{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据处理：SMILES信息在Gene里，CP里面没有，所以首先在这里实现映射和对齐"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import os\n",
    "import h5py\n",
    "\n",
    "def load_from_HDF(fname):\n",
    "    \"\"\"Load data from a HDF5 file to a dictionary.\"\"\"\n",
    "    data = dict()\n",
    "    with h5py.File(fname, 'r') as f:\n",
    "        for key in f:\n",
    "            data[key] = np.asarray(f[key])\n",
    "            if isinstance(data[key][0], np.bytes_):\n",
    "                data[key] = data[key].astype(str)\n",
    "    return data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "看文件名就能大致推断这些是 L1000（基因表达）实验数据的不同处理版本。拆一下：\n",
    "\n",
    "# replicate_level_l1k.csv.gz\n",
    "\n",
    "replicate level 表示这是原始的重复水平（每个实验重复、每个孔的独立测量）。\n",
    "\n",
    "没有额外后缀，通常代表的是比较“基础”的数值（可能是直接从测序/芯片信号经过标准化后的结果）。\n",
    "\n",
    "# replicate_level_l1k_pclfc.csv.gz\n",
    "\n",
    "pclfc 应该是 plate-centered log fold change 的缩写。\n",
    "\n",
    "意味着：对同一板（plate）的数据做了中心化（plate centering），再计算 log fold change，相当于消除板间差异的影响。\n",
    "\n",
    "# replicate_level_l1k_pczscore.csv.gz\n",
    "\n",
    "pczscore = plate-centered z-score。\n",
    "\n",
    "在每个板内，先做中心化，再按标准差缩放，得到标准正态分布的 z-score 值。常用于跨板比较，因为板效应（batch effect）被部分去掉。\n",
    "\n",
    "# replicate_level_l1k_vczscore.csv.gz\n",
    "\n",
    "vczscore = vehicle-centered z-score。\n",
    "\n",
    "是以 对照组（vehicle control） 为基准，做 z-score 标准化。这样更直接衡量药物相对对照的扰动幅度。\n",
    "\n",
    "# treatment_level_l1k.csv.gz\n",
    "\n",
    "treatment level 表示已经把 replicate-level 聚合到 处理水平（treatment level）。\n",
    "\n",
    "一个药物 × 剂量 × 时间点的所有重复实验已经合并成一个代表性 profile（比如均值或中位数）。\n",
    "\n",
    "通常用于下游分析（聚类、表型比较），因为它去掉了重复的噪声。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果你要做 模型训练，通常会优先用 replicate_level，因为保留了最大的信息量；如果要做 统计比较或可视化聚类，则 treatment_level 更合适。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_2269741/4254072982.py:7: DtypeWarning: Columns (985) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  GE_CSV = pd.read_csv(GE_path)\n"
     ]
    },
    {
     "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>221227_x_at</th>\n",
       "      <th>212345_s_at</th>\n",
       "      <th>218597_s_at</th>\n",
       "      <th>217140_s_at</th>\n",
       "      <th>209253_at</th>\n",
       "      <th>214404_x_at</th>\n",
       "      <th>219888_at</th>\n",
       "      <th>201225_s_at</th>\n",
       "      <th>202535_at</th>\n",
       "      <th>219499_at</th>\n",
       "      <th>...</th>\n",
       "      <th>203897_at</th>\n",
       "      <th>pert_id</th>\n",
       "      <th>pert_dose</th>\n",
       "      <th>BROAD_CPD_ID</th>\n",
       "      <th>CPD_NAME</th>\n",
       "      <th>CPD_TYPE</th>\n",
       "      <th>CPD_SMILES</th>\n",
       "      <th>pert_sample_dose</th>\n",
       "      <th>pert_type</th>\n",
       "      <th>control_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.547527</td>\n",
       "      <td>-0.607310</td>\n",
       "      <td>-1.260622</td>\n",
       "      <td>1.837584</td>\n",
       "      <td>-1.176752</td>\n",
       "      <td>5.684604</td>\n",
       "      <td>0.756884</td>\n",
       "      <td>-0.920996</td>\n",
       "      <td>-7.327544</td>\n",
       "      <td>2.412345</td>\n",
       "      <td>...</td>\n",
       "      <td>2.971061</td>\n",
       "      <td>BRD-K07762753-001-03-6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>BRD-K07762753</td>\n",
       "      <td>aminopurvalanol A</td>\n",
       "      <td>BIO</td>\n",
       "      <td>CC(C)[C@H](CO)Nc1nc(Nc2cc(N)cc(Cl)c2)c2ncn(C(C...</td>\n",
       "      <td>BRD-K07762753-001-03-6_50.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.028035</td>\n",
       "      <td>-0.502602</td>\n",
       "      <td>0.146508</td>\n",
       "      <td>-0.384191</td>\n",
       "      <td>0.495755</td>\n",
       "      <td>-2.705428</td>\n",
       "      <td>0.654355</td>\n",
       "      <td>0.256602</td>\n",
       "      <td>-0.157098</td>\n",
       "      <td>-0.115186</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.714138</td>\n",
       "      <td>BRD-K09991945-001-02-0</td>\n",
       "      <td>12.7</td>\n",
       "      <td>BRD-K09991945</td>\n",
       "      <td>GSK-3 inhibitor II</td>\n",
       "      <td>BIO</td>\n",
       "      <td>Ic1cccc(CSc2nnc(o2)-c2ccncc2)c1</td>\n",
       "      <td>BRD-K09991945-001-02-0_12.7</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.394348</td>\n",
       "      <td>1.190005</td>\n",
       "      <td>0.171630</td>\n",
       "      <td>-0.702371</td>\n",
       "      <td>-0.770646</td>\n",
       "      <td>-0.968737</td>\n",
       "      <td>-0.161941</td>\n",
       "      <td>0.348620</td>\n",
       "      <td>-1.860317</td>\n",
       "      <td>-1.486289</td>\n",
       "      <td>...</td>\n",
       "      <td>1.679504</td>\n",
       "      <td>BRD-K46678324-001-03-7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>BRD-K46678324</td>\n",
       "      <td>RHO-kinase inhibitor II</td>\n",
       "      <td>BIO</td>\n",
       "      <td>Clc1cc(Cl)c(NC(=O)Nc2ccncc2)c(Cl)c1</td>\n",
       "      <td>BRD-K46678324-001-03-7_50.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.079737</td>\n",
       "      <td>-0.078623</td>\n",
       "      <td>0.979632</td>\n",
       "      <td>-1.157979</td>\n",
       "      <td>-2.021536</td>\n",
       "      <td>-1.020384</td>\n",
       "      <td>-0.988245</td>\n",
       "      <td>0.841324</td>\n",
       "      <td>-2.685479</td>\n",
       "      <td>-0.412295</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.494014</td>\n",
       "      <td>BRD-K67860401-001-02-3</td>\n",
       "      <td>16.2</td>\n",
       "      <td>BRD-K67860401</td>\n",
       "      <td>GSK-3beta inhibitor VIII</td>\n",
       "      <td>BIO</td>\n",
       "      <td>COc1ccc(CNC(=O)Nc2ncc(s2)[N+]([O-])=O)cc1</td>\n",
       "      <td>BRD-K67860401-001-02-3_16.2</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.807001</td>\n",
       "      <td>1.405668</td>\n",
       "      <td>-0.116184</td>\n",
       "      <td>-0.799675</td>\n",
       "      <td>-0.420112</td>\n",
       "      <td>-0.459989</td>\n",
       "      <td>0.096274</td>\n",
       "      <td>-0.130844</td>\n",
       "      <td>0.460715</td>\n",
       "      <td>1.213526</td>\n",
       "      <td>...</td>\n",
       "      <td>0.201490</td>\n",
       "      <td>BRD-K52620403-001-01-8</td>\n",
       "      <td>12.5</td>\n",
       "      <td>BRD-K52620403</td>\n",
       "      <td>STO 609</td>\n",
       "      <td>BIO</td>\n",
       "      <td>OC(=O)c1ccc2c3nc4ccccc4n3c(=O)c3cccc1c23</td>\n",
       "      <td>BRD-K52620403-001-01-8_12.5</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 986 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   221227_x_at  212345_s_at  218597_s_at  217140_s_at  209253_at  214404_x_at  \\\n",
       "0    -0.547527    -0.607310    -1.260622     1.837584  -1.176752     5.684604   \n",
       "1    -0.028035    -0.502602     0.146508    -0.384191   0.495755    -2.705428   \n",
       "2    -0.394348     1.190005     0.171630    -0.702371  -0.770646    -0.968737   \n",
       "3    -0.079737    -0.078623     0.979632    -1.157979  -2.021536    -1.020384   \n",
       "4     0.807001     1.405668    -0.116184    -0.799675  -0.420112    -0.459989   \n",
       "\n",
       "   219888_at  201225_s_at  202535_at  219499_at  ...  203897_at  \\\n",
       "0   0.756884    -0.920996  -7.327544   2.412345  ...   2.971061   \n",
       "1   0.654355     0.256602  -0.157098  -0.115186  ...  -1.714138   \n",
       "2  -0.161941     0.348620  -1.860317  -1.486289  ...   1.679504   \n",
       "3  -0.988245     0.841324  -2.685479  -0.412295  ...  -0.494014   \n",
       "4   0.096274    -0.130844   0.460715   1.213526  ...   0.201490   \n",
       "\n",
       "                  pert_id  pert_dose   BROAD_CPD_ID                  CPD_NAME  \\\n",
       "0  BRD-K07762753-001-03-6       50.0  BRD-K07762753         aminopurvalanol A   \n",
       "1  BRD-K09991945-001-02-0       12.7  BRD-K09991945        GSK-3 inhibitor II   \n",
       "2  BRD-K46678324-001-03-7       50.0  BRD-K46678324   RHO-kinase inhibitor II   \n",
       "3  BRD-K67860401-001-02-3       16.2  BRD-K67860401  GSK-3beta inhibitor VIII   \n",
       "4  BRD-K52620403-001-01-8       12.5  BRD-K52620403                   STO 609   \n",
       "\n",
       "   CPD_TYPE                                         CPD_SMILES  \\\n",
       "0       BIO  CC(C)[C@H](CO)Nc1nc(Nc2cc(N)cc(Cl)c2)c2ncn(C(C...   \n",
       "1       BIO                    Ic1cccc(CSc2nnc(o2)-c2ccncc2)c1   \n",
       "2       BIO                Clc1cc(Cl)c(NC(=O)Nc2ccncc2)c(Cl)c1   \n",
       "3       BIO          COc1ccc(CNC(=O)Nc2ncc(s2)[N+]([O-])=O)cc1   \n",
       "4       BIO           OC(=O)c1ccc2c3nc4ccccc4n3c(=O)c3cccc1c23   \n",
       "\n",
       "              pert_sample_dose  pert_type  control_type  \n",
       "0  BRD-K07762753-001-03-6_50.0        trt           NaN  \n",
       "1  BRD-K09991945-001-02-0_12.7        trt           NaN  \n",
       "2  BRD-K46678324-001-03-7_50.0        trt           NaN  \n",
       "3  BRD-K67860401-001-02-3_16.2        trt           NaN  \n",
       "4  BRD-K52620403-001-01-8_12.5        trt           NaN  \n",
       "\n",
       "[5 rows x 986 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "root = '/home/bob/boom/VCBench/data/MVC/CDRP-BBBC047-Bray/'\n",
    "\n",
    "CP_path = root + 'CellPainting/replicate_level_cp_normalized_variable_selected.csv.gz'\n",
    "GE_path = root + 'L1000/replicate_level_l1k.csv.gz'\n",
    "\n",
    "# CP_CSV = pd.read_csv(CP_path)\n",
    "GE_CSV = pd.read_csv(GE_path)\n",
    "# print(GE_CSV.shape, CP_CSV.shape)\n",
    "GE_CSV.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(68120, 986)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GE_CSV.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CCCCC\\C=C\\C=C1/[C@@H](C\\C=C/CCCC(O)=O)C=CC1=O                                                                                   715\n",
       "Oc1ccc(cc1)-c1coc2cc(O)cc(O)c2c1=O                                                                                              193\n",
       "C[C@]12CC[C@H]3[C@@H](CCc4cc(O)ccc34)[C@@H]1CC[C@@H]2O                                                                          193\n",
       "CC(/C=C/C1=C(C)CCCC1(C)C)=C\\C=C\\C(C)=C\\C(O)=O                                                                                   190\n",
       "COC1CC(CC(C)C2CC(=O)C(C)\\C=C(C)\\C(O)C(OC)C(=O)C(C)CC(C)\\C=C\\C=C\\C=C(C)\\C(CC3CCC(C)C(O)(O3)C(=O)C(=O)N3CCCCC3C(=O)O2)OC)CCC1O    189\n",
       "                                                                                                                               ... \n",
       "COC(=O)C=CC(=O)NC1CCC2(O)C3Cc4ccc(O)c5OC1C2(CCN3CC1CC1)c45                                                                        1\n",
       "CN(C1CCCCC1N1CCCC1)C(=O)c1ccc(Cl)c(Cl)c1                                                                                          1\n",
       "Cc1nn(c(OC(=O)C2CCCC2)c1S(=O)(=O)c1ccccc1)C(C)(C)C                                                                                1\n",
       "CC1(C)[C@H](O)CC(=O)[C@@]2(C)C1CC(=O)[C@]1(C)C2CC[C@@]2(C)[C@@H](OC(=O)[C@H]3O[C@@]123)c1ccoc1                                    1\n",
       "OC(=O)C1CCCN(CCC=C(c2ccccc2)c2ccccc2)C1                                                                                           1\n",
       "Name: CPD_SMILES, Length: 21781, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GE_CSV['CPD_SMILES'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NaN数量: 0\n"
     ]
    }
   ],
   "source": [
    "nan_count = GE_CSV['CPD_SMILES'].isna().sum()\n",
    "print(f\"NaN数量: {nan_count}\")  # 3478"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===== Checking GeneExpression =====\n",
      "Shape: (68120, 986)\n",
      "Total NaNs: 75076 (0.11% of all values)\n",
      "\n",
      "Summary statistics:\n",
      "                 mean       std        min        max  nan_count\n",
      "221227_x_at -0.050873  0.890101 -14.905430  10.504144          0\n",
      "212345_s_at  0.059451  0.909314  -9.599837  10.908337          0\n",
      "218597_s_at -0.070412  0.914794 -12.414081   6.307222          0\n",
      "217140_s_at -0.029349  0.932918 -37.611337  11.847358          0\n",
      "209253_at   -0.050370  0.883516 -13.595227   7.430222          0\n",
      "214404_x_at  0.065518  0.895404  -7.354430  12.951966          0\n",
      "219888_at    0.062615  0.922233  -6.044906  17.532259          0\n",
      "201225_s_at -0.039507  0.893109 -15.351103   9.122618          0\n",
      "202535_at   -0.092677  0.942675 -11.542489   8.357049          0\n",
      "219499_at    0.037418  0.913377 -13.644873  16.996099          0\n",
      "... (968 more columns)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "def check_dataframe_stats(df, name=\"DataFrame\", max_cols=10):\n",
    "    print(f\"\\n===== Checking {name} =====\")\n",
    "    print(f\"Shape: {df.shape}\")\n",
    "    \n",
    "    # NaN 检查\n",
    "    nan_counts = df.isna().sum()\n",
    "    total_nan = nan_counts.sum()\n",
    "    print(f\"Total NaNs: {total_nan} \"\n",
    "          f\"({total_nan/df.size:.2%} of all values)\")\n",
    "    \n",
    "    # 数值列统计\n",
    "    numeric_df = df.select_dtypes(include=[np.number])\n",
    "    if numeric_df.shape[1] == 0:\n",
    "        print(\"No numeric columns found.\")\n",
    "        return\n",
    "    \n",
    "    stats = pd.DataFrame({\n",
    "        \"mean\": numeric_df.mean(),\n",
    "        \"std\": numeric_df.std(),\n",
    "        \"min\": numeric_df.min(),\n",
    "        \"max\": numeric_df.max(),\n",
    "        \"nan_count\": nan_counts.loc[numeric_df.columns]\n",
    "    })\n",
    "    \n",
    "    print(\"\\nSummary statistics:\")\n",
    "    if numeric_df.shape[1] > max_cols:\n",
    "        # 只展示前 max_cols 列\n",
    "        print(stats.head(max_cols))\n",
    "        print(f\"... ({numeric_df.shape[1]-max_cols} more columns)\")\n",
    "    else:\n",
    "        print(stats)\n",
    "\n",
    "    # 检查是否有异常（例如 std=0 或 min=max）\n",
    "    bad_cols = stats[(stats[\"std\"] == 0) | (stats[\"min\"] == stats[\"max\"])]\n",
    "    if not bad_cols.empty:\n",
    "        print(\"\\nPotentially problematic columns (constant values):\")\n",
    "        print(bad_cols)\n",
    "\n",
    "# 使用\n",
    "check_dataframe_stats(GE_CSV, \"GeneExpression\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===== Checking CellPainting =====\n",
      "Shape: (153386, 919)\n",
      "Total NaNs: 15092945 (10.71% of all values)\n",
      "\n",
      "Summary statistics:\n",
      "                                          mean         std           min  \\\n",
      "Metadata_Plate                    25549.173738  778.815664  24277.000000   \n",
      "Metadata_Assay_Plate_Barcode      25549.173738  778.815664  24277.000000   \n",
      "Metadata_mmoles_per_liter             4.139222    2.001665      0.000000   \n",
      "Metadata_pert_id_vendor                    NaN         NaN           NaN   \n",
      "Cells_AreaShape_Compactness           0.090607    0.225140     -1.313544   \n",
      "Cells_AreaShape_EulerNumber                NaN         NaN           NaN   \n",
      "Cells_AreaShape_Extent               -0.033060    0.176837     -3.000090   \n",
      "Cells_AreaShape_FormFactor            0.021036    0.300102     -3.415679   \n",
      "Cells_AreaShape_MaxFeretDiameter      0.108925    0.482565     -3.018066   \n",
      "Cells_AreaShape_MaximumRadius         0.053408    0.796516     -3.267396   \n",
      "\n",
      "                                           max  nan_count  \n",
      "Metadata_Plate                    26795.000000          0  \n",
      "Metadata_Assay_Plate_Barcode      26795.000000          0  \n",
      "Metadata_mmoles_per_liter            25.000000          0  \n",
      "Metadata_pert_id_vendor                    NaN     153386  \n",
      "Cells_AreaShape_Compactness          20.910727          0  \n",
      "Cells_AreaShape_EulerNumber                NaN     153386  \n",
      "Cells_AreaShape_Extent                5.296431          0  \n",
      "Cells_AreaShape_FormFactor            5.439152          0  \n",
      "Cells_AreaShape_MaxFeretDiameter     40.497419          0  \n",
      "Cells_AreaShape_MaximumRadius       134.437945          0  \n",
      "... (889 more columns)\n",
      "\n",
      "Potentially problematic columns (constant values):\n",
      "                                        mean  std  min  max  nan_count\n",
      "Cells_Correlation_Manders_AGP_Mito      -inf  NaN -inf -inf     152590\n",
      "Cells_Correlation_Manders_AGP_RNA       -inf  NaN -inf -inf     152978\n",
      "Cells_Correlation_Manders_DNA_AGP       -inf  NaN -inf -inf     153269\n",
      "Cells_Correlation_Manders_DNA_ER        -inf  NaN -inf -inf     151860\n",
      "Cells_Correlation_Manders_DNA_Mito      -inf  NaN -inf -inf     153214\n",
      "Cells_Correlation_Manders_DNA_RNA       -inf  NaN -inf -inf     153365\n",
      "Cells_Correlation_Manders_ER_AGP        -inf  NaN -inf -inf     153254\n",
      "Cells_Correlation_Manders_ER_Mito       -inf  NaN -inf -inf     152963\n",
      "Cells_Correlation_Manders_ER_RNA        -inf  NaN -inf -inf     153190\n",
      "Cells_Correlation_Manders_Mito_AGP      -inf  NaN -inf -inf     153066\n",
      "Cells_Correlation_Manders_Mito_RNA      -inf  NaN -inf -inf     152995\n",
      "Cells_Correlation_Manders_RNA_AGP       -inf  NaN -inf -inf     153059\n",
      "Cells_Correlation_Manders_RNA_Mito      -inf  NaN -inf -inf     152566\n",
      "Cytoplasm_Correlation_Manders_AGP_DNA   -inf  NaN -inf -inf     152609\n",
      "Cytoplasm_Correlation_Manders_AGP_Mito  -inf  NaN -inf -inf     152783\n",
      "Cytoplasm_Correlation_Manders_AGP_RNA   -inf  NaN -inf -inf     153350\n",
      "Cytoplasm_Correlation_Manders_DNA_AGP   -inf  NaN -inf -inf     153123\n",
      "Cytoplasm_Correlation_Manders_DNA_Mito  -inf  NaN -inf -inf     152658\n",
      "Cytoplasm_Correlation_Manders_DNA_RNA   -inf  NaN -inf -inf     153341\n",
      "Cytoplasm_Correlation_Manders_ER_AGP    -inf  NaN -inf -inf     153308\n",
      "Cytoplasm_Correlation_Manders_ER_DNA    -inf  NaN -inf -inf     153184\n",
      "Cytoplasm_Correlation_Manders_ER_Mito   -inf  NaN -inf -inf     153091\n",
      "Cytoplasm_Correlation_Manders_ER_RNA    -inf  NaN -inf -inf     153367\n",
      "Cytoplasm_Correlation_Manders_Mito_AGP  -inf  NaN -inf -inf     153193\n",
      "Cytoplasm_Correlation_Manders_Mito_DNA  -inf  NaN -inf -inf     152635\n",
      "Cytoplasm_Correlation_Manders_Mito_RNA  -inf  NaN -inf -inf     153358\n",
      "Cytoplasm_Correlation_Manders_RNA_AGP   -inf  NaN -inf -inf     153135\n",
      "Cytoplasm_Correlation_Manders_RNA_DNA   -inf  NaN -inf -inf     152606\n",
      "Cytoplasm_Correlation_Manders_RNA_Mito  -inf  NaN -inf -inf     152669\n",
      "Nuclei_AreaShape_EulerNumber            -inf  NaN -inf -inf     153378\n",
      "Nuclei_Correlation_Manders_AGP_DNA      -inf  NaN -inf -inf     152875\n",
      "Nuclei_Correlation_Manders_AGP_ER       -inf  NaN -inf -inf     153250\n",
      "Nuclei_Correlation_Manders_AGP_Mito     -inf  NaN -inf -inf     153372\n",
      "Nuclei_Correlation_Manders_AGP_RNA      -inf  NaN -inf -inf     153382\n",
      "Nuclei_Correlation_Manders_DNA_AGP      -inf  NaN -inf -inf     153373\n",
      "Nuclei_Correlation_Manders_DNA_ER       -inf  NaN -inf -inf     153278\n",
      "Nuclei_Correlation_Manders_DNA_Mito     -inf  NaN -inf -inf     153374\n",
      "Nuclei_Correlation_Manders_DNA_RNA      -inf  NaN -inf -inf     153384\n",
      "Nuclei_Correlation_Manders_ER_AGP       -inf  NaN -inf -inf     153380\n",
      "Nuclei_Correlation_Manders_ER_DNA       -inf  NaN -inf -inf     152884\n",
      "Nuclei_Correlation_Manders_ER_Mito      -inf  NaN -inf -inf     153377\n",
      "Nuclei_Correlation_Manders_ER_RNA       -inf  NaN -inf -inf     153384\n",
      "Nuclei_Correlation_Manders_Mito_AGP     -inf  NaN -inf -inf     153374\n",
      "Nuclei_Correlation_Manders_Mito_DNA     -inf  NaN -inf -inf     152876\n",
      "Nuclei_Correlation_Manders_Mito_ER      -inf  NaN -inf -inf     153247\n",
      "Nuclei_Correlation_Manders_Mito_RNA     -inf  NaN -inf -inf     153381\n",
      "Nuclei_Correlation_Manders_RNA_AGP      -inf  NaN -inf -inf     153366\n",
      "Nuclei_Correlation_Manders_RNA_DNA      -inf  NaN -inf -inf     152875\n",
      "Nuclei_Correlation_Manders_RNA_ER       -inf  NaN -inf -inf     153246\n",
      "Nuclei_Correlation_Manders_RNA_Mito     -inf  NaN -inf -inf     153368\n"
     ]
    }
   ],
   "source": [
    "check_dataframe_stats(CP_CSV, \"CellPainting\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>221227_x_at</th>\n",
       "      <th>212345_s_at</th>\n",
       "      <th>218597_s_at</th>\n",
       "      <th>217140_s_at</th>\n",
       "      <th>209253_at</th>\n",
       "      <th>214404_x_at</th>\n",
       "      <th>219888_at</th>\n",
       "      <th>201225_s_at</th>\n",
       "      <th>202535_at</th>\n",
       "      <th>219499_at</th>\n",
       "      <th>...</th>\n",
       "      <th>203897_at</th>\n",
       "      <th>pert_id</th>\n",
       "      <th>pert_dose</th>\n",
       "      <th>BROAD_CPD_ID</th>\n",
       "      <th>CPD_NAME</th>\n",
       "      <th>CPD_TYPE</th>\n",
       "      <th>CPD_SMILES</th>\n",
       "      <th>pert_sample_dose</th>\n",
       "      <th>pert_type</th>\n",
       "      <th>control_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.440750</td>\n",
       "      <td>-0.980983</td>\n",
       "      <td>-1.465698</td>\n",
       "      <td>1.760966</td>\n",
       "      <td>-0.476869</td>\n",
       "      <td>2.479918</td>\n",
       "      <td>0.758642</td>\n",
       "      <td>-0.595733</td>\n",
       "      <td>-3.361279</td>\n",
       "      <td>1.425795</td>\n",
       "      <td>...</td>\n",
       "      <td>1.622410</td>\n",
       "      <td>BRD-K07762753-001-03-6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>BRD-K07762753</td>\n",
       "      <td>aminopurvalanol A</td>\n",
       "      <td>BIO</td>\n",
       "      <td>CC(C)[C@H](CO)Nc1nc(Nc2cc(N)cc(Cl)c2)c2ncn(C(C...</td>\n",
       "      <td>BRD-K07762753-001-03-6_50.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.160911</td>\n",
       "      <td>-0.885708</td>\n",
       "      <td>-0.003157</td>\n",
       "      <td>0.005624</td>\n",
       "      <td>0.580509</td>\n",
       "      <td>-1.285631</td>\n",
       "      <td>0.655823</td>\n",
       "      <td>0.540452</td>\n",
       "      <td>0.286736</td>\n",
       "      <td>-0.206910</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.786290</td>\n",
       "      <td>BRD-K09991945-001-02-0</td>\n",
       "      <td>12.7</td>\n",
       "      <td>BRD-K09991945</td>\n",
       "      <td>GSK-3 inhibitor II</td>\n",
       "      <td>BIO</td>\n",
       "      <td>Ic1cccc(CSc2nnc(o2)-c2ccncc2)c1</td>\n",
       "      <td>BRD-K09991945-001-02-0_12.7</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.263342</td>\n",
       "      <td>0.654407</td>\n",
       "      <td>0.022953</td>\n",
       "      <td>-0.245757</td>\n",
       "      <td>-0.220124</td>\n",
       "      <td>-0.506183</td>\n",
       "      <td>-0.162781</td>\n",
       "      <td>0.629234</td>\n",
       "      <td>-0.579788</td>\n",
       "      <td>-1.092600</td>\n",
       "      <td>...</td>\n",
       "      <td>0.958410</td>\n",
       "      <td>BRD-K46678324-001-03-7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>BRD-K46678324</td>\n",
       "      <td>RHO-kinase inhibitor II</td>\n",
       "      <td>BIO</td>\n",
       "      <td>Clc1cc(Cl)c(NC(=O)Nc2ccncc2)c(Cl)c1</td>\n",
       "      <td>BRD-K46678324-001-03-7_50.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.101031</td>\n",
       "      <td>-0.499927</td>\n",
       "      <td>0.862773</td>\n",
       "      <td>-0.605716</td>\n",
       "      <td>-1.010951</td>\n",
       "      <td>-0.529362</td>\n",
       "      <td>-0.991423</td>\n",
       "      <td>1.104611</td>\n",
       "      <td>-0.999595</td>\n",
       "      <td>-0.398834</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.159014</td>\n",
       "      <td>BRD-K67860401-001-02-3</td>\n",
       "      <td>16.2</td>\n",
       "      <td>BRD-K67860401</td>\n",
       "      <td>GSK-3beta inhibitor VIII</td>\n",
       "      <td>BIO</td>\n",
       "      <td>COc1ccc(CNC(=O)Nc2ncc(s2)[N+]([O-])=O)cc1</td>\n",
       "      <td>BRD-K67860401-001-02-3_16.2</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.128023</td>\n",
       "      <td>0.850640</td>\n",
       "      <td>-0.276194</td>\n",
       "      <td>-0.322634</td>\n",
       "      <td>0.001487</td>\n",
       "      <td>-0.277850</td>\n",
       "      <td>0.096163</td>\n",
       "      <td>0.166631</td>\n",
       "      <td>0.601053</td>\n",
       "      <td>0.651396</td>\n",
       "      <td>...</td>\n",
       "      <td>0.198551</td>\n",
       "      <td>BRD-K52620403-001-01-8</td>\n",
       "      <td>12.5</td>\n",
       "      <td>BRD-K52620403</td>\n",
       "      <td>STO 609</td>\n",
       "      <td>BIO</td>\n",
       "      <td>OC(=O)c1ccc2c3nc4ccccc4n3c(=O)c3cccc1c23</td>\n",
       "      <td>BRD-K52620403-001-01-8_12.5</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 986 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   221227_x_at  212345_s_at  218597_s_at  217140_s_at  209253_at  214404_x_at  \\\n",
       "0    -0.440750    -0.980983    -1.465698     1.760966  -0.476869     2.479918   \n",
       "1     0.160911    -0.885708    -0.003157     0.005624   0.580509    -1.285631   \n",
       "2    -0.263342     0.654407     0.022953    -0.245757  -0.220124    -0.506183   \n",
       "3     0.101031    -0.499927     0.862773    -0.605716  -1.010951    -0.529362   \n",
       "4     1.128023     0.850640    -0.276194    -0.322634   0.001487    -0.277850   \n",
       "\n",
       "   219888_at  201225_s_at  202535_at  219499_at  ...  203897_at  \\\n",
       "0   0.758642    -0.595733  -3.361279   1.425795  ...   1.622410   \n",
       "1   0.655823     0.540452   0.286736  -0.206910  ...  -0.786290   \n",
       "2  -0.162781     0.629234  -0.579788  -1.092600  ...   0.958410   \n",
       "3  -0.991423     1.104611  -0.999595  -0.398834  ...  -0.159014   \n",
       "4   0.096163     0.166631   0.601053   0.651396  ...   0.198551   \n",
       "\n",
       "                  pert_id  pert_dose   BROAD_CPD_ID                  CPD_NAME  \\\n",
       "0  BRD-K07762753-001-03-6       50.0  BRD-K07762753         aminopurvalanol A   \n",
       "1  BRD-K09991945-001-02-0       12.7  BRD-K09991945        GSK-3 inhibitor II   \n",
       "2  BRD-K46678324-001-03-7       50.0  BRD-K46678324   RHO-kinase inhibitor II   \n",
       "3  BRD-K67860401-001-02-3       16.2  BRD-K67860401  GSK-3beta inhibitor VIII   \n",
       "4  BRD-K52620403-001-01-8       12.5  BRD-K52620403                   STO 609   \n",
       "\n",
       "   CPD_TYPE                                         CPD_SMILES  \\\n",
       "0       BIO  CC(C)[C@H](CO)Nc1nc(Nc2cc(N)cc(Cl)c2)c2ncn(C(C...   \n",
       "1       BIO                    Ic1cccc(CSc2nnc(o2)-c2ccncc2)c1   \n",
       "2       BIO                Clc1cc(Cl)c(NC(=O)Nc2ccncc2)c(Cl)c1   \n",
       "3       BIO          COc1ccc(CNC(=O)Nc2ncc(s2)[N+]([O-])=O)cc1   \n",
       "4       BIO           OC(=O)c1ccc2c3nc4ccccc4n3c(=O)c3cccc1c23   \n",
       "\n",
       "              pert_sample_dose  pert_type  control_type  \n",
       "0  BRD-K07762753-001-03-6_50.0        trt           NaN  \n",
       "1  BRD-K09991945-001-02-0_12.7        trt           NaN  \n",
       "2  BRD-K46678324-001-03-7_50.0        trt           NaN  \n",
       "3  BRD-K67860401-001-02-3_16.2        trt           NaN  \n",
       "4  BRD-K52620403-001-01-8_12.5        trt           NaN  \n",
       "\n",
       "[5 rows x 986 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GE_CSV.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Metadata_Plate</th>\n",
       "      <th>Metadata_Well</th>\n",
       "      <th>Metadata_Assay_Plate_Barcode</th>\n",
       "      <th>Metadata_Plate_Map_Name</th>\n",
       "      <th>Metadata_well_position</th>\n",
       "      <th>Metadata_ASSAY_WELL_ROLE</th>\n",
       "      <th>Metadata_broad_sample</th>\n",
       "      <th>Metadata_mmoles_per_liter</th>\n",
       "      <th>Metadata_solvent</th>\n",
       "      <th>Metadata_pert_id</th>\n",
       "      <th>...</th>\n",
       "      <th>Nuclei_Texture_Variance_ER_5_0</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_5_0</th>\n",
       "      <th>Metadata_pert_iname</th>\n",
       "      <th>Metadata_pert_iname2</th>\n",
       "      <th>Metadata_moa</th>\n",
       "      <th>Metadata_target</th>\n",
       "      <th>Metadata_mmoles_per_liter2</th>\n",
       "      <th>Metadata_Sample_Dose</th>\n",
       "      <th>pert_type</th>\n",
       "      <th>control_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24277</td>\n",
       "      <td>a01</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a01</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18250272-003-03-7</td>\n",
       "      <td>3.022516</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18250272</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.199967</td>\n",
       "      <td>-0.075658</td>\n",
       "      <td>propoxycaine</td>\n",
       "      <td>propoxycaine</td>\n",
       "      <td>local anesthetic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.05</td>\n",
       "      <td>BRD-K18250272-003-03-7_6.05</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>24277</td>\n",
       "      <td>a02</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a02</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18316707-001-01-9</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18316707</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.126183</td>\n",
       "      <td>0.018563</td>\n",
       "      <td>O-1918</td>\n",
       "      <td>BRD-K18316707</td>\n",
       "      <td>cannabinoid receptor antagonist</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18316707-001-01-9_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24277</td>\n",
       "      <td>a03</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a03</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18438502-001-02-6</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18438502</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.034355</td>\n",
       "      <td>0.052914</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18438502-001-02-6_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24277</td>\n",
       "      <td>a04</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a04</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18550767-001-02-8</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18550767</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.042241</td>\n",
       "      <td>0.249977</td>\n",
       "      <td>bergenin</td>\n",
       "      <td>bergenin</td>\n",
       "      <td>interleukin inhibitor</td>\n",
       "      <td>IL1B, TNF</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18550767-001-02-8_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24277</td>\n",
       "      <td>a05</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a05</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18574842-323-03-3</td>\n",
       "      <td>2.195487</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18574842</td>\n",
       "      <td>...</td>\n",
       "      <td>0.080018</td>\n",
       "      <td>0.335890</td>\n",
       "      <td>nafcillin</td>\n",
       "      <td>nafcillin</td>\n",
       "      <td>bacterial cell wall synthesis inhibitor</td>\n",
       "      <td>CYP1A2, CYP3A4, SLC22A6</td>\n",
       "      <td>4.39</td>\n",
       "      <td>BRD-K18574842-323-03-3_4.39</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 919 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Metadata_Plate Metadata_Well  Metadata_Assay_Plate_Barcode  \\\n",
       "0           24277           a01                         24277   \n",
       "1           24277           a02                         24277   \n",
       "2           24277           a03                         24277   \n",
       "3           24277           a04                         24277   \n",
       "4           24277           a05                         24277   \n",
       "\n",
       "  Metadata_Plate_Map_Name Metadata_well_position Metadata_ASSAY_WELL_ROLE  \\\n",
       "0            H-BIOA-004-3                    a01                  treated   \n",
       "1            H-BIOA-004-3                    a02                  treated   \n",
       "2            H-BIOA-004-3                    a03                  treated   \n",
       "3            H-BIOA-004-3                    a04                  treated   \n",
       "4            H-BIOA-004-3                    a05                  treated   \n",
       "\n",
       "    Metadata_broad_sample  Metadata_mmoles_per_liter Metadata_solvent  \\\n",
       "0  BRD-K18250272-003-03-7                   3.022516             DMSO   \n",
       "1  BRD-K18316707-001-01-9                   5.000000             DMSO   \n",
       "2  BRD-K18438502-001-02-6                   5.000000             DMSO   \n",
       "3  BRD-K18550767-001-02-8                   5.000000             DMSO   \n",
       "4  BRD-K18574842-323-03-3                   2.195487             DMSO   \n",
       "\n",
       "  Metadata_pert_id  ... Nuclei_Texture_Variance_ER_5_0  \\\n",
       "0    BRD-K18250272  ...                      -0.199967   \n",
       "1    BRD-K18316707  ...                      -0.126183   \n",
       "2    BRD-K18438502  ...                      -0.034355   \n",
       "3    BRD-K18550767  ...                      -0.042241   \n",
       "4    BRD-K18574842  ...                       0.080018   \n",
       "\n",
       "  Nuclei_Texture_Variance_RNA_5_0  Metadata_pert_iname Metadata_pert_iname2  \\\n",
       "0                       -0.075658         propoxycaine         propoxycaine   \n",
       "1                        0.018563               O-1918        BRD-K18316707   \n",
       "2                        0.052914                  NaN                  NaN   \n",
       "3                        0.249977             bergenin             bergenin   \n",
       "4                        0.335890            nafcillin            nafcillin   \n",
       "\n",
       "                              Metadata_moa          Metadata_target  \\\n",
       "0                         local anesthetic                      NaN   \n",
       "1          cannabinoid receptor antagonist                      NaN   \n",
       "2                                      NaN                      NaN   \n",
       "3                    interleukin inhibitor                IL1B, TNF   \n",
       "4  bacterial cell wall synthesis inhibitor  CYP1A2, CYP3A4, SLC22A6   \n",
       "\n",
       "  Metadata_mmoles_per_liter2         Metadata_Sample_Dose  pert_type  \\\n",
       "0                       6.05  BRD-K18250272-003-03-7_6.05        trt   \n",
       "1                      10.00  BRD-K18316707-001-01-9_10.0        trt   \n",
       "2                      10.00  BRD-K18438502-001-02-6_10.0        trt   \n",
       "3                      10.00  BRD-K18550767-001-02-8_10.0        trt   \n",
       "4                       4.39  BRD-K18574842-323-03-3_4.39        trt   \n",
       "\n",
       "   control_type  \n",
       "0           NaN  \n",
       "1           NaN  \n",
       "2           NaN  \n",
       "3           NaN  \n",
       "4           NaN  \n",
       "\n",
       "[5 rows x 919 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CP_CSV.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'det_plate'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "File \u001b[0;32m~/anaconda3/envs/boom/lib/python3.11/site-packages/pandas/core/indexes/base.py:3802\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   3801\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3802\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3803\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n",
      "File \u001b[0;32m~/anaconda3/envs/boom/lib/python3.11/site-packages/pandas/_libs/index.pyx:138\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/envs/boom/lib/python3.11/site-packages/pandas/_libs/index.pyx:165\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:5745\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:5753\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'det_plate'",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[5], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28mlen\u001b[39m(GE_CSV[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCPD_SMILES\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39munique()), \u001b[38;5;28mlen\u001b[39m(\u001b[43mGE_CSV\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mdet_plate\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241m.\u001b[39munique()))  \u001b[38;5;66;03m# 这里错了\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/envs/boom/lib/python3.11/site-packages/pandas/core/frame.py:3807\u001b[0m, in \u001b[0;36mDataFrame.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3805\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcolumns\u001b[38;5;241m.\u001b[39mnlevels \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m   3806\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_getitem_multilevel(key)\n\u001b[0;32m-> 3807\u001b[0m indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3808\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_integer(indexer):\n\u001b[1;32m   3809\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m [indexer]\n",
      "File \u001b[0;32m~/anaconda3/envs/boom/lib/python3.11/site-packages/pandas/core/indexes/base.py:3804\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   3802\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_engine\u001b[38;5;241m.\u001b[39mget_loc(casted_key)\n\u001b[1;32m   3803\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[0;32m-> 3804\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m   3805\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m   3806\u001b[0m     \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m   3807\u001b[0m     \u001b[38;5;66;03m#  InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m   3808\u001b[0m     \u001b[38;5;66;03m#  the TypeError.\u001b[39;00m\n\u001b[1;32m   3809\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n",
      "\u001b[0;31mKeyError\u001b[0m: 'det_plate'"
     ]
    }
   ],
   "source": [
    "print(len(GE_CSV['CPD_SMILES'].unique()), len(GE_CSV['det_plate'].unique()))  # 这里错了"
   ]
  },
  {
   "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>index</th>\n",
       "      <th>pert_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>trt</td>\n",
       "      <td>126814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>control</td>\n",
       "      <td>26572</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     index  pert_type\n",
       "0      trt     126814\n",
       "1  control      26572"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CP_CSV['pert_type'].value_counts().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30413"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(CP_CSV['Metadata_pert_id'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "映射字典大小: 21782\n",
      "匹配成功: 86844/153386 (56.62%)\n"
     ]
    }
   ],
   "source": [
    "# 创建BROAD_CPD_ID到CPD_SMILES的映射字典\n",
    "smiles_mapping = dict(zip(GE_CSV['BROAD_CPD_ID'], GE_CSV['CPD_SMILES']))\n",
    "\n",
    "# 检查映射是否唯一（键值对数量应等于唯一ID数量）\n",
    "print(f\"映射字典大小: {len(smiles_mapping)}\")\n",
    "\n",
    "# 使用映射为CP_CSV添加SMILES列\n",
    "CP_CSV['SMILES'] = CP_CSV['Metadata_pert_id'].map(smiles_mapping)\n",
    "\n",
    "# 检查匹配情况\n",
    "matched = CP_CSV['SMILES'].notna().sum()\n",
    "total = len(CP_CSV)\n",
    "print(f\"匹配成功: {matched}/{total} ({matched/total:.2%})\")\n",
    "\n",
    "# 保存结果\n",
    "# CP_CSV.to_csv('path/to/updated_cp_data.csv', index=False)   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(113416, 920)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 提取匹配成功或者pert_type为'control'的记录（或关系）\n",
    "\n",
    "CP_CSV_matched = CP_CSV[\n",
    "    (CP_CSV['SMILES'].notna()) |  # 匹配成功的记录\n",
    "    (CP_CSV['pert_type'] == 'control')  # 或pert_type为control的记录\n",
    "].copy()\n",
    "CP_CSV_matched.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>Metadata_Plate</th>\n",
       "      <th>Metadata_Well</th>\n",
       "      <th>Metadata_Assay_Plate_Barcode</th>\n",
       "      <th>Metadata_Plate_Map_Name</th>\n",
       "      <th>Metadata_well_position</th>\n",
       "      <th>Metadata_ASSAY_WELL_ROLE</th>\n",
       "      <th>Metadata_broad_sample</th>\n",
       "      <th>Metadata_mmoles_per_liter</th>\n",
       "      <th>Metadata_solvent</th>\n",
       "      <th>Metadata_pert_id</th>\n",
       "      <th>...</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_5_0</th>\n",
       "      <th>Metadata_pert_iname</th>\n",
       "      <th>Metadata_pert_iname2</th>\n",
       "      <th>Metadata_moa</th>\n",
       "      <th>Metadata_target</th>\n",
       "      <th>Metadata_mmoles_per_liter2</th>\n",
       "      <th>Metadata_Sample_Dose</th>\n",
       "      <th>pert_type</th>\n",
       "      <th>control_type</th>\n",
       "      <th>SMILES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24277</td>\n",
       "      <td>a01</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a01</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18250272-003-03-7</td>\n",
       "      <td>3.022516</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18250272</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.075658</td>\n",
       "      <td>propoxycaine</td>\n",
       "      <td>propoxycaine</td>\n",
       "      <td>local anesthetic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.05</td>\n",
       "      <td>BRD-K18250272-003-03-7_6.05</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>24277</td>\n",
       "      <td>a02</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a02</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18316707-001-01-9</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18316707</td>\n",
       "      <td>...</td>\n",
       "      <td>0.018563</td>\n",
       "      <td>O-1918</td>\n",
       "      <td>BRD-K18316707</td>\n",
       "      <td>cannabinoid receptor antagonist</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18316707-001-01-9_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24277</td>\n",
       "      <td>a03</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a03</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18438502-001-02-6</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18438502</td>\n",
       "      <td>...</td>\n",
       "      <td>0.052914</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18438502-001-02-6_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1cc(O)cc(\\C=C\\c2ccccc2)c1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24277</td>\n",
       "      <td>a04</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a04</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18550767-001-02-8</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18550767</td>\n",
       "      <td>...</td>\n",
       "      <td>0.249977</td>\n",
       "      <td>bergenin</td>\n",
       "      <td>bergenin</td>\n",
       "      <td>interleukin inhibitor</td>\n",
       "      <td>IL1B, TNF</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18550767-001-02-8_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24277</td>\n",
       "      <td>a05</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a05</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18574842-323-03-3</td>\n",
       "      <td>2.195487</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18574842</td>\n",
       "      <td>...</td>\n",
       "      <td>0.335890</td>\n",
       "      <td>nafcillin</td>\n",
       "      <td>nafcillin</td>\n",
       "      <td>bacterial cell wall synthesis inhibitor</td>\n",
       "      <td>CYP1A2, CYP3A4, SLC22A6</td>\n",
       "      <td>4.39</td>\n",
       "      <td>BRD-K18574842-323-03-3_4.39</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 920 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Metadata_Plate Metadata_Well  Metadata_Assay_Plate_Barcode  \\\n",
       "0           24277           a01                         24277   \n",
       "1           24277           a02                         24277   \n",
       "2           24277           a03                         24277   \n",
       "3           24277           a04                         24277   \n",
       "4           24277           a05                         24277   \n",
       "\n",
       "  Metadata_Plate_Map_Name Metadata_well_position Metadata_ASSAY_WELL_ROLE  \\\n",
       "0            H-BIOA-004-3                    a01                  treated   \n",
       "1            H-BIOA-004-3                    a02                  treated   \n",
       "2            H-BIOA-004-3                    a03                  treated   \n",
       "3            H-BIOA-004-3                    a04                  treated   \n",
       "4            H-BIOA-004-3                    a05                  treated   \n",
       "\n",
       "    Metadata_broad_sample  Metadata_mmoles_per_liter Metadata_solvent  \\\n",
       "0  BRD-K18250272-003-03-7                   3.022516             DMSO   \n",
       "1  BRD-K18316707-001-01-9                   5.000000             DMSO   \n",
       "2  BRD-K18438502-001-02-6                   5.000000             DMSO   \n",
       "3  BRD-K18550767-001-02-8                   5.000000             DMSO   \n",
       "4  BRD-K18574842-323-03-3                   2.195487             DMSO   \n",
       "\n",
       "  Metadata_pert_id  ... Nuclei_Texture_Variance_RNA_5_0 Metadata_pert_iname  \\\n",
       "0    BRD-K18250272  ...                       -0.075658        propoxycaine   \n",
       "1    BRD-K18316707  ...                        0.018563              O-1918   \n",
       "2    BRD-K18438502  ...                        0.052914                 NaN   \n",
       "3    BRD-K18550767  ...                        0.249977            bergenin   \n",
       "4    BRD-K18574842  ...                        0.335890           nafcillin   \n",
       "\n",
       "   Metadata_pert_iname2                             Metadata_moa  \\\n",
       "0          propoxycaine                         local anesthetic   \n",
       "1         BRD-K18316707          cannabinoid receptor antagonist   \n",
       "2                   NaN                                      NaN   \n",
       "3              bergenin                    interleukin inhibitor   \n",
       "4             nafcillin  bacterial cell wall synthesis inhibitor   \n",
       "\n",
       "           Metadata_target Metadata_mmoles_per_liter2  \\\n",
       "0                      NaN                       6.05   \n",
       "1                      NaN                      10.00   \n",
       "2                      NaN                      10.00   \n",
       "3                IL1B, TNF                      10.00   \n",
       "4  CYP1A2, CYP3A4, SLC22A6                       4.39   \n",
       "\n",
       "          Metadata_Sample_Dose  pert_type  control_type  \\\n",
       "0  BRD-K18250272-003-03-7_6.05        trt           NaN   \n",
       "1  BRD-K18316707-001-01-9_10.0        trt           NaN   \n",
       "2  BRD-K18438502-001-02-6_10.0        trt           NaN   \n",
       "3  BRD-K18550767-001-02-8_10.0        trt           NaN   \n",
       "4  BRD-K18574842-323-03-3_4.39        trt           NaN   \n",
       "\n",
       "                                              SMILES  \n",
       "0                     CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC  \n",
       "1       COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C  \n",
       "2                       COc1cc(O)cc(\\C=C\\c2ccccc2)c1  \n",
       "3  COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...  \n",
       "4  CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...  \n",
       "\n",
       "[5 rows x 920 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CP_CSV_matched.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>index</th>\n",
       "      <th>pert_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>trt</td>\n",
       "      <td>86844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>control</td>\n",
       "      <td>26572</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     index  pert_type\n",
       "0      trt      86844\n",
       "1  control      26572"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CP_CSV_matched['pert_type'].value_counts().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>Metadata_Plate</th>\n",
       "      <th>Metadata_Well</th>\n",
       "      <th>Metadata_Assay_Plate_Barcode</th>\n",
       "      <th>Metadata_Plate_Map_Name</th>\n",
       "      <th>Metadata_well_position</th>\n",
       "      <th>Metadata_ASSAY_WELL_ROLE</th>\n",
       "      <th>Metadata_broad_sample</th>\n",
       "      <th>Metadata_mmoles_per_liter</th>\n",
       "      <th>Metadata_solvent</th>\n",
       "      <th>Metadata_pert_id</th>\n",
       "      <th>...</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_5_0</th>\n",
       "      <th>Metadata_pert_iname</th>\n",
       "      <th>Metadata_pert_iname2</th>\n",
       "      <th>Metadata_moa</th>\n",
       "      <th>Metadata_target</th>\n",
       "      <th>Metadata_mmoles_per_liter2</th>\n",
       "      <th>Metadata_Sample_Dose</th>\n",
       "      <th>pert_type</th>\n",
       "      <th>control_type</th>\n",
       "      <th>SMILES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24277</td>\n",
       "      <td>a01</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a01</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18250272-003-03-7</td>\n",
       "      <td>3.022516</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18250272</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.075658</td>\n",
       "      <td>propoxycaine</td>\n",
       "      <td>propoxycaine</td>\n",
       "      <td>local anesthetic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.05</td>\n",
       "      <td>BRD-K18250272-003-03-7_6.05</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>24277</td>\n",
       "      <td>a02</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a02</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18316707-001-01-9</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18316707</td>\n",
       "      <td>...</td>\n",
       "      <td>0.018563</td>\n",
       "      <td>O-1918</td>\n",
       "      <td>BRD-K18316707</td>\n",
       "      <td>cannabinoid receptor antagonist</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18316707-001-01-9_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24277</td>\n",
       "      <td>a03</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a03</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18438502-001-02-6</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18438502</td>\n",
       "      <td>...</td>\n",
       "      <td>0.052914</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18438502-001-02-6_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1cc(O)cc(\\C=C\\c2ccccc2)c1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24277</td>\n",
       "      <td>a04</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a04</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18550767-001-02-8</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18550767</td>\n",
       "      <td>...</td>\n",
       "      <td>0.249977</td>\n",
       "      <td>bergenin</td>\n",
       "      <td>bergenin</td>\n",
       "      <td>interleukin inhibitor</td>\n",
       "      <td>IL1B, TNF</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18550767-001-02-8_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24277</td>\n",
       "      <td>a05</td>\n",
       "      <td>24277</td>\n",
       "      <td>H-BIOA-004-3</td>\n",
       "      <td>a05</td>\n",
       "      <td>treated</td>\n",
       "      <td>BRD-K18574842-323-03-3</td>\n",
       "      <td>2.195487</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>BRD-K18574842</td>\n",
       "      <td>...</td>\n",
       "      <td>0.335890</td>\n",
       "      <td>nafcillin</td>\n",
       "      <td>nafcillin</td>\n",
       "      <td>bacterial cell wall synthesis inhibitor</td>\n",
       "      <td>CYP1A2, CYP3A4, SLC22A6</td>\n",
       "      <td>4.39</td>\n",
       "      <td>BRD-K18574842-323-03-3_4.39</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 920 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Metadata_Plate Metadata_Well  Metadata_Assay_Plate_Barcode  \\\n",
       "0           24277           a01                         24277   \n",
       "1           24277           a02                         24277   \n",
       "2           24277           a03                         24277   \n",
       "3           24277           a04                         24277   \n",
       "4           24277           a05                         24277   \n",
       "\n",
       "  Metadata_Plate_Map_Name Metadata_well_position Metadata_ASSAY_WELL_ROLE  \\\n",
       "0            H-BIOA-004-3                    a01                  treated   \n",
       "1            H-BIOA-004-3                    a02                  treated   \n",
       "2            H-BIOA-004-3                    a03                  treated   \n",
       "3            H-BIOA-004-3                    a04                  treated   \n",
       "4            H-BIOA-004-3                    a05                  treated   \n",
       "\n",
       "    Metadata_broad_sample  Metadata_mmoles_per_liter Metadata_solvent  \\\n",
       "0  BRD-K18250272-003-03-7                   3.022516             DMSO   \n",
       "1  BRD-K18316707-001-01-9                   5.000000             DMSO   \n",
       "2  BRD-K18438502-001-02-6                   5.000000             DMSO   \n",
       "3  BRD-K18550767-001-02-8                   5.000000             DMSO   \n",
       "4  BRD-K18574842-323-03-3                   2.195487             DMSO   \n",
       "\n",
       "  Metadata_pert_id  ... Nuclei_Texture_Variance_RNA_5_0 Metadata_pert_iname  \\\n",
       "0    BRD-K18250272  ...                       -0.075658        propoxycaine   \n",
       "1    BRD-K18316707  ...                        0.018563              O-1918   \n",
       "2    BRD-K18438502  ...                        0.052914                 NaN   \n",
       "3    BRD-K18550767  ...                        0.249977            bergenin   \n",
       "4    BRD-K18574842  ...                        0.335890           nafcillin   \n",
       "\n",
       "   Metadata_pert_iname2                             Metadata_moa  \\\n",
       "0          propoxycaine                         local anesthetic   \n",
       "1         BRD-K18316707          cannabinoid receptor antagonist   \n",
       "2                   NaN                                      NaN   \n",
       "3              bergenin                    interleukin inhibitor   \n",
       "4             nafcillin  bacterial cell wall synthesis inhibitor   \n",
       "\n",
       "           Metadata_target Metadata_mmoles_per_liter2  \\\n",
       "0                      NaN                       6.05   \n",
       "1                      NaN                      10.00   \n",
       "2                      NaN                      10.00   \n",
       "3                IL1B, TNF                      10.00   \n",
       "4  CYP1A2, CYP3A4, SLC22A6                       4.39   \n",
       "\n",
       "          Metadata_Sample_Dose  pert_type  control_type  \\\n",
       "0  BRD-K18250272-003-03-7_6.05        trt           NaN   \n",
       "1  BRD-K18316707-001-01-9_10.0        trt           NaN   \n",
       "2  BRD-K18438502-001-02-6_10.0        trt           NaN   \n",
       "3  BRD-K18550767-001-02-8_10.0        trt           NaN   \n",
       "4  BRD-K18574842-323-03-3_4.39        trt           NaN   \n",
       "\n",
       "                                              SMILES  \n",
       "0                     CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC  \n",
       "1       COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C  \n",
       "2                       COc1cc(O)cc(\\C=C\\c2ccccc2)c1  \n",
       "3  COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...  \n",
       "4  CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...  \n",
       "\n",
       "[5 rows x 920 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CP_CSV_matched.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 删除无关元素，保留核心"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "        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>Metadata_Plate</th>\n",
       "      <th>Metadata_pert_mfc_id</th>\n",
       "      <th>Metadata_pert_well</th>\n",
       "      <th>Metadata_pert_id_vendor</th>\n",
       "      <th>Metadata_cell_id</th>\n",
       "      <th>Metadata_broad_sample_type</th>\n",
       "      <th>Metadata_pert_vehicle</th>\n",
       "      <th>Metadata_pert_type</th>\n",
       "      <th>Cells_AreaShape_Compactness</th>\n",
       "      <th>Cells_AreaShape_EulerNumber</th>\n",
       "      <th>...</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_5_0</th>\n",
       "      <th>Metadata_pert_iname</th>\n",
       "      <th>Metadata_pert_iname2</th>\n",
       "      <th>Metadata_moa</th>\n",
       "      <th>Metadata_target</th>\n",
       "      <th>Metadata_mmoles_per_liter2</th>\n",
       "      <th>Metadata_Sample_Dose</th>\n",
       "      <th>pert_type</th>\n",
       "      <th>control_type</th>\n",
       "      <th>SMILES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24277</td>\n",
       "      <td>BRD-K18250272-003-03-7</td>\n",
       "      <td>a01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>U2OS</td>\n",
       "      <td>trt</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>trt</td>\n",
       "      <td>0.256710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.075658</td>\n",
       "      <td>propoxycaine</td>\n",
       "      <td>propoxycaine</td>\n",
       "      <td>local anesthetic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.05</td>\n",
       "      <td>BRD-K18250272-003-03-7_6.05</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>24277</td>\n",
       "      <td>BRD-K18316707-001-01-9</td>\n",
       "      <td>a02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>U2OS</td>\n",
       "      <td>trt</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>trt</td>\n",
       "      <td>0.050962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.018563</td>\n",
       "      <td>O-1918</td>\n",
       "      <td>BRD-K18316707</td>\n",
       "      <td>cannabinoid receptor antagonist</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18316707-001-01-9_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24277</td>\n",
       "      <td>BRD-K18438502-001-02-6</td>\n",
       "      <td>a03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>U2OS</td>\n",
       "      <td>trt</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>trt</td>\n",
       "      <td>-0.098185</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.052914</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18438502-001-02-6_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1cc(O)cc(\\C=C\\c2ccccc2)c1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24277</td>\n",
       "      <td>BRD-K18550767-001-02-8</td>\n",
       "      <td>a04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>U2OS</td>\n",
       "      <td>trt</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>trt</td>\n",
       "      <td>0.410722</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.249977</td>\n",
       "      <td>bergenin</td>\n",
       "      <td>bergenin</td>\n",
       "      <td>interleukin inhibitor</td>\n",
       "      <td>IL1B, TNF</td>\n",
       "      <td>10.00</td>\n",
       "      <td>BRD-K18550767-001-02-8_10.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24277</td>\n",
       "      <td>BRD-K18574842-323-03-3</td>\n",
       "      <td>a05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>U2OS</td>\n",
       "      <td>trt</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>trt</td>\n",
       "      <td>0.248559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.335890</td>\n",
       "      <td>nafcillin</td>\n",
       "      <td>nafcillin</td>\n",
       "      <td>bacterial cell wall synthesis inhibitor</td>\n",
       "      <td>CYP1A2, CYP3A4, SLC22A6</td>\n",
       "      <td>4.39</td>\n",
       "      <td>BRD-K18574842-323-03-3_4.39</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 911 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Metadata_Plate    Metadata_pert_mfc_id Metadata_pert_well  \\\n",
       "0           24277  BRD-K18250272-003-03-7                a01   \n",
       "1           24277  BRD-K18316707-001-01-9                a02   \n",
       "2           24277  BRD-K18438502-001-02-6                a03   \n",
       "3           24277  BRD-K18550767-001-02-8                a04   \n",
       "4           24277  BRD-K18574842-323-03-3                a05   \n",
       "\n",
       "   Metadata_pert_id_vendor Metadata_cell_id Metadata_broad_sample_type  \\\n",
       "0                      NaN             U2OS                        trt   \n",
       "1                      NaN             U2OS                        trt   \n",
       "2                      NaN             U2OS                        trt   \n",
       "3                      NaN             U2OS                        trt   \n",
       "4                      NaN             U2OS                        trt   \n",
       "\n",
       "  Metadata_pert_vehicle Metadata_pert_type  Cells_AreaShape_Compactness  \\\n",
       "0                  DMSO                trt                     0.256710   \n",
       "1                  DMSO                trt                     0.050962   \n",
       "2                  DMSO                trt                    -0.098185   \n",
       "3                  DMSO                trt                     0.410722   \n",
       "4                  DMSO                trt                     0.248559   \n",
       "\n",
       "   Cells_AreaShape_EulerNumber  ...  Nuclei_Texture_Variance_RNA_5_0  \\\n",
       "0                          NaN  ...                        -0.075658   \n",
       "1                          NaN  ...                         0.018563   \n",
       "2                          NaN  ...                         0.052914   \n",
       "3                          NaN  ...                         0.249977   \n",
       "4                          NaN  ...                         0.335890   \n",
       "\n",
       "   Metadata_pert_iname  Metadata_pert_iname2  \\\n",
       "0         propoxycaine          propoxycaine   \n",
       "1               O-1918         BRD-K18316707   \n",
       "2                  NaN                   NaN   \n",
       "3             bergenin              bergenin   \n",
       "4            nafcillin             nafcillin   \n",
       "\n",
       "                              Metadata_moa          Metadata_target  \\\n",
       "0                         local anesthetic                      NaN   \n",
       "1          cannabinoid receptor antagonist                      NaN   \n",
       "2                                      NaN                      NaN   \n",
       "3                    interleukin inhibitor                IL1B, TNF   \n",
       "4  bacterial cell wall synthesis inhibitor  CYP1A2, CYP3A4, SLC22A6   \n",
       "\n",
       "   Metadata_mmoles_per_liter2         Metadata_Sample_Dose  pert_type  \\\n",
       "0                        6.05  BRD-K18250272-003-03-7_6.05        trt   \n",
       "1                       10.00  BRD-K18316707-001-01-9_10.0        trt   \n",
       "2                       10.00  BRD-K18438502-001-02-6_10.0        trt   \n",
       "3                       10.00  BRD-K18550767-001-02-8_10.0        trt   \n",
       "4                        4.39  BRD-K18574842-323-03-3_4.39        trt   \n",
       "\n",
       "   control_type                                             SMILES  \n",
       "0           NaN                     CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC  \n",
       "1           NaN       COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C  \n",
       "2           NaN                       COc1cc(O)cc(\\C=C\\c2ccccc2)c1  \n",
       "3           NaN  COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...  \n",
       "4           NaN  CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...  \n",
       "\n",
       "[5 rows x 911 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CP_CSV_matched_filter = CP_CSV_matched.drop(columns=['Metadata_Well', 'Metadata_Assay_Plate_Barcode', 'Metadata_Plate_Map_Name', 'Metadata_well_position',\\\n",
    "    'Metadata_ASSAY_WELL_ROLE', 'Metadata_broad_sample', 'Metadata_mmoles_per_liter', 'Metadata_solvent', 'Metadata_pert_id'])\n",
    "CP_CSV_matched_filter.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Metadata_Plate</th>\n",
       "      <th>Metadata_pert_mfc_id</th>\n",
       "      <th>Metadata_pert_well</th>\n",
       "      <th>Metadata_pert_id_vendor</th>\n",
       "      <th>Metadata_cell_id</th>\n",
       "      <th>Metadata_broad_sample_type</th>\n",
       "      <th>Metadata_pert_vehicle</th>\n",
       "      <th>Metadata_pert_type</th>\n",
       "      <th>Cells_AreaShape_Compactness</th>\n",
       "      <th>Cells_AreaShape_EulerNumber</th>\n",
       "      <th>...</th>\n",
       "      <th>Nuclei_Texture_SumVariance_ER_3_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_Mito_5_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_RNA_10_0</th>\n",
       "      <th>Nuclei_Texture_Variance_AGP_5_0</th>\n",
       "      <th>Nuclei_Texture_Variance_ER_5_0</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_5_0</th>\n",
       "      <th>Metadata_moa</th>\n",
       "      <th>Metadata_mmoles_per_liter2</th>\n",
       "      <th>control_type</th>\n",
       "      <th>SMILES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24277</td>\n",
       "      <td>BRD-K18250272-003-03-7</td>\n",
       "      <td>a01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>U2OS</td>\n",
       "      <td>trt</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>trt</td>\n",
       "      <td>0.256710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.156442</td>\n",
       "      <td>-0.018014</td>\n",
       "      <td>-0.024573</td>\n",
       "      <td>-0.383890</td>\n",
       "      <td>-0.199967</td>\n",
       "      <td>-0.075658</td>\n",
       "      <td>local anesthetic</td>\n",
       "      <td>6.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>24277</td>\n",
       "      <td>BRD-K18316707-001-01-9</td>\n",
       "      <td>a02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>U2OS</td>\n",
       "      <td>trt</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>trt</td>\n",
       "      <td>0.050962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.113721</td>\n",
       "      <td>-0.089807</td>\n",
       "      <td>-0.041392</td>\n",
       "      <td>-0.248967</td>\n",
       "      <td>-0.126183</td>\n",
       "      <td>0.018563</td>\n",
       "      <td>cannabinoid receptor antagonist</td>\n",
       "      <td>10.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24277</td>\n",
       "      <td>BRD-K18438502-001-02-6</td>\n",
       "      <td>a03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>U2OS</td>\n",
       "      <td>trt</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>trt</td>\n",
       "      <td>-0.098185</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.007979</td>\n",
       "      <td>0.081155</td>\n",
       "      <td>-0.089633</td>\n",
       "      <td>0.043140</td>\n",
       "      <td>-0.034355</td>\n",
       "      <td>0.052914</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1cc(O)cc(\\C=C\\c2ccccc2)c1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24277</td>\n",
       "      <td>BRD-K18550767-001-02-8</td>\n",
       "      <td>a04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>U2OS</td>\n",
       "      <td>trt</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>trt</td>\n",
       "      <td>0.410722</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.034251</td>\n",
       "      <td>-0.047597</td>\n",
       "      <td>0.103611</td>\n",
       "      <td>-0.139579</td>\n",
       "      <td>-0.042241</td>\n",
       "      <td>0.249977</td>\n",
       "      <td>interleukin inhibitor</td>\n",
       "      <td>10.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24277</td>\n",
       "      <td>BRD-K18574842-323-03-3</td>\n",
       "      <td>a05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>U2OS</td>\n",
       "      <td>trt</td>\n",
       "      <td>DMSO</td>\n",
       "      <td>trt</td>\n",
       "      <td>0.248559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.257598</td>\n",
       "      <td>0.193370</td>\n",
       "      <td>0.238471</td>\n",
       "      <td>-0.033797</td>\n",
       "      <td>0.080018</td>\n",
       "      <td>0.335890</td>\n",
       "      <td>bacterial cell wall synthesis inhibitor</td>\n",
       "      <td>4.39</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 906 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Metadata_Plate    Metadata_pert_mfc_id Metadata_pert_well  \\\n",
       "0           24277  BRD-K18250272-003-03-7                a01   \n",
       "1           24277  BRD-K18316707-001-01-9                a02   \n",
       "2           24277  BRD-K18438502-001-02-6                a03   \n",
       "3           24277  BRD-K18550767-001-02-8                a04   \n",
       "4           24277  BRD-K18574842-323-03-3                a05   \n",
       "\n",
       "   Metadata_pert_id_vendor Metadata_cell_id Metadata_broad_sample_type  \\\n",
       "0                      NaN             U2OS                        trt   \n",
       "1                      NaN             U2OS                        trt   \n",
       "2                      NaN             U2OS                        trt   \n",
       "3                      NaN             U2OS                        trt   \n",
       "4                      NaN             U2OS                        trt   \n",
       "\n",
       "  Metadata_pert_vehicle Metadata_pert_type  Cells_AreaShape_Compactness  \\\n",
       "0                  DMSO                trt                     0.256710   \n",
       "1                  DMSO                trt                     0.050962   \n",
       "2                  DMSO                trt                    -0.098185   \n",
       "3                  DMSO                trt                     0.410722   \n",
       "4                  DMSO                trt                     0.248559   \n",
       "\n",
       "   Cells_AreaShape_EulerNumber  ...  Nuclei_Texture_SumVariance_ER_3_0  \\\n",
       "0                          NaN  ...                          -0.156442   \n",
       "1                          NaN  ...                          -0.113721   \n",
       "2                          NaN  ...                          -0.007979   \n",
       "3                          NaN  ...                          -0.034251   \n",
       "4                          NaN  ...                           0.257598   \n",
       "\n",
       "   Nuclei_Texture_SumVariance_Mito_5_0  Nuclei_Texture_SumVariance_RNA_10_0  \\\n",
       "0                            -0.018014                            -0.024573   \n",
       "1                            -0.089807                            -0.041392   \n",
       "2                             0.081155                            -0.089633   \n",
       "3                            -0.047597                             0.103611   \n",
       "4                             0.193370                             0.238471   \n",
       "\n",
       "   Nuclei_Texture_Variance_AGP_5_0  Nuclei_Texture_Variance_ER_5_0  \\\n",
       "0                        -0.383890                       -0.199967   \n",
       "1                        -0.248967                       -0.126183   \n",
       "2                         0.043140                       -0.034355   \n",
       "3                        -0.139579                       -0.042241   \n",
       "4                        -0.033797                        0.080018   \n",
       "\n",
       "   Nuclei_Texture_Variance_RNA_5_0                             Metadata_moa  \\\n",
       "0                        -0.075658                         local anesthetic   \n",
       "1                         0.018563          cannabinoid receptor antagonist   \n",
       "2                         0.052914                                      NaN   \n",
       "3                         0.249977                    interleukin inhibitor   \n",
       "4                         0.335890  bacterial cell wall synthesis inhibitor   \n",
       "\n",
       "   Metadata_mmoles_per_liter2  control_type  \\\n",
       "0                        6.05           NaN   \n",
       "1                       10.00           NaN   \n",
       "2                       10.00           NaN   \n",
       "3                       10.00           NaN   \n",
       "4                        4.39           NaN   \n",
       "\n",
       "                                              SMILES  \n",
       "0                     CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC  \n",
       "1       COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C  \n",
       "2                       COc1cc(O)cc(\\C=C\\c2ccccc2)c1  \n",
       "3  COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...  \n",
       "4  CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...  \n",
       "\n",
       "[5 rows x 906 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CP_CSV_matched_filter = CP_CSV_matched_filter.drop(columns=['Metadata_pert_iname', 'Metadata_Sample_Dose', \\\n",
    "    'Metadata_pert_iname2', 'Metadata_target', 'pert_type'])\n",
    "CP_CSV_matched_filter.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Metadata_Plate</th>\n",
       "      <th>Cells_AreaShape_Compactness</th>\n",
       "      <th>Cells_AreaShape_EulerNumber</th>\n",
       "      <th>Cells_AreaShape_Extent</th>\n",
       "      <th>Cells_AreaShape_FormFactor</th>\n",
       "      <th>Cells_AreaShape_MaxFeretDiameter</th>\n",
       "      <th>Cells_AreaShape_MaximumRadius</th>\n",
       "      <th>Cells_AreaShape_Solidity</th>\n",
       "      <th>Cells_AreaShape_Zernike_0_0</th>\n",
       "      <th>Cells_AreaShape_Zernike_1_1</th>\n",
       "      <th>...</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_RNA_5_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_ER_3_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_Mito_5_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_RNA_10_0</th>\n",
       "      <th>Nuclei_Texture_Variance_AGP_5_0</th>\n",
       "      <th>Nuclei_Texture_Variance_ER_5_0</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_5_0</th>\n",
       "      <th>Metadata_moa</th>\n",
       "      <th>Metadata_mmoles_per_liter2</th>\n",
       "      <th>SMILES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24277</td>\n",
       "      <td>0.256710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.114990</td>\n",
       "      <td>-0.237090</td>\n",
       "      <td>0.615594</td>\n",
       "      <td>0.550434</td>\n",
       "      <td>0.072795</td>\n",
       "      <td>-0.210908</td>\n",
       "      <td>0.008488</td>\n",
       "      <td>...</td>\n",
       "      <td>0.118997</td>\n",
       "      <td>-0.156442</td>\n",
       "      <td>-0.018014</td>\n",
       "      <td>-0.024573</td>\n",
       "      <td>-0.383890</td>\n",
       "      <td>-0.199967</td>\n",
       "      <td>-0.075658</td>\n",
       "      <td>local anesthetic</td>\n",
       "      <td>6.05</td>\n",
       "      <td>CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>24277</td>\n",
       "      <td>0.050962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.051053</td>\n",
       "      <td>-0.033733</td>\n",
       "      <td>0.271953</td>\n",
       "      <td>0.172714</td>\n",
       "      <td>0.145941</td>\n",
       "      <td>-0.039057</td>\n",
       "      <td>-0.070826</td>\n",
       "      <td>...</td>\n",
       "      <td>0.065822</td>\n",
       "      <td>-0.113721</td>\n",
       "      <td>-0.089807</td>\n",
       "      <td>-0.041392</td>\n",
       "      <td>-0.248967</td>\n",
       "      <td>-0.126183</td>\n",
       "      <td>0.018563</td>\n",
       "      <td>cannabinoid receptor antagonist</td>\n",
       "      <td>10.00</td>\n",
       "      <td>COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24277</td>\n",
       "      <td>-0.098185</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.044212</td>\n",
       "      <td>0.164668</td>\n",
       "      <td>0.011985</td>\n",
       "      <td>0.127098</td>\n",
       "      <td>0.094736</td>\n",
       "      <td>0.078257</td>\n",
       "      <td>0.119333</td>\n",
       "      <td>...</td>\n",
       "      <td>0.079777</td>\n",
       "      <td>-0.007979</td>\n",
       "      <td>0.081155</td>\n",
       "      <td>-0.089633</td>\n",
       "      <td>0.043140</td>\n",
       "      <td>-0.034355</td>\n",
       "      <td>0.052914</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>COc1cc(O)cc(\\C=C\\c2ccccc2)c1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24277</td>\n",
       "      <td>0.410722</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.236208</td>\n",
       "      <td>-0.055084</td>\n",
       "      <td>0.694648</td>\n",
       "      <td>0.516785</td>\n",
       "      <td>0.154239</td>\n",
       "      <td>-0.347572</td>\n",
       "      <td>-0.172400</td>\n",
       "      <td>...</td>\n",
       "      <td>0.339100</td>\n",
       "      <td>-0.034251</td>\n",
       "      <td>-0.047597</td>\n",
       "      <td>0.103611</td>\n",
       "      <td>-0.139579</td>\n",
       "      <td>-0.042241</td>\n",
       "      <td>0.249977</td>\n",
       "      <td>interleukin inhibitor</td>\n",
       "      <td>10.00</td>\n",
       "      <td>COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24277</td>\n",
       "      <td>0.248559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.020058</td>\n",
       "      <td>0.085772</td>\n",
       "      <td>0.678742</td>\n",
       "      <td>0.671897</td>\n",
       "      <td>0.214587</td>\n",
       "      <td>-0.221396</td>\n",
       "      <td>-0.086168</td>\n",
       "      <td>...</td>\n",
       "      <td>0.415623</td>\n",
       "      <td>0.257598</td>\n",
       "      <td>0.193370</td>\n",
       "      <td>0.238471</td>\n",
       "      <td>-0.033797</td>\n",
       "      <td>0.080018</td>\n",
       "      <td>0.335890</td>\n",
       "      <td>bacterial cell wall synthesis inhibitor</td>\n",
       "      <td>4.39</td>\n",
       "      <td>CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 898 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Metadata_Plate  Cells_AreaShape_Compactness  Cells_AreaShape_EulerNumber  \\\n",
       "0           24277                     0.256710                          NaN   \n",
       "1           24277                     0.050962                          NaN   \n",
       "2           24277                    -0.098185                          NaN   \n",
       "3           24277                     0.410722                          NaN   \n",
       "4           24277                     0.248559                          NaN   \n",
       "\n",
       "   Cells_AreaShape_Extent  Cells_AreaShape_FormFactor  \\\n",
       "0               -0.114990                   -0.237090   \n",
       "1                0.051053                   -0.033733   \n",
       "2                0.044212                    0.164668   \n",
       "3               -0.236208                   -0.055084   \n",
       "4               -0.020058                    0.085772   \n",
       "\n",
       "   Cells_AreaShape_MaxFeretDiameter  Cells_AreaShape_MaximumRadius  \\\n",
       "0                          0.615594                       0.550434   \n",
       "1                          0.271953                       0.172714   \n",
       "2                          0.011985                       0.127098   \n",
       "3                          0.694648                       0.516785   \n",
       "4                          0.678742                       0.671897   \n",
       "\n",
       "   Cells_AreaShape_Solidity  Cells_AreaShape_Zernike_0_0  \\\n",
       "0                  0.072795                    -0.210908   \n",
       "1                  0.145941                    -0.039057   \n",
       "2                  0.094736                     0.078257   \n",
       "3                  0.154239                    -0.347572   \n",
       "4                  0.214587                    -0.221396   \n",
       "\n",
       "   Cells_AreaShape_Zernike_1_1  ...  Nuclei_Texture_SumEntropy_RNA_5_0  \\\n",
       "0                     0.008488  ...                           0.118997   \n",
       "1                    -0.070826  ...                           0.065822   \n",
       "2                     0.119333  ...                           0.079777   \n",
       "3                    -0.172400  ...                           0.339100   \n",
       "4                    -0.086168  ...                           0.415623   \n",
       "\n",
       "   Nuclei_Texture_SumVariance_ER_3_0  Nuclei_Texture_SumVariance_Mito_5_0  \\\n",
       "0                          -0.156442                            -0.018014   \n",
       "1                          -0.113721                            -0.089807   \n",
       "2                          -0.007979                             0.081155   \n",
       "3                          -0.034251                            -0.047597   \n",
       "4                           0.257598                             0.193370   \n",
       "\n",
       "   Nuclei_Texture_SumVariance_RNA_10_0  Nuclei_Texture_Variance_AGP_5_0  \\\n",
       "0                            -0.024573                        -0.383890   \n",
       "1                            -0.041392                        -0.248967   \n",
       "2                            -0.089633                         0.043140   \n",
       "3                             0.103611                        -0.139579   \n",
       "4                             0.238471                        -0.033797   \n",
       "\n",
       "   Nuclei_Texture_Variance_ER_5_0  Nuclei_Texture_Variance_RNA_5_0  \\\n",
       "0                       -0.199967                        -0.075658   \n",
       "1                       -0.126183                         0.018563   \n",
       "2                       -0.034355                         0.052914   \n",
       "3                       -0.042241                         0.249977   \n",
       "4                        0.080018                         0.335890   \n",
       "\n",
       "                              Metadata_moa  Metadata_mmoles_per_liter2  \\\n",
       "0                         local anesthetic                        6.05   \n",
       "1          cannabinoid receptor antagonist                       10.00   \n",
       "2                                      NaN                       10.00   \n",
       "3                    interleukin inhibitor                       10.00   \n",
       "4  bacterial cell wall synthesis inhibitor                        4.39   \n",
       "\n",
       "                                              SMILES  \n",
       "0                     CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC  \n",
       "1       COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C  \n",
       "2                       COc1cc(O)cc(\\C=C\\c2ccccc2)c1  \n",
       "3  COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...  \n",
       "4  CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...  \n",
       "\n",
       "[5 rows x 898 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CP_CSV_matched_filter = CP_CSV_matched_filter.drop(columns=['Metadata_pert_mfc_id', 'Metadata_pert_type', 'control_type', \\\n",
    "    'Metadata_pert_well', 'Metadata_pert_id_vendor', 'Metadata_cell_id', 'Metadata_broad_sample_type', 'Metadata_pert_vehicle'])\n",
    "CP_CSV_matched_filter.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Metadata_moa</th>\n",
       "      <th>Metadata_mmoles_per_liter2</th>\n",
       "      <th>SMILES</th>\n",
       "      <th>Metadata_Plate</th>\n",
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       "      <th>Cells_AreaShape_Extent</th>\n",
       "      <th>Cells_AreaShape_FormFactor</th>\n",
       "      <th>Cells_AreaShape_MaxFeretDiameter</th>\n",
       "      <th>Cells_AreaShape_MaximumRadius</th>\n",
       "      <th>...</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_DNA_5_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_ER_3_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_Mito_3_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_RNA_5_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_ER_3_0</th>\n",
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       "      <th>Nuclei_Texture_SumVariance_RNA_10_0</th>\n",
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       "      <th>Nuclei_Texture_Variance_RNA_5_0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>local anesthetic</td>\n",
       "      <td>6.05</td>\n",
       "      <td>CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC</td>\n",
       "      <td>24277</td>\n",
       "      <td>0.256710</td>\n",
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       "      <td>-0.114990</td>\n",
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       "      <td>0.615594</td>\n",
       "      <td>0.550434</td>\n",
       "      <td>...</td>\n",
       "      <td>0.090021</td>\n",
       "      <td>0.375747</td>\n",
       "      <td>-0.010427</td>\n",
       "      <td>0.118997</td>\n",
       "      <td>-0.156442</td>\n",
       "      <td>-0.018014</td>\n",
       "      <td>-0.024573</td>\n",
       "      <td>-0.383890</td>\n",
       "      <td>-0.199967</td>\n",
       "      <td>-0.075658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>cannabinoid receptor antagonist</td>\n",
       "      <td>10.00</td>\n",
       "      <td>COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C</td>\n",
       "      <td>24277</td>\n",
       "      <td>0.050962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.051053</td>\n",
       "      <td>-0.033733</td>\n",
       "      <td>0.271953</td>\n",
       "      <td>0.172714</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.030338</td>\n",
       "      <td>0.390687</td>\n",
       "      <td>-0.058560</td>\n",
       "      <td>0.065822</td>\n",
       "      <td>-0.113721</td>\n",
       "      <td>-0.089807</td>\n",
       "      <td>-0.041392</td>\n",
       "      <td>-0.248967</td>\n",
       "      <td>-0.126183</td>\n",
       "      <td>0.018563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>COc1cc(O)cc(\\C=C\\c2ccccc2)c1</td>\n",
       "      <td>24277</td>\n",
       "      <td>-0.098185</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.044212</td>\n",
       "      <td>0.164668</td>\n",
       "      <td>0.011985</td>\n",
       "      <td>0.127098</td>\n",
       "      <td>...</td>\n",
       "      <td>0.102946</td>\n",
       "      <td>0.279148</td>\n",
       "      <td>0.029891</td>\n",
       "      <td>0.079777</td>\n",
       "      <td>-0.007979</td>\n",
       "      <td>0.081155</td>\n",
       "      <td>-0.089633</td>\n",
       "      <td>0.043140</td>\n",
       "      <td>-0.034355</td>\n",
       "      <td>0.052914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>interleukin inhibitor</td>\n",
       "      <td>10.00</td>\n",
       "      <td>COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...</td>\n",
       "      <td>24277</td>\n",
       "      <td>0.410722</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.236208</td>\n",
       "      <td>-0.055084</td>\n",
       "      <td>0.694648</td>\n",
       "      <td>0.516785</td>\n",
       "      <td>...</td>\n",
       "      <td>0.470516</td>\n",
       "      <td>0.214792</td>\n",
       "      <td>0.015408</td>\n",
       "      <td>0.339100</td>\n",
       "      <td>-0.034251</td>\n",
       "      <td>-0.047597</td>\n",
       "      <td>0.103611</td>\n",
       "      <td>-0.139579</td>\n",
       "      <td>-0.042241</td>\n",
       "      <td>0.249977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bacterial cell wall synthesis inhibitor</td>\n",
       "      <td>4.39</td>\n",
       "      <td>CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...</td>\n",
       "      <td>24277</td>\n",
       "      <td>0.248559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.020058</td>\n",
       "      <td>0.085772</td>\n",
       "      <td>0.678742</td>\n",
       "      <td>0.671897</td>\n",
       "      <td>...</td>\n",
       "      <td>0.671790</td>\n",
       "      <td>0.424186</td>\n",
       "      <td>0.118873</td>\n",
       "      <td>0.415623</td>\n",
       "      <td>0.257598</td>\n",
       "      <td>0.193370</td>\n",
       "      <td>0.238471</td>\n",
       "      <td>-0.033797</td>\n",
       "      <td>0.080018</td>\n",
       "      <td>0.335890</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 898 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              Metadata_moa  Metadata_mmoles_per_liter2  \\\n",
       "0                         local anesthetic                        6.05   \n",
       "1          cannabinoid receptor antagonist                       10.00   \n",
       "2                                      NaN                       10.00   \n",
       "3                    interleukin inhibitor                       10.00   \n",
       "4  bacterial cell wall synthesis inhibitor                        4.39   \n",
       "\n",
       "                                              SMILES  Metadata_Plate  \\\n",
       "0                     CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC           24277   \n",
       "1       COc1cc(C)cc(OC)c1[C@@H]1C=C(C)CC[C@H]1C(C)=C           24277   \n",
       "2                       COc1cc(O)cc(\\C=C\\c2ccccc2)c1           24277   \n",
       "3  COc1c(O)cc2C(=O)O[C@H]3[C@@H](O)[C@H](O)[C@@H]...           24277   \n",
       "4  CCOc1ccc2ccccc2c1C(=O)N[C@H]1[C@H]2SC(C)(C)[C@...           24277   \n",
       "\n",
       "   Cells_AreaShape_Compactness  Cells_AreaShape_EulerNumber  \\\n",
       "0                     0.256710                          NaN   \n",
       "1                     0.050962                          NaN   \n",
       "2                    -0.098185                          NaN   \n",
       "3                     0.410722                          NaN   \n",
       "4                     0.248559                          NaN   \n",
       "\n",
       "   Cells_AreaShape_Extent  Cells_AreaShape_FormFactor  \\\n",
       "0               -0.114990                   -0.237090   \n",
       "1                0.051053                   -0.033733   \n",
       "2                0.044212                    0.164668   \n",
       "3               -0.236208                   -0.055084   \n",
       "4               -0.020058                    0.085772   \n",
       "\n",
       "   Cells_AreaShape_MaxFeretDiameter  Cells_AreaShape_MaximumRadius  ...  \\\n",
       "0                          0.615594                       0.550434  ...   \n",
       "1                          0.271953                       0.172714  ...   \n",
       "2                          0.011985                       0.127098  ...   \n",
       "3                          0.694648                       0.516785  ...   \n",
       "4                          0.678742                       0.671897  ...   \n",
       "\n",
       "   Nuclei_Texture_SumEntropy_DNA_5_0  Nuclei_Texture_SumEntropy_ER_3_0  \\\n",
       "0                           0.090021                          0.375747   \n",
       "1                          -0.030338                          0.390687   \n",
       "2                           0.102946                          0.279148   \n",
       "3                           0.470516                          0.214792   \n",
       "4                           0.671790                          0.424186   \n",
       "\n",
       "   Nuclei_Texture_SumEntropy_Mito_3_0  Nuclei_Texture_SumEntropy_RNA_5_0  \\\n",
       "0                           -0.010427                           0.118997   \n",
       "1                           -0.058560                           0.065822   \n",
       "2                            0.029891                           0.079777   \n",
       "3                            0.015408                           0.339100   \n",
       "4                            0.118873                           0.415623   \n",
       "\n",
       "   Nuclei_Texture_SumVariance_ER_3_0  Nuclei_Texture_SumVariance_Mito_5_0  \\\n",
       "0                          -0.156442                            -0.018014   \n",
       "1                          -0.113721                            -0.089807   \n",
       "2                          -0.007979                             0.081155   \n",
       "3                          -0.034251                            -0.047597   \n",
       "4                           0.257598                             0.193370   \n",
       "\n",
       "   Nuclei_Texture_SumVariance_RNA_10_0  Nuclei_Texture_Variance_AGP_5_0  \\\n",
       "0                            -0.024573                        -0.383890   \n",
       "1                            -0.041392                        -0.248967   \n",
       "2                            -0.089633                         0.043140   \n",
       "3                             0.103611                        -0.139579   \n",
       "4                             0.238471                        -0.033797   \n",
       "\n",
       "   Nuclei_Texture_Variance_ER_5_0  Nuclei_Texture_Variance_RNA_5_0  \n",
       "0                       -0.199967                        -0.075658  \n",
       "1                       -0.126183                         0.018563  \n",
       "2                       -0.034355                         0.052914  \n",
       "3                       -0.042241                         0.249977  \n",
       "4                        0.080018                         0.335890  \n",
       "\n",
       "[5 rows x 898 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 把最后3列移动到前面\n",
    "cols = CP_CSV_matched_filter.columns.tolist()\n",
    "cols = cols[-3:] + cols[:-3]   # 取最后3列 + 前面所有列\n",
    "CP_CSV_matched_filter = CP_CSV_matched_filter[cols]\n",
    "CP_CSV_matched_filter.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NaN count in SMILES: 26572\n",
      "NaN ratio in SMILES: 23.43%\n"
     ]
    }
   ],
   "source": [
    "# 统计 NaN 数量\n",
    "nan_count = CP_CSV_matched_filter['SMILES'].isna().sum()\n",
    "print(f\"NaN count in SMILES: {nan_count}\")\n",
    "\n",
    "# 也可以看比例\n",
    "nan_ratio = nan_count / len(CP_CSV_matched_filter)\n",
    "print(f\"NaN ratio in SMILES: {nan_ratio:.2%}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>SMILES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DMSO</td>\n",
       "      <td>26572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CC(C)(C)NC[C@@H](O)COc1cccc2C(=O)CCCc12</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CC(C)NCC(O)COc1cccc2[nH]ccc12</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>COCC(=O)O[C@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2c...</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>COc1c(oc2cc3oc(=O)ccc3cc12)C(C)C</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20337</th>\n",
       "      <td>OC[C@H]1O[C@@H](CC(=O)N2CCCCC2)C[C@@H]2[C@H]1O...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20338</th>\n",
       "      <td>OC[C@@H]1O[C@H](CC(=O)N2CCCCC2)C[C@H]2[C@@H]1O...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20339</th>\n",
       "      <td>OC[C@H]1O[C@H](CC(=O)N2CCCCC2)C[C@@H]2[C@H]1Oc...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20340</th>\n",
       "      <td>OC[C@@H]1O[C@@H](CC(=O)N2CCCCC2)C[C@H]2[C@@H]1...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20341</th>\n",
       "      <td>CS(=O)(=O)Nc1ccc2O[C@H]3[C@H](C[C@H](CC(=O)NCc...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20342 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   index  SMILES\n",
       "0                                                   DMSO   26572\n",
       "1                CC(C)(C)NC[C@@H](O)COc1cccc2C(=O)CCCc12      16\n",
       "2                          CC(C)NCC(O)COc1cccc2[nH]ccc12      16\n",
       "3      COCC(=O)O[C@]1(CCN(C)CCCc2nc3ccccc3[nH]2)CCc2c...      12\n",
       "4                       COc1c(oc2cc3oc(=O)ccc3cc12)C(C)C      12\n",
       "...                                                  ...     ...\n",
       "20337  OC[C@H]1O[C@@H](CC(=O)N2CCCCC2)C[C@@H]2[C@H]1O...       1\n",
       "20338  OC[C@@H]1O[C@H](CC(=O)N2CCCCC2)C[C@H]2[C@@H]1O...       1\n",
       "20339  OC[C@H]1O[C@H](CC(=O)N2CCCCC2)C[C@@H]2[C@H]1Oc...       1\n",
       "20340  OC[C@@H]1O[C@@H](CC(=O)N2CCCCC2)C[C@H]2[C@@H]1...       1\n",
       "20341  CS(=O)(=O)Nc1ccc2O[C@H]3[C@H](C[C@H](CC(=O)NCc...       1\n",
       "\n",
       "[20342 rows x 2 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CP_CSV_matched_filter['SMILES'] = CP_CSV_matched_filter['SMILES'].fillna(\"DMSO\")\n",
    "\n",
    "CP_CSV_matched_filter['SMILES'].value_counts().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "CP_CSV_matched_filter.to_parquet('./CP_data.parquet', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 处理基因表达"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>221227_x_at</th>\n",
       "      <th>212345_s_at</th>\n",
       "      <th>218597_s_at</th>\n",
       "      <th>217140_s_at</th>\n",
       "      <th>209253_at</th>\n",
       "      <th>214404_x_at</th>\n",
       "      <th>219888_at</th>\n",
       "      <th>201225_s_at</th>\n",
       "      <th>202535_at</th>\n",
       "      <th>219499_at</th>\n",
       "      <th>...</th>\n",
       "      <th>pert_dose</th>\n",
       "      <th>det_plate</th>\n",
       "      <th>BROAD_CPD_ID</th>\n",
       "      <th>CPD_NAME</th>\n",
       "      <th>CPD_TYPE</th>\n",
       "      <th>CPD_SMILES</th>\n",
       "      <th>pert_id_dose</th>\n",
       "      <th>pert_sample_dose</th>\n",
       "      <th>pert_type</th>\n",
       "      <th>control_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.118505</td>\n",
       "      <td>-0.293445</td>\n",
       "      <td>-0.294088</td>\n",
       "      <td>0.292745</td>\n",
       "      <td>-0.145896</td>\n",
       "      <td>0.97358</td>\n",
       "      <td>0.247915</td>\n",
       "      <td>-0.159028</td>\n",
       "      <td>-1.249049</td>\n",
       "      <td>0.357185</td>\n",
       "      <td>...</td>\n",
       "      <td>50.0</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>BRD-K07762753</td>\n",
       "      <td>aminopurvalanol A</td>\n",
       "      <td>BIO</td>\n",
       "      <td>CC(C)[C@H](CO)Nc1nc(Nc2cc(N)cc(Cl)c2)c2ncn(C(C...</td>\n",
       "      <td>BRD-K07762753_50.0</td>\n",
       "      <td>BRD-K07762753-001-03-6_50.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.043264</td>\n",
       "      <td>-0.264945</td>\n",
       "      <td>-0.000633</td>\n",
       "      <td>0.000935</td>\n",
       "      <td>0.177604</td>\n",
       "      <td>-0.50472</td>\n",
       "      <td>0.214315</td>\n",
       "      <td>0.144271</td>\n",
       "      <td>0.106551</td>\n",
       "      <td>-0.051834</td>\n",
       "      <td>...</td>\n",
       "      <td>12.7</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>BRD-K09991945</td>\n",
       "      <td>GSK-3 inhibitor II</td>\n",
       "      <td>BIO</td>\n",
       "      <td>Ic1cccc(CSc2nnc(o2)-c2ccncc2)c1</td>\n",
       "      <td>BRD-K09991945_12.7</td>\n",
       "      <td>BRD-K09991945-001-02-0_12.7</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.070805</td>\n",
       "      <td>0.195755</td>\n",
       "      <td>0.004606</td>\n",
       "      <td>-0.040855</td>\n",
       "      <td>-0.067346</td>\n",
       "      <td>-0.19872</td>\n",
       "      <td>-0.053195</td>\n",
       "      <td>0.167971</td>\n",
       "      <td>-0.215449</td>\n",
       "      <td>-0.273714</td>\n",
       "      <td>...</td>\n",
       "      <td>50.0</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>BRD-K46678324</td>\n",
       "      <td>RHO-kinase inhibitor II</td>\n",
       "      <td>BIO</td>\n",
       "      <td>Clc1cc(Cl)c(NC(=O)Nc2ccncc2)c(Cl)c1</td>\n",
       "      <td>BRD-K46678324_50.0</td>\n",
       "      <td>BRD-K46678324-001-03-7_50.0</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.027165</td>\n",
       "      <td>-0.149545</td>\n",
       "      <td>0.173113</td>\n",
       "      <td>-0.100695</td>\n",
       "      <td>-0.309296</td>\n",
       "      <td>-0.20782</td>\n",
       "      <td>-0.323985</td>\n",
       "      <td>0.294872</td>\n",
       "      <td>-0.371449</td>\n",
       "      <td>-0.099914</td>\n",
       "      <td>...</td>\n",
       "      <td>16.2</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>BRD-K67860401</td>\n",
       "      <td>GSK-3beta inhibitor VIII</td>\n",
       "      <td>BIO</td>\n",
       "      <td>COc1ccc(CNC(=O)Nc2ncc(s2)[N+]([O-])=O)cc1</td>\n",
       "      <td>BRD-K67860401_16.2</td>\n",
       "      <td>BRD-K67860401-001-02-3_16.2</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.303294</td>\n",
       "      <td>0.254455</td>\n",
       "      <td>-0.055418</td>\n",
       "      <td>-0.053635</td>\n",
       "      <td>0.000455</td>\n",
       "      <td>-0.10908</td>\n",
       "      <td>0.031425</td>\n",
       "      <td>0.044482</td>\n",
       "      <td>0.223351</td>\n",
       "      <td>0.163186</td>\n",
       "      <td>...</td>\n",
       "      <td>12.5</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>BRD-K52620403</td>\n",
       "      <td>STO 609</td>\n",
       "      <td>BIO</td>\n",
       "      <td>OC(=O)c1ccc2c3nc4ccccc4n3c(=O)c3cccc1c23</td>\n",
       "      <td>BRD-K52620403_12.5</td>\n",
       "      <td>BRD-K52620403-001-01-8_12.5</td>\n",
       "      <td>trt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 988 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   221227_x_at  212345_s_at  218597_s_at  217140_s_at  209253_at  214404_x_at  \\\n",
       "0    -0.118505    -0.293445    -0.294088     0.292745  -0.145896      0.97358   \n",
       "1     0.043264    -0.264945    -0.000633     0.000935   0.177604     -0.50472   \n",
       "2    -0.070805     0.195755     0.004606    -0.040855  -0.067346     -0.19872   \n",
       "3     0.027165    -0.149545     0.173113    -0.100695  -0.309296     -0.20782   \n",
       "4     0.303294     0.254455    -0.055418    -0.053635   0.000455     -0.10908   \n",
       "\n",
       "   219888_at  201225_s_at  202535_at  219499_at  ...  pert_dose  \\\n",
       "0   0.247915    -0.159028  -1.249049   0.357185  ...       50.0   \n",
       "1   0.214315     0.144271   0.106551  -0.051834  ...       12.7   \n",
       "2  -0.053195     0.167971  -0.215449  -0.273714  ...       50.0   \n",
       "3  -0.323985     0.294872  -0.371449  -0.099914  ...       16.2   \n",
       "4   0.031425     0.044482   0.223351   0.163186  ...       12.5   \n",
       "\n",
       "                       det_plate   BROAD_CPD_ID                  CPD_NAME  \\\n",
       "0  PAC001_U2OS_6H_X1_B1_UNI4445L  BRD-K07762753         aminopurvalanol A   \n",
       "1  PAC001_U2OS_6H_X1_B1_UNI4445L  BRD-K09991945        GSK-3 inhibitor II   \n",
       "2  PAC001_U2OS_6H_X1_B1_UNI4445L  BRD-K46678324   RHO-kinase inhibitor II   \n",
       "3  PAC001_U2OS_6H_X1_B1_UNI4445L  BRD-K67860401  GSK-3beta inhibitor VIII   \n",
       "4  PAC001_U2OS_6H_X1_B1_UNI4445L  BRD-K52620403                   STO 609   \n",
       "\n",
       "   CPD_TYPE                                         CPD_SMILES  \\\n",
       "0       BIO  CC(C)[C@H](CO)Nc1nc(Nc2cc(N)cc(Cl)c2)c2ncn(C(C...   \n",
       "1       BIO                    Ic1cccc(CSc2nnc(o2)-c2ccncc2)c1   \n",
       "2       BIO                Clc1cc(Cl)c(NC(=O)Nc2ccncc2)c(Cl)c1   \n",
       "3       BIO          COc1ccc(CNC(=O)Nc2ncc(s2)[N+]([O-])=O)cc1   \n",
       "4       BIO           OC(=O)c1ccc2c3nc4ccccc4n3c(=O)c3cccc1c23   \n",
       "\n",
       "         pert_id_dose             pert_sample_dose  pert_type  control_type  \n",
       "0  BRD-K07762753_50.0  BRD-K07762753-001-03-6_50.0        trt           NaN  \n",
       "1  BRD-K09991945_12.7  BRD-K09991945-001-02-0_12.7        trt           NaN  \n",
       "2  BRD-K46678324_50.0  BRD-K46678324-001-03-7_50.0        trt           NaN  \n",
       "3  BRD-K67860401_16.2  BRD-K67860401-001-02-3_16.2        trt           NaN  \n",
       "4  BRD-K52620403_12.5  BRD-K52620403-001-01-8_12.5        trt           NaN  \n",
       "\n",
       "[5 rows x 988 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GE_CSV.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>pert_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "     index  pert_type\n",
       "0      trt      64642\n",
       "1  control       3478"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "GE_CSV['pert_type'].value_counts().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>221227_x_at</th>\n",
       "      <th>212345_s_at</th>\n",
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       "      <td>0.247915</td>\n",
       "      <td>-0.159028</td>\n",
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       "      <td>0.357185</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.97559</td>\n",
       "      <td>-1.740605</td>\n",
       "      <td>0.340382</td>\n",
       "      <td>0.498778</td>\n",
       "      <td>0.352152</td>\n",
       "      <td>0.53591</td>\n",
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       "      <td>50.0</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>CC(C)[C@H](CO)Nc1nc(Nc2cc(N)cc(Cl)c2)c2ncn(C(C...</td>\n",
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       "      <td>0.043264</td>\n",
       "      <td>-0.264945</td>\n",
       "      <td>-0.000633</td>\n",
       "      <td>0.000935</td>\n",
       "      <td>0.177604</td>\n",
       "      <td>-0.50472</td>\n",
       "      <td>0.214315</td>\n",
       "      <td>0.144271</td>\n",
       "      <td>0.106551</td>\n",
       "      <td>-0.051834</td>\n",
       "      <td>...</td>\n",
       "      <td>0.25051</td>\n",
       "      <td>-0.025625</td>\n",
       "      <td>-0.024428</td>\n",
       "      <td>-0.225122</td>\n",
       "      <td>0.533052</td>\n",
       "      <td>-0.19329</td>\n",
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       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>Ic1cccc(CSc2nnc(o2)-c2ccncc2)c1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.070805</td>\n",
       "      <td>0.195755</td>\n",
       "      <td>0.004606</td>\n",
       "      <td>-0.040855</td>\n",
       "      <td>-0.067346</td>\n",
       "      <td>-0.19872</td>\n",
       "      <td>-0.053195</td>\n",
       "      <td>0.167971</td>\n",
       "      <td>-0.215449</td>\n",
       "      <td>-0.273714</td>\n",
       "      <td>...</td>\n",
       "      <td>0.05681</td>\n",
       "      <td>0.130695</td>\n",
       "      <td>0.005919</td>\n",
       "      <td>-0.408722</td>\n",
       "      <td>-0.057177</td>\n",
       "      <td>-0.25699</td>\n",
       "      <td>0.31004</td>\n",
       "      <td>50.0</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>Clc1cc(Cl)c(NC(=O)Nc2ccncc2)c(Cl)c1</td>\n",
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       "      <th>3</th>\n",
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       "      <td>-0.149545</td>\n",
       "      <td>0.173113</td>\n",
       "      <td>-0.100695</td>\n",
       "      <td>-0.309296</td>\n",
       "      <td>-0.20782</td>\n",
       "      <td>-0.323985</td>\n",
       "      <td>0.294872</td>\n",
       "      <td>-0.371449</td>\n",
       "      <td>-0.099914</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.16129</td>\n",
       "      <td>0.365195</td>\n",
       "      <td>-0.040848</td>\n",
       "      <td>-0.251122</td>\n",
       "      <td>0.040732</td>\n",
       "      <td>0.17091</td>\n",
       "      <td>-0.05144</td>\n",
       "      <td>16.2</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>COc1ccc(CNC(=O)Nc2ncc(s2)[N+]([O-])=O)cc1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>-0.055418</td>\n",
       "      <td>-0.053635</td>\n",
       "      <td>0.000455</td>\n",
       "      <td>-0.10908</td>\n",
       "      <td>0.031425</td>\n",
       "      <td>0.044482</td>\n",
       "      <td>0.223351</td>\n",
       "      <td>0.163186</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00784</td>\n",
       "      <td>0.093595</td>\n",
       "      <td>-0.303418</td>\n",
       "      <td>0.474878</td>\n",
       "      <td>-0.022947</td>\n",
       "      <td>-0.28589</td>\n",
       "      <td>0.06423</td>\n",
       "      <td>12.5</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>OC(=O)c1ccc2c3nc4ccccc4n3c(=O)c3cccc1c23</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 980 columns</p>\n",
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       "   221227_x_at  212345_s_at  218597_s_at  217140_s_at  209253_at  214404_x_at  \\\n",
       "0    -0.118505    -0.293445    -0.294088     0.292745  -0.145896      0.97358   \n",
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       "2    -0.070805     0.195755     0.004606    -0.040855  -0.067346     -0.19872   \n",
       "3     0.027165    -0.149545     0.173113    -0.100695  -0.309296     -0.20782   \n",
       "4     0.303294     0.254455    -0.055418    -0.053635   0.000455     -0.10908   \n",
       "\n",
       "   219888_at  201225_s_at  202535_at  219499_at  ...  211071_s_at  203341_at  \\\n",
       "0   0.247915    -0.159028  -1.249049   0.357185  ...     -0.97559  -1.740605   \n",
       "1   0.214315     0.144271   0.106551  -0.051834  ...      0.25051  -0.025625   \n",
       "2  -0.053195     0.167971  -0.215449  -0.273714  ...      0.05681   0.130695   \n",
       "3  -0.323985     0.294872  -0.371449  -0.099914  ...     -0.16129   0.365195   \n",
       "4   0.031425     0.044482   0.223351   0.163186  ...      0.00784   0.093595   \n",
       "\n",
       "   202801_at  206414_s_at  204978_at  205379_at  203897_at  pert_dose  \\\n",
       "0   0.340382     0.498778   0.352152    0.53591    0.52484       50.0   \n",
       "1  -0.024428    -0.225122   0.533052   -0.19329   -0.25436       12.7   \n",
       "2   0.005919    -0.408722  -0.057177   -0.25699    0.31004       50.0   \n",
       "3  -0.040848    -0.251122   0.040732    0.17091   -0.05144       16.2   \n",
       "4  -0.303418     0.474878  -0.022947   -0.28589    0.06423       12.5   \n",
       "\n",
       "                       det_plate  \\\n",
       "0  PAC001_U2OS_6H_X1_B1_UNI4445L   \n",
       "1  PAC001_U2OS_6H_X1_B1_UNI4445L   \n",
       "2  PAC001_U2OS_6H_X1_B1_UNI4445L   \n",
       "3  PAC001_U2OS_6H_X1_B1_UNI4445L   \n",
       "4  PAC001_U2OS_6H_X1_B1_UNI4445L   \n",
       "\n",
       "                                          CPD_SMILES  \n",
       "0  CC(C)[C@H](CO)Nc1nc(Nc2cc(N)cc(Cl)c2)c2ncn(C(C...  \n",
       "1                    Ic1cccc(CSc2nnc(o2)-c2ccncc2)c1  \n",
       "2                Clc1cc(Cl)c(NC(=O)Nc2ccncc2)c(Cl)c1  \n",
       "3          COc1ccc(CNC(=O)Nc2ncc(s2)[N+]([O-])=O)cc1  \n",
       "4           OC(=O)c1ccc2c3nc4ccccc4n3c(=O)c3cccc1c23  \n",
       "\n",
       "[5 rows x 980 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GE_CSV_filter = GE_CSV.drop(columns=['CPD_TYPE', 'pert_id', 'BROAD_CPD_ID', 'CPD_NAME', 'pert_type', 'control_type', 'pert_sample_dose', 'pert_id_dose'])\n",
    "GE_CSV_filter.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
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       "      <th>pert_dose</th>\n",
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       "      <td>-0.529905</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12.7</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>Ic1cccc(CSc2nnc(o2)-c2ccncc2)c1</td>\n",
       "      <td>0.043264</td>\n",
       "      <td>-0.264945</td>\n",
       "      <td>-0.000633</td>\n",
       "      <td>0.000935</td>\n",
       "      <td>0.177604</td>\n",
       "      <td>-0.50472</td>\n",
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       "      <td>0.228895</td>\n",
       "      <td>-0.381308</td>\n",
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       "      <td>-0.225122</td>\n",
       "      <td>0.533052</td>\n",
       "      <td>-0.19329</td>\n",
       "      <td>-0.25436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>50.0</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>Clc1cc(Cl)c(NC(=O)Nc2ccncc2)c(Cl)c1</td>\n",
       "      <td>-0.070805</td>\n",
       "      <td>0.195755</td>\n",
       "      <td>0.004606</td>\n",
       "      <td>-0.040855</td>\n",
       "      <td>-0.067346</td>\n",
       "      <td>-0.19872</td>\n",
       "      <td>-0.053195</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.031795</td>\n",
       "      <td>-0.051728</td>\n",
       "      <td>-0.017741</td>\n",
       "      <td>0.05681</td>\n",
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       "      <td>0.005919</td>\n",
       "      <td>-0.408722</td>\n",
       "      <td>-0.057177</td>\n",
       "      <td>-0.25699</td>\n",
       "      <td>0.31004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16.2</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>COc1ccc(CNC(=O)Nc2ncc(s2)[N+]([O-])=O)cc1</td>\n",
       "      <td>0.027165</td>\n",
       "      <td>-0.149545</td>\n",
       "      <td>0.173113</td>\n",
       "      <td>-0.100695</td>\n",
       "      <td>-0.309296</td>\n",
       "      <td>-0.20782</td>\n",
       "      <td>-0.323985</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.013787</td>\n",
       "      <td>-0.177608</td>\n",
       "      <td>0.219869</td>\n",
       "      <td>-0.16129</td>\n",
       "      <td>0.365195</td>\n",
       "      <td>-0.040848</td>\n",
       "      <td>-0.251122</td>\n",
       "      <td>0.040732</td>\n",
       "      <td>0.17091</td>\n",
       "      <td>-0.05144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12.5</td>\n",
       "      <td>PAC001_U2OS_6H_X1_B1_UNI4445L</td>\n",
       "      <td>OC(=O)c1ccc2c3nc4ccccc4n3c(=O)c3cccc1c23</td>\n",
       "      <td>0.303294</td>\n",
       "      <td>0.254455</td>\n",
       "      <td>-0.055418</td>\n",
       "      <td>-0.053635</td>\n",
       "      <td>0.000455</td>\n",
       "      <td>-0.10908</td>\n",
       "      <td>0.031425</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.052585</td>\n",
       "      <td>-0.196108</td>\n",
       "      <td>0.245469</td>\n",
       "      <td>0.00784</td>\n",
       "      <td>0.093595</td>\n",
       "      <td>-0.303418</td>\n",
       "      <td>0.474878</td>\n",
       "      <td>-0.022947</td>\n",
       "      <td>-0.28589</td>\n",
       "      <td>0.06423</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 980 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   pert_dose                      det_plate  \\\n",
       "0       50.0  PAC001_U2OS_6H_X1_B1_UNI4445L   \n",
       "1       12.7  PAC001_U2OS_6H_X1_B1_UNI4445L   \n",
       "2       50.0  PAC001_U2OS_6H_X1_B1_UNI4445L   \n",
       "3       16.2  PAC001_U2OS_6H_X1_B1_UNI4445L   \n",
       "4       12.5  PAC001_U2OS_6H_X1_B1_UNI4445L   \n",
       "\n",
       "                                          CPD_SMILES  221227_x_at  \\\n",
       "0  CC(C)[C@H](CO)Nc1nc(Nc2cc(N)cc(Cl)c2)c2ncn(C(C...    -0.118505   \n",
       "1                    Ic1cccc(CSc2nnc(o2)-c2ccncc2)c1     0.043264   \n",
       "2                Clc1cc(Cl)c(NC(=O)Nc2ccncc2)c(Cl)c1    -0.070805   \n",
       "3          COc1ccc(CNC(=O)Nc2ncc(s2)[N+]([O-])=O)cc1     0.027165   \n",
       "4           OC(=O)c1ccc2c3nc4ccccc4n3c(=O)c3cccc1c23     0.303294   \n",
       "\n",
       "   212345_s_at  218597_s_at  217140_s_at  209253_at  214404_x_at  219888_at  \\\n",
       "0    -0.293445    -0.294088     0.292745  -0.145896      0.97358   0.247915   \n",
       "1    -0.264945    -0.000633     0.000935   0.177604     -0.50472   0.214315   \n",
       "2     0.195755     0.004606    -0.040855  -0.067346     -0.19872  -0.053195   \n",
       "3    -0.149545     0.173113    -0.100695  -0.309296     -0.20782  -0.323985   \n",
       "4     0.254455    -0.055418    -0.053635   0.000455     -0.10908   0.031425   \n",
       "\n",
       "   ...  218397_at  202996_at  204608_at  211071_s_at  203341_at  202801_at  \\\n",
       "0  ...  -0.529905   0.804992   0.430269     -0.97559  -1.740605   0.340382   \n",
       "1  ...   0.228895  -0.381308   0.556969      0.25051  -0.025625  -0.024428   \n",
       "2  ...  -0.031795  -0.051728  -0.017741      0.05681   0.130695   0.005919   \n",
       "3  ...  -0.013787  -0.177608   0.219869     -0.16129   0.365195  -0.040848   \n",
       "4  ...  -0.052585  -0.196108   0.245469      0.00784   0.093595  -0.303418   \n",
       "\n",
       "   206414_s_at  204978_at  205379_at  203897_at  \n",
       "0     0.498778   0.352152    0.53591    0.52484  \n",
       "1    -0.225122   0.533052   -0.19329   -0.25436  \n",
       "2    -0.408722  -0.057177   -0.25699    0.31004  \n",
       "3    -0.251122   0.040732    0.17091   -0.05144  \n",
       "4     0.474878  -0.022947   -0.28589    0.06423  \n",
       "\n",
       "[5 rows x 980 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 把最后3列换成前面3列\n",
    "\n",
    "cols = GE_CSV_filter.columns.tolist()\n",
    "cols = cols[-3:] + cols[:-3]\n",
    "GE_CSV_filter = GE_CSV_filter[cols]\n",
    "GE_CSV_filter.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save as GE_data.parquet\n",
    "\n",
    "GE_CSV_filter.to_parquet('./GE_data.parquet', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# GE_CSV_filter.to_csv('./GE_data.csv', index=False)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(68120, 980)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GE_CSV_filter.shape"
   ]
  }
 ],
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