",
       "      <td>1315.240801</td>\n",
       "      <td>1507.926397</td>\n",
       "      <td>1606.261738</td>\n",
       "      <td>1944.414335</td>\n",
       "      <td>2613.784943</td>\n",
       "      <td>1321.123854</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3639 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    propNucleiExprs  propExprsIn.Astro  propExprsIn.Excit_A  \\\n",
       "spot                                                                          \n",
       "AAACAAGTATCTCCCA-1      3872.346630        2642.832007          7018.911621   \n",
       "AAACAATCTACTAGCA-1      1818.123814        1257.411637          3262.992943   \n",
       "AAACACCAATAACTGC-1      3325.648112        2228.864291          5708.383927   \n",
       "AAACAGAGCGACTCCT-1      3231.553315        2220.716078          5847.601985   \n",
       "AAACAGCTTTCAGAAG-1      2954.688495        1985.757572          5314.943103   \n",
       "...                             ...                ...                  ...   \n",
       "TTGTTTCACATCCAGG-1      2963.818965        1975.380996          5141.776059   \n",
       "TTGTTTCATTAGTCTA-1      2897.385575        1948.256883          5010.352741   \n",
       "TTGTTTCCATACAACT-1      2730.221024        1863.334562          4913.836828   \n",
       "TTGTTTGTATTACACG-1      1600.858072        1079.394340          2743.651031   \n",
       "TTGTTTGTGTAAATTC-1      3058.467861        2097.783679          5521.746582   \n",
       "\n",
       "                    propExprsIn.Excit_B  propExprsIn.Excit_C  \\\n",
       "spot                                                           \n",
       "AAACAAGTATCTCCCA-1          6087.503842          7506.812222   \n",
       "AAACAATCTACTAGCA-1          2865.913023          3488.866031   \n",
       "AAACACCAATAACTGC-1          4957.663402          6122.907038   \n",
       "AAACAGAGCGACTCCT-1          5098.481981          6279.206862   \n",
       "AAACAGCTTTCAGAAG-1          4610.970168          5678.369534   \n",
       "...                                 ...                  ...   \n",
       "TTGTTTCACATCCAGG-1          4485.981556          5527.048329   \n",
       "TTGTTTCATTAGTCTA-1          4368.898614          5379.258556   \n",
       "TTGTTTCCATACAACT-1          4277.107642          5262.788398   \n",
       "TTGTTTGTATTACACG-1          2400.304901          2934.994929   \n",
       "TTGTTTGTGTAAATTC-1          4834.560383          5931.706050   \n",
       "\n",
       "                    propExprsIn.Excit_D  propExprsIn.Excit_E  \\\n",
       "spot                                                           \n",
       "AAACAAGTATCTCCCA-1          6752.147272          7453.208674   \n",
       "AAACAATCTACTAGCA-1          3140.902020          3446.643939   \n",
       "AAACACCAATAACTGC-1          5479.680616          6046.942483   \n",
       "AAACAGAGCGACTCCT-1          5637.303738          6215.024012   \n",
       "AAACAGCTTTCAGAAG-1          5112.134491          5640.653788   \n",
       "...                                 ...                  ...   \n",
       "TTGTTTCACATCCAGG-1          4944.449145          5446.545983   \n",
       "TTGTTTCATTAGTCTA-1          4811.213498          5294.060329   \n",
       "TTGTTTCCATACAACT-1          4719.008967          5197.383556   \n",
       "TTGTTTGTATTACACG-1          2631.636075          2904.499758   \n",
       "TTGTTTGTGTAAATTC-1          5319.323149          5846.211453   \n",
       "\n",
       "                    propExprsIn.Excit_F  propExprsIn.Inhib_A  \\\n",
       "spot                                                           \n",
       "AAACAAGTATCTCCCA-1          6731.041330          5552.417505   \n",
       "AAACAATCTACTAGCA-1          3112.962894          2608.151451   \n",
       "AAACACCAATAACTGC-1          5471.124464          4531.935516   \n",
       "AAACAGAGCGACTCCT-1          5600.976607          4615.366777   \n",
       "AAACAGCTTTCAGAAG-1          5082.219769          4191.696644   \n",
       "...                                 ...                  ...   \n",
       "TTGTTTCACATCCAGG-1          4921.510032          4058.464220   \n",
       "TTGTTTCATTAGTCTA-1          4796.372077          3970.254937   \n",
       "TTGTTTCCATACAACT-1          4714.841247          3890.629976   \n",
       "TTGTTTGTATTACACG-1          2622.340956          2187.528228   \n",
       "TTGTTTGTGTAAATTC-1          5282.896818          4372.079833   \n",
       "\n",
       "                    propExprsIn.Inhib_B  propExprsIn.Inhib_C  \\\n",
       "spot                                                           \n",
       "AAACAAGTATCTCCCA-1          4956.741282          5846.716693   \n",
       "AAACAATCTACTAGCA-1          2318.360793          2741.565479   \n",
       "AAACACCAATAACTGC-1          4041.553366          4800.901274   \n",
       "AAACAGAGCGACTCCT-1          4131.385009          4876.602139   \n",
       "AAACAGCTTTCAGAAG-1          3750.608790          4426.383089   \n",
       "...                                 ...                  ...   \n",
       "TTGTTTCACATCCAGG-1          3618.277533          4302.711878   \n",
       "TTGTTTCATTAGTCTA-1          3541.809843          4211.807344   \n",
       "TTGTTTCCATACAACT-1          3483.946618          4120.010604   \n",
       "TTGTTTGTATTACACG-1          1932.161181          2304.647926   \n",
       "TTGTTTGTGTAAATTC-1          3903.581565          4615.173912   \n",
       "\n",
       "                    propExprsIn.Inhib_D  propExprsIn.Inhib_E  \\\n",
       "spot                                                           \n",
       "AAACAAGTATCTCCCA-1          6382.812088          4917.816656   \n",
       "AAACAATCTACTAGCA-1          2950.656416          2318.057143   \n",
       "AAACACCAATAACTGC-1          5186.062748          4012.194939   \n",
       "AAACAGAGCGACTCCT-1          5300.246256          4080.374052   \n",
       "AAACAGCTTTCAGAAG-1          4796.091605          3723.956689   \n",
       "...                                 ...                  ...   \n",
       "TTGTTTCACATCCAGG-1          4631.947917          3585.413461   \n",
       "TTGTTTCATTAGTCTA-1          4520.510734          3518.326211   \n",
       "TTGTTTCCATACAACT-1          4458.125474          3441.950304   \n",
       "TTGTTTGTATTACACG-1          2458.942183          1937.636735   \n",
       "TTGTTTGTGTAAATTC-1          4988.719660          3867.089502   \n",
       "\n",
       "                    propExprsIn.Inhib_F  propExprsIn.Macrophage  \\\n",
       "spot                                                              \n",
       "AAACAAGTATCTCCCA-1          5353.395509             1684.973860   \n",
       "AAACAATCTACTAGCA-1          2527.045833              793.358333   \n",
       "AAACACCAATAACTGC-1          4388.179879             1468.233175   \n",
       "AAACAGAGCGACTCCT-1          4480.050460             1405.433120   \n",
       "AAACAGCTTTCAGAAG-1          4057.896627             1286.904444   \n",
       "...                                 ...                     ...   \n",
       "TTGTTTCACATCCAGG-1          3942.228301             1296.488506   \n",
       "TTGTTTCATTAGTCTA-1          3864.749301             1268.268070   \n",
       "TTGTTTCCATACAACT-1          3807.219242             1187.807799   \n",
       "TTGTTTGTATTACACG-1          2088.381250              706.827143   \n",
       "TTGTTTGTGTAAATTC-1          4255.891004             1315.240801   \n",
       "\n",
       "                    propExprsIn.Micro  propExprsIn.Mural  propExprsIn.Oligo  \\\n",
       "spot                                                                          \n",
       "AAACAAGTATCTCCCA-1        1923.925501        2023.325058        2454.525595   \n",
       "AAACAATCTACTAGCA-1         894.193686         962.107407        1165.344714   \n",
       "AAACACCAATAACTGC-1        1664.116295        1741.998814        2320.187604   \n",
       "AAACAGAGCGACTCCT-1        1608.437888        1693.026609        2046.515528   \n",
       "AAACAGCTTTCAGAAG-1        1467.826020        1548.469004        1911.830945   \n",
       "...                               ...                ...                ...   \n",
       "TTGTTTCACATCCAGG-1        1452.350151        1541.044194        2040.716375   \n",
       "TTGTTTCATTAGTCTA-1        1432.922554        1519.411410        1997.743298   \n",
       "TTGTTTCCATACAACT-1        1346.798273        1431.025419        1749.750488   \n",
       "TTGTTTGTATTACACG-1         789.574945         823.868386        1123.185409   \n",
       "TTGTTTGTGTAAATTC-1        1507.926397        1606.261738        1944.414335   \n",
       "\n",
       "                    propExprsIn.OPC  propExprsIn.Tcell  \n",
       "spot                                                    \n",
       "AAACAAGTATCTCCCA-1      3299.786482        1672.598649  \n",
       "AAACAATCTACTAGCA-1      1547.183159         798.601852  \n",
       "AAACACCAATAACTGC-1      2804.326459        1463.306574  \n",
       "AAACAGAGCGACTCCT-1      2762.711550        1392.287101  \n",
       "AAACAGCTTTCAGAAG-1      2491.305207        1304.882672  \n",
       "...                             ...                ...  \n",
       "TTGTTTCACATCCAGG-1      2487.350923        1293.606790  \n",
       "TTGTTTCATTAGTCTA-1      2449.287342        1270.021673  \n",
       "TTGTTTCCATACAACT-1      2325.950771        1175.253255  \n",
       "TTGTTTGTATTACACG-1      1332.032959         711.623545  \n",
       "TTGTTTGTGTAAATTC-1      2613.784943        1321.123854  \n",
       "\n",
       "[3639 rows x 20 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# from spotxgene counts matrix, multiply proportion of cell type when gene count >0 at spot; then add across all spots. \n",
    "# see which is the highest... will probs have to rethink if this is valid.... \n",
    "spot_type = temp.set_index('spot') @ same_genes.set_index('ID')\n",
    "spot_type"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.13 ('CellDART')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "097bc2b42b2476aac01f79cce36ba62d71b4905bef5fba83d7b38d4fb598770b"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}