merge_dfs_human_ecoli.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sys\n",
    "import_path_base = '/home/henrike/Documents/PD_AS/src/'\n",
    "sys.path.insert(1, import_path_base + 'PRISM/prism/scripts/')\n",
    "from PrismData import PrismParser, VariantData#VariantParser, VariantData\n",
    "from Bio import AlignIO\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#read in ecoli prism data\n",
    "base_dir = '/home/henrike/Documents/PD_AS/projects/Sofie_Mave/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_from_prism(primsfile):\n",
    "\tparser = PrismParser()\n",
    "\tdataframe = parser.read(primsfile).dataframe\n",
    "\tmeta_data = parser.read_header(primsfile)\n",
    "\treturn meta_data, dataframe\n",
    "\n",
    "def write_prism(metadata, dataframe, prism_file, comment=''):\n",
    "\tvariant_dataset = VariantData(metadata, dataframe)\n",
    "\tparser = PrismParser()\n",
    "\tparser.write(prism_file, variant_dataset, comment_lines=comment)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "ecoli_meta_data, ecoli_df = read_from_prism(base_dir + 'results/prism_mave/prism_mave_thompsen_Ecoli_dhfr.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#remove double mutants\n",
    "ecoli_df = ecoli_df[ecoli_df['n_mut']==1]\n",
    "#and introduce a WT col with WT AA + pos for searching\n",
    "ecoli_df['WT'] = ecoli_df['variant'].apply(lambda x: x[0:-1])\n",
    "#and rename columns\n",
    "ecoli_df = ecoli_df.rename(columns={'variant':'ecoli_variant', 'n_mut':'ecoli_n_mut','aa_ref':'ecoli_aa_ref','resi':'ecoli_resi','aa_var':'ecoli_aa_var','WT':'ecoli_WT'})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "#read in an prepare human dhfr data \n",
    "human_meta_data, human_df = read_from_prism(base_dir + 'data/prism_MAVE_001_DHFR.txt')\n",
    "human_df = human_df[human_df['n_mut']==1]\n",
    "human_df['WT'] = human_df['variant'].apply(lambda x: x[0:-1])\n",
    "human_df = human_df.rename(columns={'variant':'human_variant', 'n_mut':'human_n_mut','aa_ref':'human_aa_ref','resi':'human_resi','aa_var':'human_aa_var','WT':'human_WT'})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#read in alignment\n",
    "s_align = AlignIO.read(open(base_dir + 'results/tcoffee_expresso/result.clustalw_aln'), \"clustal\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#init merged df\n",
    "merge_df = pd.DataFrame(columns=list(human_df.columns)+list(ecoli_df.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "amino_acids = ['H','K','R','D','E','C','M','N','Q','S','T','A','I','L','V','F','W','Y','G','P','*']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "human: M 1 ecoli: - 0\n",
      "human: V 2 ecoli: - 0\n",
      "human: G 3 ecoli: - 0\n",
      "human: S 4 ecoli: M 1\n",
      "human: L 5 ecoli: I 2\n",
      "human: N 6 ecoli: S 3\n",
      "human: C 7 ecoli: L 4\n",
      "human: I 8 ecoli: I 5\n",
      "human: V 9 ecoli: A 6\n",
      "human: A 10 ecoli: A 7\n",
      "human: V 11 ecoli: L 8\n",
      "human: S 12 ecoli: A 9\n",
      "human: Q 13 ecoli: V 10\n",
      "human: N 14 ecoli: D 11\n",
      "human: M 15 ecoli: R 12\n",
      "human: G 16 ecoli: V 13\n",
      "human: I 17 ecoli: I 14\n",
      "human: G 18 ecoli: G 15\n",
      "human: K 19 ecoli: M 16\n",
      "human: N 20 ecoli: E 17\n",
      "human: G 21 ecoli: N 18\n",
      "human: D 22 ecoli: A 19\n",
      "human: L 23 ecoli: M 20\n",
      "human: P 24 ecoli: P 21\n",
      "human: W 25 ecoli: W 22\n",
      "human: P 26 ecoli: N 23\n",
      "human: P 27 ecoli: - 23\n",
      "human: L 28 ecoli: L 24\n",
      "human: R 29 ecoli: P 25\n",
      "human: N 30 ecoli: A 26\n",
      "human: E 31 ecoli: D 27\n",
      "human: F 32 ecoli: L 28\n",
      "human: R 33 ecoli: A 29\n",
      "human: Y 34 ecoli: W 30\n",
      "human: F 35 ecoli: F 31\n",
      "human: Q 36 ecoli: K 32\n",
      "human: R 37 ecoli: R 33\n",
      "human: M 38 ecoli: N 34\n",
      "human: T 39 ecoli: T 35\n",
      "human: T 40 ecoli: L 36\n",
      "human: T 41 ecoli: N 37\n",
      "human: S 42 ecoli: - 37\n",
      "human: S 43 ecoli: - 37\n",
      "human: V 44 ecoli: - 37\n",
      "human: E 45 ecoli: - 37\n",
      "human: G 46 ecoli: - 37\n",
      "human: K 47 ecoli: - 37\n",
      "human: Q 48 ecoli: - 37\n",
      "human: N 49 ecoli: K 38\n",
      "human: L 50 ecoli: P 39\n",
      "human: V 51 ecoli: V 40\n",
      "human: I 52 ecoli: I 41\n",
      "human: M 53 ecoli: M 42\n",
      "human: G 54 ecoli: G 43\n",
      "human: K 55 ecoli: R 44\n",
      "human: K 56 ecoli: H 45\n",
      "human: T 57 ecoli: T 46\n",
      "human: W 58 ecoli: W 47\n",
      "human: F 59 ecoli: E 48\n",
      "human: S 60 ecoli: S 49\n",
      "human: I 61 ecoli: I 50\n",
      "human: P 62 ecoli: G 51\n",
      "human: E 63 ecoli: - 51\n",
      "human: K 64 ecoli: - 51\n",
      "human: N 65 ecoli: - 51\n",
      "human: R 66 ecoli: R 52\n",
      "human: P 67 ecoli: P 53\n",
      "human: L 68 ecoli: L 54\n",
      "human: K 69 ecoli: P 55\n",
      "human: G 70 ecoli: G 56\n",
      "human: R 71 ecoli: R 57\n",
      "human: I 72 ecoli: K 58\n",
      "human: N 73 ecoli: N 59\n",
      "human: L 74 ecoli: I 60\n",
      "human: V 75 ecoli: I 61\n",
      "human: L 76 ecoli: L 62\n",
      "human: S 77 ecoli: S 63\n",
      "human: R 78 ecoli: S 64\n",
      "human: E 79 ecoli: Q 65\n",
      "human: L 80 ecoli: - 65\n",
      "human: K 81 ecoli: - 65\n",
      "human: E 82 ecoli: P 66\n",
      "human: P 83 ecoli: G 67\n",
      "human: P 84 ecoli: T 68\n",
      "human: Q 85 ecoli: D 69\n",
      "human: G 86 ecoli: D 70\n",
      "human: A 87 ecoli: R 71\n",
      "human: H 88 ecoli: V 72\n",
      "human: F 89 ecoli: T 73\n",
      "human: L 90 ecoli: W 74\n",
      "human: S 91 ecoli: V 75\n",
      "human: R 92 ecoli: K 76\n",
      "human: S 93 ecoli: S 77\n",
      "human: L 94 ecoli: V 78\n",
      "human: D 95 ecoli: D 79\n",
      "human: D 96 ecoli: E 80\n",
      "human: A 97 ecoli: A 81\n",
      "human: L 98 ecoli: I 82\n",
      "human: K 99 ecoli: A 83\n",
      "human: L 100 ecoli: A 84\n",
      "human: T 101 ecoli: C 85\n",
      "human: E 102 ecoli: - 85\n",
      "human: Q 103 ecoli: - 85\n",
      "human: P 104 ecoli: - 85\n",
      "human: E 105 ecoli: - 85\n",
      "human: L 106 ecoli: - 85\n",
      "human: A 107 ecoli: - 85\n",
      "human: N 108 ecoli: G 86\n",
      "human: K 109 ecoli: D 87\n",
      "human: V 110 ecoli: V 88\n",
      "human: D 111 ecoli: P 89\n",
      "human: M 112 ecoli: E 90\n",
      "human: V 113 ecoli: I 91\n",
      "human: W 114 ecoli: M 92\n",
      "human: I 115 ecoli: V 93\n",
      "human: V 116 ecoli: I 94\n",
      "human: G 117 ecoli: G 95\n",
      "human: G 118 ecoli: G 96\n",
      "human: S 119 ecoli: G 97\n",
      "human: S 120 ecoli: R 98\n",
      "human: V 121 ecoli: V 99\n",
      "human: Y 122 ecoli: Y 100\n",
      "human: K 123 ecoli: E 101\n",
      "human: E 124 ecoli: Q 102\n",
      "human: A 125 ecoli: F 103\n",
      "human: M 126 ecoli: L 104\n",
      "human: N 127 ecoli: P 105\n",
      "human: H 128 ecoli: K 106\n",
      "human: P 129 ecoli: - 106\n",
      "human: G 130 ecoli: - 106\n",
      "human: H 131 ecoli: A 107\n",
      "human: L 132 ecoli: Q 108\n",
      "human: K 133 ecoli: K 109\n",
      "human: L 134 ecoli: L 110\n",
      "human: F 135 ecoli: Y 111\n",
      "human: V 136 ecoli: L 112\n",
      "human: T 137 ecoli: T 113\n",
      "human: R 138 ecoli: H 114\n",
      "human: I 139 ecoli: I 115\n",
      "human: M 140 ecoli: D 116\n",
      "human: Q 141 ecoli: A 117\n",
      "human: D 142 ecoli: E 118\n",
      "human: F 143 ecoli: V 119\n",
      "human: E 144 ecoli: E 120\n",
      "human: S 145 ecoli: G 121\n",
      "human: D 146 ecoli: D 122\n",
      "human: T 147 ecoli: T 123\n",
      "human: F 148 ecoli: H 124\n",
      "human: F 149 ecoli: F 125\n",
      "human: P 150 ecoli: P 126\n",
      "human: E 151 ecoli: D 127\n",
      "human: I 152 ecoli: Y 128\n",
      "human: D 153 ecoli: E 129\n",
      "human: L 154 ecoli: P 130\n",
      "human: E 155 ecoli: D 131\n",
      "human: K 156 ecoli: D 132\n",
      "human: Y 157 ecoli: W 133\n",
      "human: K 158 ecoli: E 134\n",
      "human: L 159 ecoli: S 135\n",
      "human: L 160 ecoli: V 136\n",
      "human: P 161 ecoli: F 137\n",
      "human: E 162 ecoli: - 137\n",
      "human: Y 163 ecoli: - 137\n",
      "human: P 164 ecoli: - 137\n",
      "human: G 165 ecoli: S 138\n",
      "human: V 166 ecoli: E 139\n",
      "human: L 167 ecoli: F 140\n",
      "human: S 168 ecoli: H 141\n",
      "human: D 169 ecoli: D 142\n",
      "human: V 170 ecoli: A 143\n",
      "human: Q 171 ecoli: D 144\n",
      "human: E 172 ecoli: A 145\n",
      "human: E 173 ecoli: Q 146\n",
      "human: K 174 ecoli: N 147\n",
      "human: G 175 ecoli: S 148\n",
      "human: I 176 ecoli: H 149\n",
      "human: K 177 ecoli: S 150\n",
      "human: Y 178 ecoli: Y 151\n",
      "human: K 179 ecoli: C 152\n",
      "human: F 180 ecoli: F 153\n",
      "human: E 181 ecoli: E 154\n",
      "human: V 182 ecoli: I 155\n",
      "human: Y 183 ecoli: L 156\n",
      "human: E 184 ecoli: E 157\n",
      "human: K 185 ecoli: R 158\n",
      "human: N 186 ecoli: R 159\n",
      "human: D 187 ecoli: - 159\n"
     ]
    }
   ],
   "source": [
    "#go through alignment and add rows to the merged df\n",
    "human_c = 0\n",
    "ecoli_c = 0\n",
    "#for i in range(0, len(s_align[0].seq)):\n",
    "#the current human DHFR tile only goes til 39 anyway\n",
    "#full length dhfr has 187 positions\n",
    "for i in range(0,187):\n",
    "    if s_align[0].seq[i] != '-': human_c += 1\n",
    "    if s_align[1].seq[i] != '-': ecoli_c += 1\n",
    "    print('human:', s_align[0].seq[i], str(human_c), 'ecoli:', s_align[1].seq[i], str(ecoli_c))\n",
    "    for aa in amino_acids:\n",
    "        #append row with human:S4A and ecoli:M1A\n",
    "        merge_df = merge_df.append(pd.concat([human_df.loc[human_df['human_variant'] == s_align[0].seq[i]+str(human_c)+aa].reset_index(drop=True),ecoli_df.loc[ecoli_df['ecoli_variant'] == s_align[1].seq[i]+str(ecoli_c)+aa].reset_index(drop=True)], axis = 1), ignore_index=True)\n",
    "    \n",
    "\n"
   ]
  },
  {
   "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>human_variant</th>\n",
       "      <th>score</th>\n",
       "      <th>SE</th>\n",
       "      <th>tile</th>\n",
       "      <th>human_n_mut</th>\n",
       "      <th>human_aa_ref</th>\n",
       "      <th>human_resi</th>\n",
       "      <th>human_aa_var</th>\n",
       "      <th>human_WT</th>\n",
       "      <th>ecoli_variant</th>\n",
       "      <th>...</th>\n",
       "      <th>Lon_minus_std_dev</th>\n",
       "      <th>Lon_minus_std_err</th>\n",
       "      <th>Lon_plus_score</th>\n",
       "      <th>Lon_plus_std_dev</th>\n",
       "      <th>Lon_plus_std_err</th>\n",
       "      <th>ecoli_n_mut</th>\n",
       "      <th>ecoli_aa_ref</th>\n",
       "      <th>ecoli_resi</th>\n",
       "      <th>ecoli_aa_var</th>\n",
       "      <th>ecoli_WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>V2H</td>\n",
       "      <td>-0.391535</td>\n",
       "      <td>0.311642</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>[V]</td>\n",
       "      <td>[2]</td>\n",
       "      <td>[H]</td>\n",
       "      <td>V2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>V2K</td>\n",
       "      <td>0.206199</td>\n",
       "      <td>0.232451</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>[V]</td>\n",
       "      <td>[2]</td>\n",
       "      <td>[K]</td>\n",
       "      <td>V2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>V2R</td>\n",
       "      <td>0.061586</td>\n",
       "      <td>0.251602</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>[V]</td>\n",
       "      <td>[2]</td>\n",
       "      <td>[R]</td>\n",
       "      <td>V2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>V2D</td>\n",
       "      <td>0.121341</td>\n",
       "      <td>0.194870</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>[V]</td>\n",
       "      <td>[2]</td>\n",
       "      <td>[D]</td>\n",
       "      <td>V2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>V2E</td>\n",
       "      <td>0.115536</td>\n",
       "      <td>0.160239</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>[V]</td>\n",
       "      <td>[2]</td>\n",
       "      <td>[E]</td>\n",
       "      <td>V2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3717</th>\n",
       "      <td>D187F</td>\n",
       "      <td>0.200886</td>\n",
       "      <td>0.026569</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>[D]</td>\n",
       "      <td>[187]</td>\n",
       "      <td>[F]</td>\n",
       "      <td>D187</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3718</th>\n",
       "      <td>D187W</td>\n",
       "      <td>0.210491</td>\n",
       "      <td>0.050457</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>[D]</td>\n",
       "      <td>[187]</td>\n",
       "      <td>[W]</td>\n",
       "      <td>D187</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3719</th>\n",
       "      <td>D187Y</td>\n",
       "      <td>0.414320</td>\n",
       "      <td>0.059295</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>[D]</td>\n",
       "      <td>[187]</td>\n",
       "      <td>[Y]</td>\n",
       "      <td>D187</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3720</th>\n",
       "      <td>D187G</td>\n",
       "      <td>0.279710</td>\n",
       "      <td>0.043179</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>[D]</td>\n",
       "      <td>[187]</td>\n",
       "      <td>[G]</td>\n",
       "      <td>D187</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3721</th>\n",
       "      <td>D187P</td>\n",
       "      <td>0.293374</td>\n",
       "      <td>0.051991</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>[D]</td>\n",
       "      <td>[187]</td>\n",
       "      <td>[P]</td>\n",
       "      <td>D187</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3722 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     human_variant     score        SE tile human_n_mut human_aa_ref  \\\n",
       "0              V2H -0.391535  0.311642    1           1          [V]   \n",
       "1              V2K  0.206199  0.232451    1           1          [V]   \n",
       "2              V2R  0.061586  0.251602    1           1          [V]   \n",
       "3              V2D  0.121341  0.194870    1           1          [V]   \n",
       "4              V2E  0.115536  0.160239    1           1          [V]   \n",
       "...            ...       ...       ...  ...         ...          ...   \n",
       "3717         D187F  0.200886  0.026569    5           1          [D]   \n",
       "3718         D187W  0.210491  0.050457    5           1          [D]   \n",
       "3719         D187Y  0.414320  0.059295    5           1          [D]   \n",
       "3720         D187G  0.279710  0.043179    5           1          [D]   \n",
       "3721         D187P  0.293374  0.051991    5           1          [D]   \n",
       "\n",
       "     human_resi human_aa_var human_WT ecoli_variant  ...  Lon_minus_std_dev  \\\n",
       "0           [2]          [H]       V2           NaN  ...                NaN   \n",
       "1           [2]          [K]       V2           NaN  ...                NaN   \n",
       "2           [2]          [R]       V2           NaN  ...                NaN   \n",
       "3           [2]          [D]       V2           NaN  ...                NaN   \n",
       "4           [2]          [E]       V2           NaN  ...                NaN   \n",
       "...         ...          ...      ...           ...  ...                ...   \n",
       "3717      [187]          [F]     D187           NaN  ...                NaN   \n",
       "3718      [187]          [W]     D187           NaN  ...                NaN   \n",
       "3719      [187]          [Y]     D187           NaN  ...                NaN   \n",
       "3720      [187]          [G]     D187           NaN  ...                NaN   \n",
       "3721      [187]          [P]     D187           NaN  ...                NaN   \n",
       "\n",
       "      Lon_minus_std_err  Lon_plus_score  Lon_plus_std_dev  Lon_plus_std_err  \\\n",
       "0                   NaN             NaN               NaN               NaN   \n",
       "1                   NaN             NaN               NaN               NaN   \n",
       "2                   NaN             NaN               NaN               NaN   \n",
       "3                   NaN             NaN               NaN               NaN   \n",
       "4                   NaN             NaN               NaN               NaN   \n",
       "...                 ...             ...               ...               ...   \n",
       "3717                NaN             NaN               NaN               NaN   \n",
       "3718                NaN             NaN               NaN               NaN   \n",
       "3719                NaN             NaN               NaN               NaN   \n",
       "3720                NaN             NaN               NaN               NaN   \n",
       "3721                NaN             NaN               NaN               NaN   \n",
       "\n",
       "      ecoli_n_mut  ecoli_aa_ref ecoli_resi ecoli_aa_var ecoli_WT  \n",
       "0             NaN           NaN        NaN          NaN      NaN  \n",
       "1             NaN           NaN        NaN          NaN      NaN  \n",
       "2             NaN           NaN        NaN          NaN      NaN  \n",
       "3             NaN           NaN        NaN          NaN      NaN  \n",
       "4             NaN           NaN        NaN          NaN      NaN  \n",
       "...           ...           ...        ...          ...      ...  \n",
       "3717          NaN           NaN        NaN          NaN      NaN  \n",
       "3718          NaN           NaN        NaN          NaN      NaN  \n",
       "3719          NaN           NaN        NaN          NaN      NaN  \n",
       "3720          NaN           NaN        NaN          NaN      NaN  \n",
       "3721          NaN           NaN        NaN          NaN      NaN  \n",
       "\n",
       "[3722 rows x 21 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merge_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "merge_df.to_csv(base_dir+'/data/merge_human_ecoli_fulldhfr.csv', sep = '\\t', na_rep='NA')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "human: M 1 ecoli: - 0\n",
      "human: V 2 ecoli: - 0\n"
     ]
    }
   ],
   "source": [
    "#test:\n",
    "merge_df2 = pd.DataFrame(columns=list(human_df.columns)+list(ecoli_df.columns))\n",
    "\n",
    "human_c = 0\n",
    "ecoli_c = 0\n",
    "#for i in range(0, len(s_align[0].seq)):\n",
    "for i in range(0,2):\n",
    "    if s_align[0].seq[i] != '-': human_c += 1\n",
    "    if s_align[1].seq[i] != '-': ecoli_c += 1\n",
    "    print('human:', s_align[0].seq[i], str(human_c), 'ecoli:', s_align[1].seq[i], str(ecoli_c))\n",
    "    for aa in amino_acids:\n",
    "        #append row with human:S4A and ecoli:M1A\n",
    "        merge_df2 = merge_df2.append(pd.concat([human_df.loc[human_df['human_variant'] == s_align[0].seq[i]+str(human_c)+aa].reset_index(drop=True),ecoli_df.loc[ecoli_df['ecoli_variant'] == s_align[1].seq[i]+str(ecoli_c)+aa].reset_index(drop=True)], axis = 1), ignore_index=True)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>human_variant</th>\n",
       "      <th>MTX_score</th>\n",
       "      <th>MTX_SE</th>\n",
       "      <th>MTX_Cu_score</th>\n",
       "      <th>MTX_Cu_SE</th>\n",
       "      <th>37_score</th>\n",
       "      <th>37_SE</th>\n",
       "      <th>37_Cu_score</th>\n",
       "      <th>37_Cu_SE</th>\n",
       "      <th>human_n_mut</th>\n",
       "      <th>...</th>\n",
       "      <th>Lon_minus_std_dev</th>\n",
       "      <th>Lon_minus_std_err</th>\n",
       "      <th>Lon_plus_score</th>\n",
       "      <th>Lon_plus_std_dev</th>\n",
       "      <th>Lon_plus_std_err</th>\n",
       "      <th>ecoli_n_mut</th>\n",
       "      <th>ecoli_aa_ref</th>\n",
       "      <th>ecoli_resi</th>\n",
       "      <th>ecoli_aa_var</th>\n",
       "      <th>ecoli_WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>V2H</td>\n",
       "      <td>-0.286942</td>\n",
       "      <td>0.356365</td>\n",
       "      <td>-0.701059</td>\n",
       "      <td>0.198073</td>\n",
       "      <td>-0.319804</td>\n",
       "      <td>0.536673</td>\n",
       "      <td>0.401002</td>\n",
       "      <td>0.737741</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>V2K</td>\n",
       "      <td>0.020324</td>\n",
       "      <td>0.221691</td>\n",
       "      <td>0.689756</td>\n",
       "      <td>0.490723</td>\n",
       "      <td>1.749161</td>\n",
       "      <td>1.007435</td>\n",
       "      <td>0.437940</td>\n",
       "      <td>0.281015</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>V2R</td>\n",
       "      <td>0.205459</td>\n",
       "      <td>0.099615</td>\n",
       "      <td>-0.035478</td>\n",
       "      <td>0.207287</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.257201</td>\n",
       "      <td>0.378342</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>V2D</td>\n",
       "      <td>-0.007734</td>\n",
       "      <td>0.744842</td>\n",
       "      <td>-0.093837</td>\n",
       "      <td>0.476336</td>\n",
       "      <td>-0.928840</td>\n",
       "      <td>0.548459</td>\n",
       "      <td>0.406764</td>\n",
       "      <td>0.776011</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>V2E</td>\n",
       "      <td>-0.157151</td>\n",
       "      <td>0.148753</td>\n",
       "      <td>0.520350</td>\n",
       "      <td>0.367248</td>\n",
       "      <td>-0.158215</td>\n",
       "      <td>0.499464</td>\n",
       "      <td>-0.410229</td>\n",
       "      <td>0.428925</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>V2C</td>\n",
       "      <td>0.810929</td>\n",
       "      <td>0.684289</td>\n",
       "      <td>0.334408</td>\n",
       "      <td>1.087821</td>\n",
       "      <td>-0.314401</td>\n",
       "      <td>1.017164</td>\n",
       "      <td>0.208587</td>\n",
       "      <td>0.286785</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>V2M</td>\n",
       "      <td>0.468150</td>\n",
       "      <td>0.414734</td>\n",
       "      <td>0.371962</td>\n",
       "      <td>0.413697</td>\n",
       "      <td>0.762780</td>\n",
       "      <td>0.657686</td>\n",
       "      <td>0.163284</td>\n",
       "      <td>0.791211</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>V2N</td>\n",
       "      <td>-0.459645</td>\n",
       "      <td>0.484509</td>\n",
       "      <td>-0.361201</td>\n",
       "      <td>0.441901</td>\n",
       "      <td>-0.358981</td>\n",
       "      <td>0.322562</td>\n",
       "      <td>-0.714165</td>\n",
       "      <td>0.518612</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>V2Q</td>\n",
       "      <td>-0.140268</td>\n",
       "      <td>0.465379</td>\n",
       "      <td>0.082057</td>\n",
       "      <td>0.445276</td>\n",
       "      <td>-0.762146</td>\n",
       "      <td>0.635072</td>\n",
       "      <td>-0.147298</td>\n",
       "      <td>0.392828</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>V2S</td>\n",
       "      <td>0.020571</td>\n",
       "      <td>0.066504</td>\n",
       "      <td>-0.219469</td>\n",
       "      <td>0.168145</td>\n",
       "      <td>0.595595</td>\n",
       "      <td>0.594085</td>\n",
       "      <td>-0.116430</td>\n",
       "      <td>0.457736</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>V2T</td>\n",
       "      <td>0.340897</td>\n",
       "      <td>0.292280</td>\n",
       "      <td>-0.427087</td>\n",
       "      <td>0.516722</td>\n",
       "      <td>-0.121132</td>\n",
       "      <td>0.277999</td>\n",
       "      <td>-0.132329</td>\n",
       "      <td>0.277394</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>V2A</td>\n",
       "      <td>-0.144436</td>\n",
       "      <td>0.207918</td>\n",
       "      <td>-0.048312</td>\n",
       "      <td>0.086620</td>\n",
       "      <td>0.271316</td>\n",
       "      <td>0.653001</td>\n",
       "      <td>0.240384</td>\n",
       "      <td>0.270966</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>V2I</td>\n",
       "      <td>-0.748312</td>\n",
       "      <td>0.488069</td>\n",
       "      <td>-0.368338</td>\n",
       "      <td>0.143316</td>\n",
       "      <td>-0.837198</td>\n",
       "      <td>0.232719</td>\n",
       "      <td>-0.567405</td>\n",
       "      <td>0.182908</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>V2L</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.465342</td>\n",
       "      <td>0.408500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.223191</td>\n",
       "      <td>0.150480</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>V2F</td>\n",
       "      <td>-0.112675</td>\n",
       "      <td>0.125393</td>\n",
       "      <td>-0.972789</td>\n",
       "      <td>0.228885</td>\n",
       "      <td>-1.071899</td>\n",
       "      <td>0.070878</td>\n",
       "      <td>-0.331263</td>\n",
       "      <td>0.307833</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>V2W</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.061704</td>\n",
       "      <td>0.325974</td>\n",
       "      <td>-0.440371</td>\n",
       "      <td>0.503913</td>\n",
       "      <td>-0.735029</td>\n",
       "      <td>0.546943</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>V2Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.531448</td>\n",
       "      <td>0.730146</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.084163</td>\n",
       "      <td>0.748352</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>V2G</td>\n",
       "      <td>-0.023711</td>\n",
       "      <td>0.092107</td>\n",
       "      <td>0.001101</td>\n",
       "      <td>0.140023</td>\n",
       "      <td>-0.163210</td>\n",
       "      <td>1.113850</td>\n",
       "      <td>-0.153493</td>\n",
       "      <td>0.330262</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>V2P</td>\n",
       "      <td>0.291268</td>\n",
       "      <td>0.472379</td>\n",
       "      <td>0.321542</td>\n",
       "      <td>0.066486</td>\n",
       "      <td>0.030170</td>\n",
       "      <td>0.564313</td>\n",
       "      <td>-0.375665</td>\n",
       "      <td>0.505646</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>19 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   human_variant  MTX_score    MTX_SE  MTX_Cu_score  MTX_Cu_SE  37_score  \\\n",
       "0            V2H  -0.286942  0.356365     -0.701059   0.198073 -0.319804   \n",
       "1            V2K   0.020324  0.221691      0.689756   0.490723  1.749161   \n",
       "2            V2R   0.205459  0.099615     -0.035478   0.207287       NaN   \n",
       "3            V2D  -0.007734  0.744842     -0.093837   0.476336 -0.928840   \n",
       "4            V2E  -0.157151  0.148753      0.520350   0.367248 -0.158215   \n",
       "5            V2C   0.810929  0.684289      0.334408   1.087821 -0.314401   \n",
       "6            V2M   0.468150  0.414734      0.371962   0.413697  0.762780   \n",
       "7            V2N  -0.459645  0.484509     -0.361201   0.441901 -0.358981   \n",
       "8            V2Q  -0.140268  0.465379      0.082057   0.445276 -0.762146   \n",
       "9            V2S   0.020571  0.066504     -0.219469   0.168145  0.595595   \n",
       "10           V2T   0.340897  0.292280     -0.427087   0.516722 -0.121132   \n",
       "11           V2A  -0.144436  0.207918     -0.048312   0.086620  0.271316   \n",
       "12           V2I  -0.748312  0.488069     -0.368338   0.143316 -0.837198   \n",
       "13           V2L        NaN       NaN      0.465342   0.408500       NaN   \n",
       "14           V2F  -0.112675  0.125393     -0.972789   0.228885 -1.071899   \n",
       "15           V2W        NaN       NaN     -0.061704   0.325974 -0.440371   \n",
       "16           V2Y        NaN       NaN      0.531448   0.730146       NaN   \n",
       "17           V2G  -0.023711  0.092107      0.001101   0.140023 -0.163210   \n",
       "18           V2P   0.291268  0.472379      0.321542   0.066486  0.030170   \n",
       "\n",
       "       37_SE  37_Cu_score  37_Cu_SE human_n_mut  ... Lon_minus_std_dev  \\\n",
       "0   0.536673     0.401002  0.737741           1  ...               NaN   \n",
       "1   1.007435     0.437940  0.281015           1  ...               NaN   \n",
       "2        NaN     0.257201  0.378342           1  ...               NaN   \n",
       "3   0.548459     0.406764  0.776011           1  ...               NaN   \n",
       "4   0.499464    -0.410229  0.428925           1  ...               NaN   \n",
       "5   1.017164     0.208587  0.286785           1  ...               NaN   \n",
       "6   0.657686     0.163284  0.791211           1  ...               NaN   \n",
       "7   0.322562    -0.714165  0.518612           1  ...               NaN   \n",
       "8   0.635072    -0.147298  0.392828           1  ...               NaN   \n",
       "9   0.594085    -0.116430  0.457736           1  ...               NaN   \n",
       "10  0.277999    -0.132329  0.277394           1  ...               NaN   \n",
       "11  0.653001     0.240384  0.270966           1  ...               NaN   \n",
       "12  0.232719    -0.567405  0.182908           1  ...               NaN   \n",
       "13       NaN    -0.223191  0.150480           1  ...               NaN   \n",
       "14  0.070878    -0.331263  0.307833           1  ...               NaN   \n",
       "15  0.503913    -0.735029  0.546943           1  ...               NaN   \n",
       "16       NaN     1.084163  0.748352           1  ...               NaN   \n",
       "17  1.113850    -0.153493  0.330262           1  ...               NaN   \n",
       "18  0.564313    -0.375665  0.505646           1  ...               NaN   \n",
       "\n",
       "   Lon_minus_std_err Lon_plus_score Lon_plus_std_dev Lon_plus_std_err  \\\n",
       "0                NaN            NaN              NaN              NaN   \n",
       "1                NaN            NaN              NaN              NaN   \n",
       "2                NaN            NaN              NaN              NaN   \n",
       "3                NaN            NaN              NaN              NaN   \n",
       "4                NaN            NaN              NaN              NaN   \n",
       "5                NaN            NaN              NaN              NaN   \n",
       "6                NaN            NaN              NaN              NaN   \n",
       "7                NaN            NaN              NaN              NaN   \n",
       "8                NaN            NaN              NaN              NaN   \n",
       "9                NaN            NaN              NaN              NaN   \n",
       "10               NaN            NaN              NaN              NaN   \n",
       "11               NaN            NaN              NaN              NaN   \n",
       "12               NaN            NaN              NaN              NaN   \n",
       "13               NaN            NaN              NaN              NaN   \n",
       "14               NaN            NaN              NaN              NaN   \n",
       "15               NaN            NaN              NaN              NaN   \n",
       "16               NaN            NaN              NaN              NaN   \n",
       "17               NaN            NaN              NaN              NaN   \n",
       "18               NaN            NaN              NaN              NaN   \n",
       "\n",
       "    ecoli_n_mut  ecoli_aa_ref  ecoli_resi  ecoli_aa_var  ecoli_WT  \n",
       "0           NaN           NaN         NaN           NaN       NaN  \n",
       "1           NaN           NaN         NaN           NaN       NaN  \n",
       "2           NaN           NaN         NaN           NaN       NaN  \n",
       "3           NaN           NaN         NaN           NaN       NaN  \n",
       "4           NaN           NaN         NaN           NaN       NaN  \n",
       "5           NaN           NaN         NaN           NaN       NaN  \n",
       "6           NaN           NaN         NaN           NaN       NaN  \n",
       "7           NaN           NaN         NaN           NaN       NaN  \n",
       "8           NaN           NaN         NaN           NaN       NaN  \n",
       "9           NaN           NaN         NaN           NaN       NaN  \n",
       "10          NaN           NaN         NaN           NaN       NaN  \n",
       "11          NaN           NaN         NaN           NaN       NaN  \n",
       "12          NaN           NaN         NaN           NaN       NaN  \n",
       "13          NaN           NaN         NaN           NaN       NaN  \n",
       "14          NaN           NaN         NaN           NaN       NaN  \n",
       "15          NaN           NaN         NaN           NaN       NaN  \n",
       "16          NaN           NaN         NaN           NaN       NaN  \n",
       "17          NaN           NaN         NaN           NaN       NaN  \n",
       "18          NaN           NaN         NaN           NaN       NaN  \n",
       "\n",
       "[19 rows x 26 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merge_df2\n",
    "#observation:\n",
    "#It skips completely empty rows (composed only of NAs) like the human:M1 line (the mave starts at pos 2 since we use a fusion protein)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "human: M1H ecoli: -0H\n",
      "human: M1K ecoli: -0K\n",
      "human: M1R ecoli: -0R\n",
      "human: M1D ecoli: -0D\n",
      "human: M1E ecoli: -0E\n",
      "human: M1C ecoli: -0C\n",
      "human: M1M ecoli: -0M\n",
      "human: M1N ecoli: -0N\n",
      "human: M1Q ecoli: -0Q\n",
      "human: M1S ecoli: -0S\n",
      "human: M1T ecoli: -0T\n",
      "human: M1A ecoli: -0A\n",
      "human: M1I ecoli: -0I\n",
      "human: M1L ecoli: -0L\n",
      "human: M1V ecoli: -0V\n",
      "human: M1F ecoli: -0F\n",
      "human: M1W ecoli: -0W\n",
      "human: M1Y ecoli: -0Y\n",
      "human: M1G ecoli: -0G\n",
      "human: M1P ecoli: -0P\n",
      "human: M1* ecoli: -0*\n",
      "human: V2H ecoli: -0H\n",
      "human: V2K ecoli: -0K\n",
      "human: V2R ecoli: -0R\n",
      "human: V2D ecoli: -0D\n",
      "human: V2E ecoli: -0E\n",
      "human: V2C ecoli: -0C\n",
      "human: V2M ecoli: -0M\n",
      "human: V2N ecoli: -0N\n",
      "human: V2Q ecoli: -0Q\n",
      "human: V2S ecoli: -0S\n",
      "human: V2T ecoli: -0T\n",
      "human: V2A ecoli: -0A\n",
      "human: V2I ecoli: -0I\n",
      "human: V2L ecoli: -0L\n",
      "human: V2V ecoli: -0V\n",
      "human: V2F ecoli: -0F\n",
      "human: V2W ecoli: -0W\n",
      "human: V2Y ecoli: -0Y\n",
      "human: V2G ecoli: -0G\n",
      "human: V2P ecoli: -0P\n",
      "human: V2* ecoli: -0*\n",
      "human: G3H ecoli: -0H\n",
      "human: G3K ecoli: -0K\n",
      "human: G3R ecoli: -0R\n",
      "human: G3D ecoli: -0D\n",
      "human: G3E ecoli: -0E\n",
      "human: G3C ecoli: -0C\n",
      "human: G3M ecoli: -0M\n",
      "human: G3N ecoli: -0N\n",
      "human: G3Q ecoli: -0Q\n",
      "human: G3S ecoli: -0S\n",
      "human: G3T ecoli: -0T\n",
      "human: G3A ecoli: -0A\n",
      "human: G3I ecoli: -0I\n",
      "human: G3L ecoli: -0L\n",
      "human: G3V ecoli: -0V\n",
      "human: G3F ecoli: -0F\n",
      "human: G3W ecoli: -0W\n",
      "human: G3Y ecoli: -0Y\n",
      "human: G3G ecoli: -0G\n",
      "human: G3P ecoli: -0P\n",
      "human: G3* ecoli: -0*\n",
      "human: S4H ecoli: M1H\n",
      "human: S4K ecoli: M1K\n",
      "human: S4R ecoli: M1R\n",
      "human: S4D ecoli: M1D\n",
      "human: S4E ecoli: M1E\n",
      "human: S4C ecoli: M1C\n",
      "human: S4M ecoli: M1M\n",
      "human: S4N ecoli: M1N\n",
      "human: S4Q ecoli: M1Q\n",
      "human: S4S ecoli: M1S\n",
      "human: S4T ecoli: M1T\n",
      "human: S4A ecoli: M1A\n",
      "human: S4I ecoli: M1I\n",
      "human: S4L ecoli: M1L\n",
      "human: S4V ecoli: M1V\n",
      "human: S4F ecoli: M1F\n",
      "human: S4W ecoli: M1W\n",
      "human: S4Y ecoli: M1Y\n",
      "human: S4G ecoli: M1G\n",
      "human: S4P ecoli: M1P\n",
      "human: S4* ecoli: M1*\n",
      "human: L5H ecoli: I2H\n",
      "human: L5K ecoli: I2K\n",
      "human: L5R ecoli: I2R\n",
      "human: L5D ecoli: I2D\n",
      "human: L5E ecoli: I2E\n",
      "human: L5C ecoli: I2C\n",
      "human: L5M ecoli: I2M\n",
      "human: L5N ecoli: I2N\n",
      "human: L5Q ecoli: I2Q\n",
      "human: L5S ecoli: I2S\n",
      "human: L5T ecoli: I2T\n",
      "human: L5A ecoli: I2A\n",
      "human: L5I ecoli: I2I\n",
      "human: L5L ecoli: I2L\n",
      "human: L5V ecoli: I2V\n",
      "human: L5F ecoli: I2F\n",
      "human: L5W ecoli: I2W\n",
      "human: L5Y ecoli: I2Y\n",
      "human: L5G ecoli: I2G\n",
      "human: L5P ecoli: I2P\n",
      "human: L5* ecoli: I2*\n",
      "human: N6H ecoli: S3H\n",
      "human: N6K ecoli: S3K\n",
      "human: N6R ecoli: S3R\n",
      "human: N6D ecoli: S3D\n",
      "human: N6E ecoli: S3E\n",
      "human: N6C ecoli: S3C\n",
      "human: N6M ecoli: S3M\n",
      "human: N6N ecoli: S3N\n",
      "human: N6Q ecoli: S3Q\n",
      "human: N6S ecoli: S3S\n",
      "human: N6T ecoli: S3T\n",
      "human: N6A ecoli: S3A\n",
      "human: N6I ecoli: S3I\n",
      "human: N6L ecoli: S3L\n",
      "human: N6V ecoli: S3V\n",
      "human: N6F ecoli: S3F\n",
      "human: N6W ecoli: S3W\n",
      "human: N6Y ecoli: S3Y\n",
      "human: N6G ecoli: S3G\n",
      "human: N6P ecoli: S3P\n",
      "human: N6* ecoli: S3*\n",
      "human: C7H ecoli: L4H\n",
      "human: C7K ecoli: L4K\n",
      "human: C7R ecoli: L4R\n",
      "human: C7D ecoli: L4D\n",
      "human: C7E ecoli: L4E\n",
      "human: C7C ecoli: L4C\n",
      "human: C7M ecoli: L4M\n",
      "human: C7N ecoli: L4N\n",
      "human: C7Q ecoli: L4Q\n",
      "human: C7S ecoli: L4S\n",
      "human: C7T ecoli: L4T\n",
      "human: C7A ecoli: L4A\n",
      "human: C7I ecoli: L4I\n",
      "human: C7L ecoli: L4L\n",
      "human: C7V ecoli: L4V\n",
      "human: C7F ecoli: L4F\n",
      "human: C7W ecoli: L4W\n",
      "human: C7Y ecoli: L4Y\n",
      "human: C7G ecoli: L4G\n",
      "human: C7P ecoli: L4P\n",
      "human: C7* ecoli: L4*\n",
      "human: I8H ecoli: I5H\n",
      "human: I8K ecoli: I5K\n",
      "human: I8R ecoli: I5R\n",
      "human: I8D ecoli: I5D\n",
      "human: I8E ecoli: I5E\n",
      "human: I8C ecoli: I5C\n",
      "human: I8M ecoli: I5M\n",
      "human: I8N ecoli: I5N\n",
      "human: I8Q ecoli: I5Q\n",
      "human: I8S ecoli: I5S\n",
      "human: I8T ecoli: I5T\n",
      "human: I8A ecoli: I5A\n",
      "human: I8I ecoli: I5I\n",
      "human: I8L ecoli: I5L\n",
      "human: I8V ecoli: I5V\n",
      "human: I8F ecoli: I5F\n",
      "human: I8W ecoli: I5W\n",
      "human: I8Y ecoli: I5Y\n",
      "human: I8G ecoli: I5G\n",
      "human: I8P ecoli: I5P\n",
      "human: I8* ecoli: I5*\n",
      "human: V9H ecoli: A6H\n",
      "human: V9K ecoli: A6K\n",
      "human: V9R ecoli: A6R\n",
      "human: V9D ecoli: A6D\n",
      "human: V9E ecoli: A6E\n",
      "human: V9C ecoli: A6C\n",
      "human: V9M ecoli: A6M\n",
      "human: V9N ecoli: A6N\n",
      "human: V9Q ecoli: A6Q\n",
      "human: V9S ecoli: A6S\n",
      "human: V9T ecoli: A6T\n",
      "human: V9A ecoli: A6A\n",
      "human: V9I ecoli: A6I\n",
      "human: V9L ecoli: A6L\n",
      "human: V9V ecoli: A6V\n",
      "human: V9F ecoli: A6F\n",
      "human: V9W ecoli: A6W\n",
      "human: V9Y ecoli: A6Y\n",
      "human: V9G ecoli: A6G\n",
      "human: V9P ecoli: A6P\n",
      "human: V9* ecoli: A6*\n",
      "human: A10H ecoli: A7H\n",
      "human: A10K ecoli: A7K\n",
      "human: A10R ecoli: A7R\n",
      "human: A10D ecoli: A7D\n",
      "human: A10E ecoli: A7E\n",
      "human: A10C ecoli: A7C\n",
      "human: A10M ecoli: A7M\n",
      "human: A10N ecoli: A7N\n",
      "human: A10Q ecoli: A7Q\n",
      "human: A10S ecoli: A7S\n",
      "human: A10T ecoli: A7T\n",
      "human: A10A ecoli: A7A\n",
      "human: A10I ecoli: A7I\n",
      "human: A10L ecoli: A7L\n",
      "human: A10V ecoli: A7V\n",
      "human: A10F ecoli: A7F\n",
      "human: A10W ecoli: A7W\n",
      "human: A10Y ecoli: A7Y\n",
      "human: A10G ecoli: A7G\n",
      "human: A10P ecoli: A7P\n",
      "human: A10* ecoli: A7*\n"
     ]
    }
   ],
   "source": [
    "#correct indexing?\n",
    "\n",
    "human_c = 0\n",
    "ecoli_c = 0\n",
    "#for i in range(0, len(s_align[0].seq)):\n",
    "for i in range(0,10):\n",
    "    if s_align[0].seq[i] != '-': human_c += 1\n",
    "    if s_align[1].seq[i] != '-': ecoli_c += 1\n",
    "    for aa in amino_acids:\n",
    "        print('human:', s_align[0].seq[i]+str(human_c)+aa, 'ecoli:', s_align[1].seq[i]+str(ecoli_c)+aa)\n",
    "        #append row with human:S4A and ecoli:M1A\n",
    "        #merge_df = merge_df.append(pd.concat([human_df.loc[human_df['human_variant'] == s_align[0].seq[i]+str(human_c)+aa],ecoli_df.loc[ecoli_df['ecoli_variant'] == s_align[1].seq[i]+str(ecoli_c)+aa]], axis = 1), ignore_index=True)\n",
    "    \n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>human_variant</th>\n",
       "      <th>MTX_score</th>\n",
       "      <th>MTX_SE</th>\n",
       "      <th>MTX_Cu_score</th>\n",
       "      <th>MTX_Cu_SE</th>\n",
       "      <th>37_score</th>\n",
       "      <th>37_SE</th>\n",
       "      <th>37_Cu_score</th>\n",
       "      <th>37_Cu_SE</th>\n",
       "      <th>human_n_mut</th>\n",
       "      <th>...</th>\n",
       "      <th>Lon_minus_std_dev</th>\n",
       "      <th>Lon_minus_std_err</th>\n",
       "      <th>Lon_plus_score</th>\n",
       "      <th>Lon_plus_std_dev</th>\n",
       "      <th>Lon_plus_std_err</th>\n",
       "      <th>ecoli_n_mut</th>\n",
       "      <th>ecoli_aa_ref</th>\n",
       "      <th>ecoli_resi</th>\n",
       "      <th>ecoli_aa_var</th>\n",
       "      <th>ecoli_WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S4K</td>\n",
       "      <td>-0.014153</td>\n",
       "      <td>0.600629</td>\n",
       "      <td>-0.557012</td>\n",
       "      <td>0.126831</td>\n",
       "      <td>-0.119039</td>\n",
       "      <td>0.463813</td>\n",
       "      <td>-0.835569</td>\n",
       "      <td>0.278303</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>[M]</td>\n",
       "      <td>[1]</td>\n",
       "      <td>[K]</td>\n",
       "      <td>M1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  human_variant  MTX_score    MTX_SE  MTX_Cu_score  MTX_Cu_SE  37_score  \\\n",
       "0           S4K  -0.014153  0.600629     -0.557012   0.126831 -0.119039   \n",
       "\n",
       "      37_SE  37_Cu_score  37_Cu_SE  human_n_mut  ... Lon_minus_std_dev  \\\n",
       "0  0.463813    -0.835569  0.278303            1  ...               NaN   \n",
       "\n",
       "  Lon_minus_std_err Lon_plus_score Lon_plus_std_dev Lon_plus_std_err  \\\n",
       "0               NaN            NaN              NaN              NaN   \n",
       "\n",
       "   ecoli_n_mut  ecoli_aa_ref  ecoli_resi  ecoli_aa_var  ecoli_WT  \n",
       "0            1           [M]         [1]           [K]        M1  \n",
       "\n",
       "[1 rows x 26 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#tmp_df = pd.concat([human_df.loc[human_df['human_variant'] == s_align[0].seq[i]+str(human_c)+aa],ecoli_df.loc[ecoli_df['ecoli_variant'] == s_align[1].seq[i]+str(ecoli_c)+aa]], axis = 1)\n",
    "tmp_df = pd.concat([human_df.loc[human_df['human_variant'] == 'S4K'].reset_index(drop=True),ecoli_df.loc[ecoli_df['ecoli_variant'] == 'M1K'].reset_index(drop=True)], axis = 1)\n",
    "tmp_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>human_variant</th>\n",
       "      <th>MTX_score</th>\n",
       "      <th>MTX_SE</th>\n",
       "      <th>MTX_Cu_score</th>\n",
       "      <th>MTX_Cu_SE</th>\n",
       "      <th>37_score</th>\n",
       "      <th>37_SE</th>\n",
       "      <th>37_Cu_score</th>\n",
       "      <th>37_Cu_SE</th>\n",
       "      <th>human_n_mut</th>\n",
       "      <th>human_aa_ref</th>\n",
       "      <th>human_resi</th>\n",
       "      <th>human_aa_var</th>\n",
       "      <th>human_WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S4K</td>\n",
       "      <td>-0.014153</td>\n",
       "      <td>0.600629</td>\n",
       "      <td>-0.557012</td>\n",
       "      <td>0.126831</td>\n",
       "      <td>-0.119039</td>\n",
       "      <td>0.463813</td>\n",
       "      <td>-0.835569</td>\n",
       "      <td>0.278303</td>\n",
       "      <td>1</td>\n",
       "      <td>[S]</td>\n",
       "      <td>[4]</td>\n",
       "      <td>[K]</td>\n",
       "      <td>S4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  human_variant  MTX_score    MTX_SE  MTX_Cu_score  MTX_Cu_SE  37_score  \\\n",
       "0           S4K  -0.014153  0.600629     -0.557012   0.126831 -0.119039   \n",
       "\n",
       "      37_SE  37_Cu_score  37_Cu_SE  human_n_mut human_aa_ref human_resi  \\\n",
       "0  0.463813    -0.835569  0.278303            1          [S]        [4]   \n",
       "\n",
       "  human_aa_var human_WT  \n",
       "0          [K]       S4  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "human_df.loc[human_df['human_variant'] == 'S4K'].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>human_variant</th>\n",
       "      <th>MTX_score</th>\n",
       "      <th>MTX_SE</th>\n",
       "      <th>MTX_Cu_score</th>\n",
       "      <th>MTX_Cu_SE</th>\n",
       "      <th>37_score</th>\n",
       "      <th>37_SE</th>\n",
       "      <th>37_Cu_score</th>\n",
       "      <th>37_Cu_SE</th>\n",
       "      <th>human_n_mut</th>\n",
       "      <th>...</th>\n",
       "      <th>Lon_minus_std_dev</th>\n",
       "      <th>Lon_minus_std_err</th>\n",
       "      <th>Lon_plus_score</th>\n",
       "      <th>Lon_plus_std_dev</th>\n",
       "      <th>Lon_plus_std_err</th>\n",
       "      <th>ecoli_n_mut</th>\n",
       "      <th>ecoli_aa_ref</th>\n",
       "      <th>ecoli_resi</th>\n",
       "      <th>ecoli_aa_var</th>\n",
       "      <th>ecoli_WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>L5I</td>\n",
       "      <td>-0.696559</td>\n",
       "      <td>0.556897</td>\n",
       "      <td>-0.677255</td>\n",
       "      <td>0.284411</td>\n",
       "      <td>-1.594511</td>\n",
       "      <td>0.404429</td>\n",
       "      <td>-0.257407</td>\n",
       "      <td>0.63212</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   human_variant  MTX_score    MTX_SE  MTX_Cu_score  MTX_Cu_SE  37_score  \\\n",
       "69           L5I  -0.696559  0.556897     -0.677255   0.284411 -1.594511   \n",
       "\n",
       "       37_SE  37_Cu_score  37_Cu_SE human_n_mut  ... Lon_minus_std_dev  \\\n",
       "69  0.404429    -0.257407   0.63212           1  ...               NaN   \n",
       "\n",
       "   Lon_minus_std_err Lon_plus_score Lon_plus_std_dev Lon_plus_std_err  \\\n",
       "69               NaN            NaN              NaN              NaN   \n",
       "\n",
       "    ecoli_n_mut  ecoli_aa_ref  ecoli_resi  ecoli_aa_var  ecoli_WT  \n",
       "69          NaN           NaN         NaN           NaN       NaN  \n",
       "\n",
       "[1 rows x 26 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merge_df.loc[merge_df['human_variant'] == 'L5I']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}