sbt-gather-plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import glob as glob\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "import nbpresent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ERR164407', 'ERR164408', 'ERR164409', 'ERR315858', 'ERR315859',\n",
       "       'ERR315860', 'ERR315861', 'ERR315862', 'ERR315863', 'ERR318618',\n",
       "       ...\n",
       "       'ERR599167', 'ERR599168', 'ERR599169', 'ERR599170', 'ERR599171',\n",
       "       'ERR599172', 'ERR599173', 'ERR599174', 'ERR599175', 'ERR599176'],\n",
       "      dtype='object', length=248)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test=pd.read_table('tara-analyses/ERP001736_taxonomy_abundances_v2.0.tsv')\n",
    "splitGenus=test['#SampleID'].str.split(';', expand=True)\n",
    "splitGenus.columns=['Root', 'k', 'p', 'c', 'o', 'f', 'g', 's']\n",
    "splitGenus=splitGenus.T.drop('Root').T\n",
    "Tara_taxonomy = splitGenus.join(test).T.drop('#SampleID').T\n",
    "Tara_taxonomy.columns[Tara_taxonomy.columns.str.startswith('ERR')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Genus_Tara_taxonomy=Tara_taxonomy.iloc[:,5:].groupby('g').sum()\n",
    "Genus_Tara_taxonomy=Genus_Tara_taxonomy.T.drop('s').T\n",
    "Genus_Tara_taxonomy.loc['sum']=Genus_Tara_taxonomy.sum()\n",
    "Genus_Tara_taxonomy['sum']=Genus_Tara_taxonomy.sum(axis=1)\n",
    "Genus_Tara_taxonomy=Genus_Tara_taxonomy.sort('sum',ascending=False).sort('sum',axis=1, ascending=False).drop('sum').T.drop('sum').T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:26: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "//anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:28: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n"
     ]
    }
   ],
   "source": [
    "ERRList=Tara_taxonomy.columns[Tara_taxonomy.columns.str.startswith('ERR')]\n",
    "import os\n",
    "\n",
    "sbt_gather=pd.DataFrame(columns=ERRList, dtype='float')\n",
    "\n",
    "for ERRfile in glob.glob('sourmash-sigs/abundtrim/sbt_gather/*microbes'):\n",
    "    ERRname= ERRfile.split('/')[3].split('_')[0]\n",
    "    if ERRname in ERRList:\n",
    "        if os.stat(ERRfile).st_size > 0:\n",
    "            with open(ERRfile) as f:\n",
    "                next(f)\n",
    "                for line in f:\n",
    "                    line=line.strip().split(' ')\n",
    "                    percent=float(line[0])\n",
    "                    NC=line[1]\n",
    "                    genus = line[2]\n",
    "                    if genus in sbt_gather.index:\n",
    "                        if sbt_gather.loc[genus, ERRname] > 0:\n",
    "                            sbt_gather.loc[genus, ERRname] += percent\n",
    "                        else:\n",
    "                            sbt_gather.loc[genus, ERRname] = percent\n",
    "                    else:\n",
    "                        sbt_gather.loc[genus, ERRname] = percent\n",
    "\n",
    "sbt_gather.loc['sum']=sbt_gather.sum()\n",
    "sbt_gather=sbt_gather.sort('sum', axis=1, ascending=False)\n",
    "sbt_gather['sum2']=sbt_gather.sum(axis=1)\n",
    "sbt_gather=sbt_gather.sort('sum2', ascending=False)\n",
    "sbt_gather=sbt_gather.drop('sum').T.drop('sum2').T\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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yA7hIRAZjTrkJLGPupyJySXgd2V/E31b04TwUG4WBjWbGiMh6mDnhV2H7y1gg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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120557978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hm=sns.heatmap(sbt_gather)\n",
    "hm.set_xticklabels('')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ERR599041', 'ERR599153', 'ERR599054', 'ERR599094', 'ERR599045',\n",
       "       'ERR599145', 'ERR599075', 'ERR599134', 'ERR599026', 'ERR599049',\n",
       "       ...\n",
       "       'ERR599125', 'ERR599109', 'ERR164409', 'ERR599172', 'ERR598987',\n",
       "       'ERR599037', 'ERR599099', 'ERR599147', 'ERR164408', 'ERR164407'],\n",
       "      dtype='object', length=248)"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sbt_gather.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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VaBaRcaq6TFX/CPxRRA4EPuV8yzZU1W8C3xSRacDvnSg4wA1JtyR3ihHAr4At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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120c85b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Genus_Tara_taxonomy=Genus_Tara_taxonomy.astype('float')\n",
    "hm=sns.heatmap(Genus_Tara_taxonomy.iloc[1:25][sbt_gather.columns])\n",
    "hm.set_xticklabels('')\n",
    "hm.figure.savefig('Tara_taxonomy.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.lookup of                 k                 p                  c                     o  \\\n",
       "0            None              None               None                  None   \n",
       "1      k__Archaea  p__Crenarchaeota            c__MBGA                   o__   \n",
       "2      k__Archaea  p__Crenarchaeota            c__MBGA              o__NRP-J   \n",
       "3      k__Archaea  p__Crenarchaeota            c__MBGB                   o__   \n",
       "4      k__Archaea  p__Crenarchaeota             c__MCG                   o__   \n",
       "5      k__Archaea  p__Crenarchaeota             c__MCG                o__B10   \n",
       "6      k__Archaea  p__Crenarchaeota             c__MCG            o__pGrfC26   \n",
       "7      k__Archaea  p__Crenarchaeota           c__THSCG                   o__   \n",
       "8      k__Archaea  p__Crenarchaeota  c__Thaumarchaeota               o__AK31   \n",
       "9      k__Archaea  p__Crenarchaeota  c__Thaumarchaeota      o__Cenarchaeales   \n",
       "10     k__Archaea  p__Crenarchaeota  c__Thaumarchaeota      o__Cenarchaeales   \n",
       "11     k__Archaea  p__Crenarchaeota  c__Thaumarchaeota      o__Cenarchaeales   \n",
       "12     k__Archaea  p__Crenarchaeota  c__Thaumarchaeota      o__Cenarchaeales   \n",
       "13     k__Archaea  p__Crenarchaeota  c__Thaumarchaeota      o__Cenarchaeales   \n",
       "14     k__Archaea  p__Crenarchaeota  c__Thaumarchaeota      o__Cenarchaeales   \n",
       "15     k__Archaea  p__Crenarchaeota  c__Thaumarchaeota      o__Cenarchaeales   \n",
       "16     k__Archaea  p__Crenarchaeota  c__Thaumarchaeota              o__D-F10   \n",
       "17     k__Archaea  p__Crenarchaeota  c__Thaumarchaeota    o__Nitrosocaldales   \n",
       "18     k__Archaea  p__Crenarchaeota  c__Thaumarchaeota  o__Nitrososphaerales   \n",
       "19     k__Archaea  p__Crenarchaeota  c__Thaumarchaeota  o__Nitrososphaerales   \n",
       "20     k__Archaea  p__Crenarchaeota  c__Thaumarchaeota  o__Nitrososphaerales   \n",
       "21     k__Archaea  p__Crenarchaeota    c__Thermoprotei                   o__   \n",
       "22     k__Archaea  p__Crenarchaeota           c__pUWA2                   o__   \n",
       "23     k__Archaea  p__Euryarchaeota    c__Halobacteria    o__Halobacteriales   \n",
       "24     k__Archaea  p__Euryarchaeota    c__Halobacteria    o__Halobacteriales   \n",
       "25     k__Archaea  p__Euryarchaeota    c__Halobacteria    o__Halobacteriales   \n",
       "26     k__Archaea  p__Euryarchaeota    c__Halobacteria    o__Halobacteriales   \n",
       "27     k__Archaea  p__Euryarchaeota    c__Halobacteria    o__Halobacteriales   \n",
       "28     k__Archaea  p__Euryarchaeota    c__Halobacteria    o__Halobacteriales   \n",
       "29     k__Archaea  p__Euryarchaeota    c__Halobacteria    o__Halobacteriales   \n",
       "...           ...               ...                ...                   ...   \n",
       "2481  k__Bacteria            p__WS2     c__Kazan-3B-09                   o__   \n",
       "2482  k__Bacteria            p__WS3          c__PRR-12                   o__   \n",
       "2483  k__Bacteria            p__WS3          c__PRR-12               o__GN03   \n",
       "2484  k__Bacteria            p__WS3          c__PRR-12               o__GN03   \n",
       "2485  k__Bacteria            p__WS3          c__PRR-12           o__LD1-PA13   \n",
       "2486  k__Bacteria            p__WS3          c__PRR-12          o__PBS-III-9   \n",
       "2487  k__Bacteria            p__WS3          c__PRR-12             o__SSS58A   \n",
       "2488  k__Bacteria            p__WS3          c__PRR-12         o__Sediment-1   \n",
       "2489  k__Bacteria            p__WS3          c__PRR-12         o__Sediment-1   \n",
       "2490  k__Bacteria            p__WS3          c__PRR-12         o__Sediment-1   \n",
       "2491  k__Bacteria            p__WS3          c__PRR-12         o__Sediment-1   \n",
       "2492  k__Bacteria            p__WS4                c__                   o__   \n",
       "2493  k__Bacteria           p__WWE1   c__[Cloacamonae]    o__[Cloacamonales]   \n",
       "2494  k__Bacteria           p__WWE1   c__[Cloacamonae]    o__[Cloacamonales]   \n",
       "2495  k__Bacteria           p__WWE1   c__[Cloacamonae]    o__[Cloacamonales]   \n",
       "2496  k__Bacteria            p__ZB3                c__                   o__   \n",
       "2497  k__Bacteria            p__ZB3           c__BS119                   o__   \n",
       "2498  k__Bacteria   p__[Caldithrix]            c__KSB1                   o__   \n",
       "2499  k__Bacteria   p__[Caldithrix]            c__KSB1              o__GW-22   \n",
       "2500  k__Bacteria   p__[Caldithrix]            c__KSB1            o__MSB-5B5   \n",
       "2501  k__Bacteria   p__[Caldithrix]            c__KSB1           o__Ucn15732   \n",
       "2502  k__Bacteria       p__[Thermi]      c__Deinococci      o__Deinococcales   \n",
       "2503  k__Bacteria       p__[Thermi]      c__Deinococci      o__Deinococcales   \n",
       "2504  k__Bacteria       p__[Thermi]      c__Deinococci      o__Deinococcales   \n",
       "2505  k__Bacteria       p__[Thermi]      c__Deinococci      o__Deinococcales   \n",
       "2506  k__Bacteria       p__[Thermi]      c__Deinococci      o__Deinococcales   \n",
       "2507  k__Bacteria       p__[Thermi]      c__Deinococci      o__Deinococcales   \n",
       "2508  k__Bacteria       p__[Thermi]      c__Deinococci      o__Deinococcales   \n",
       "2509  k__Bacteria       p__[Thermi]      c__Deinococci      o__Deinococcales   \n",
       "2510  k__Bacteria       p__[Thermi]      c__Deinococci          o__Thermales   \n",
       "\n",
       "                          f                            g                 s  \\\n",
       "0                      None                         None              None   \n",
       "1                       f__                          g__               s__   \n",
       "2                       f__                          g__               s__   \n",
       "3                       f__                          g__               s__   \n",
       "4                       f__                          g__               s__   \n",
       "5                       f__                          g__               s__   \n",
       "6                       f__                          g__               s__   \n",
       "7                       f__                          g__               s__   \n",
       "8                       f__                          g__               s__   \n",
       "9                       f__                          g__               s__   \n",
       "10        f__Cenarchaeaceae                          g__               s__   \n",
       "11        f__Cenarchaeaceae               g__Cenarchaeum               s__   \n",
       "12        f__Cenarchaeaceae               g__Cenarchaeum      s__symbiosum   \n",
       "13        f__Cenarchaeaceae            g__Nitrosopumilus               s__   \n",
       "14        f__Cenarchaeaceae            g__Nitrosopumilus         s__pIVWA5   \n",
       "15               f__SAGMA-X                          g__               s__   \n",
       "16                      f__                          g__               s__   \n",
       "17      f__Nitrosocaldaceae   g__CandidatusNitrosocaldus               s__   \n",
       "18    f__Nitrososphaeraceae                          g__               s__   \n",
       "19    f__Nitrososphaeraceae  g__CandidatusNitrososphaera               s__   \n",
       "20    f__Nitrososphaeraceae  g__CandidatusNitrososphaera        s__SCA1145   \n",
       "21                      f__                          g__               s__   \n",
       "22                      f__                          g__               s__   \n",
       "23      f__Halobacteriaceae                          g__               s__   \n",
       "24      f__Halobacteriaceae                    g__ArcF12               s__   \n",
       "25      f__Halobacteriaceae          g__Halobacteriaceae            s__GX3   \n",
       "26      f__Halobacteriaceae          g__Halobacteriaceae            s__R30   \n",
       "27      f__Halobacteriaceae             g__Halobacterium               s__   \n",
       "28      f__Halobacteriaceae               g__Halobaculum               s__   \n",
       "29      f__Halobacteriaceae                g__Halococcus               s__   \n",
       "...                     ...                          ...               ...   \n",
       "2481                    f__                          g__               s__   \n",
       "2482                    f__                          g__               s__   \n",
       "2483                    f__                          g__               s__   \n",
       "2484                f__KSB4                          g__               s__   \n",
       "2485                    f__                          g__               s__   \n",
       "2486                    f__                          g__               s__   \n",
       "2487                    f__                          g__               s__   \n",
       "2488                    f__                          g__               s__   \n",
       "2489               f__CV106                          g__               s__   \n",
       "2490             f__MSB-4E2                          g__               s__   \n",
       "2491              f__PRR-10                          g__               s__   \n",
       "2492                    f__                          g__               s__   \n",
       "2493                f__CW-1                          g__               s__   \n",
       "2494               f__MSBL8                          g__               s__   \n",
       "2495    f__[Cloacamonaceae]                          g__               s__   \n",
       "2496                    f__                          g__               s__   \n",
       "2497                    f__                          g__               s__   \n",
       "2498                    f__                          g__               s__   \n",
       "2499                    f__                          g__               s__   \n",
       "2500                    f__                          g__               s__   \n",
       "2501                    f__                          g__               s__   \n",
       "2502      f__Deinococcaceae                      g__CM44               s__   \n",
       "2503      f__Deinococcaceae            g__Deinobacterium               s__   \n",
       "2504      f__Deinococcaceae               g__Deinococcus               s__   \n",
       "2505      f__Deinococcaceae               g__Deinococcus  s__alpinitundrae   \n",
       "2506        f__Trueperaceae                          g__               s__   \n",
       "2507        f__Trueperaceae                      g__B-42               s__   \n",
       "2508        f__Trueperaceae                    g__GBI-58               s__   \n",
       "2509        f__Trueperaceae                  g__Truepera               s__   \n",
       "2510          f__Thermaceae                   g__Thermus               s__   \n",
       "\n",
       "     ERR164407 ERR164408 ERR164409    ...    ERR599167 ERR599168 ERR599169  \\\n",
       "0           45        35        29    ...        12323      3603      3123   \n",
       "1            0         0         0    ...          103         0         0   \n",
       "2            0         0         0    ...            3         0         0   \n",
       "3            0         0         0    ...            0         0         0   \n",
       "4            0         0         0    ...           14         0         0   \n",
       "5            0         0         0    ...            0         0         0   \n",
       "6            0         0         0    ...            3         0         0   \n",
       "7            0         0         0    ...            0         0         0   \n",
       "8            0         0         0    ...            0         0         0   \n",
       "9            0         0         0    ...            1         0         0   \n",
       "10           0         0         0    ...           36         3         0   \n",
       "11           0         0         0    ...            0         0         0   \n",
       "12           0         0         0    ...            0         0         0   \n",
       "13           0         1         0    ...          353         0         0   \n",
       "14           0         0         0    ...          353         0         0   \n",
       "15           0         0         0    ...            0         0         0   \n",
       "16           0         0         0    ...            0         0         0   \n",
       "17           0         0         0    ...            0         0         0   \n",
       "18           0         0         0    ...            0         0         0   \n",
       "19           0         0         0    ...            0         0         0   \n",
       "20           0         0         0    ...            1         0         0   \n",
       "21           0         0         0    ...            0         0         0   \n",
       "22           0         0         0    ...            0         0         0   \n",
       "23           0         0         0    ...            0         0         0   \n",
       "24           0         0         0    ...            0         0         0   \n",
       "25           0         0         0    ...            0         0         0   \n",
       "26           0         0         0    ...            0         0         0   \n",
       "27           0         0         0    ...            0         0         0   \n",
       "28           0         0         0    ...            0         0         0   \n",
       "29           0         0         0    ...            0         0         0   \n",
       "...        ...       ...       ...    ...          ...       ...       ...   \n",
       "2481         0         0         0    ...            0         0         0   \n",
       "2482         0         0         0    ...            0         0         0   \n",
       "2483         0         0         0    ...            0         0         0   \n",
       "2484         0         0         0    ...            0         0         0   \n",
       "2485         0         0         0    ...            0         0         0   \n",
       "2486         0         0         0    ...            1         0         0   \n",
       "2487         0         0         0    ...            0         0         0   \n",
       "2488         0         0         0    ...            0         0         0   \n",
       "2489         0         0         0    ...            0         0         0   \n",
       "2490         0         0         0    ...            0         0         0   \n",
       "2491         0         0         0    ...            0         0         0   \n",
       "2492         0         0         0    ...            0         0         0   \n",
       "2493         0         0         0    ...            0         0         0   \n",
       "2494         0         0         0    ...            1         0         0   \n",
       "2495         0         0         0    ...            0         0         0   \n",
       "2496         0         0         0    ...            0         0         1   \n",
       "2497         0         0         0    ...            7         5         1   \n",
       "2498         0         0         0    ...            1         0         0   \n",
       "2499         0         0         0    ...            0         0         0   \n",
       "2500         0         0         0    ...            1         0         0   \n",
       "2501         0         0         0    ...            0         0         0   \n",
       "2502         0         0         0    ...            0         0         0   \n",
       "2503         0         0         0    ...            0         0         0   \n",
       "2504         0         0         0    ...            0         0         0   \n",
       "2505         0         0         0    ...            1         0         0   \n",
       "2506         0         0         0    ...            1         0         0   \n",
       "2507         0         0         0    ...            0         0         0   \n",
       "2508         0         0         0    ...            0         0         0   \n",
       "2509         0         0         0    ...            0         0         0   \n",
       "2510         0         0         0    ...            0         0         0   \n",
       "\n",
       "     ERR599170 ERR599171 ERR599172 ERR599173 ERR599174 ERR599175 ERR599176  \n",
       "0        18915      4855      7472      8660      8598      6477      4640  \n",
       "1            2         0        62         0         0        69         0  \n",
       "2            0         0         0         0         0         1         0  \n",
       "3            0         0         0         0         0         0         0  \n",
       "4            0         0        12         0         0        22         0  \n",
       "5            0         0         1         0         0         0         0  \n",
       "6            0         0         0         0         0         0         0  \n",
       "7            0         0         0         0         0         0         0  \n",
       "8            0         0         1         0         0         0         0  \n",
       "9            0         0         0         0         0         0         0  \n",
       "10         541       270         6       265       470        31         0  \n",
       "11           0         0         0         0         0         0         0  \n",
       "12           3         3         0         5         0         1         0  \n",
       "13         103        35        51       222        80       796         2  \n",
       "14          12         3        55         6         3       495         0  \n",
       "15           1         0         0         0         2         0         0  \n",
       "16           0         0         1         0         0         0         0  \n",
       "17           0         0         0         0         0         0         0  \n",
       "18           0         0         0         0         0         0         0  \n",
       "19           0         0         1         0         0         0         0  \n",
       "20           0         0         1         0         0         0         0  \n",
       "21           0         0         0         0         0         0         0  \n",
       "22           0         0         0         0         0         0         0  \n",
       "23           3         0         0         0         0         2         0  \n",
       "24           0         0         0         0         0         0         0  \n",
       "25           0         0         0         0         0         0         0  \n",
       "26           0         0         0         0         0         0         0  \n",
       "27           0         0         0         0         0         0         0  \n",
       "28           0         0         0         0         0         0         0  \n",
       "29           0         0         0         0         0         0         0  \n",
       "...        ...       ...       ...       ...       ...       ...       ...  \n",
       "2481         0         0         0         0         0         0         0  \n",
       "2482         1         0         0         0         0         1         0  \n",
       "2483         0         0         0         0         1         0         0  \n",
       "2484         0         0         0         0         0         0         0  \n",
       "2485         0         0         0         0         0         0         0  \n",
       "2486         0         0         2         0         0         2         0  \n",
       "2487         0         0         0         0         0         0         0  \n",
       "2488         0         0         0         0         0         0         0  \n",
       "2489         0         0         0         0         0         0         0  \n",
       "2490         0         0         0         0         0         0         0  \n",
       "2491         0         0         0         0         0         0         0  \n",
       "2492         0         0         0         0         0         0         0  \n",
       "2493         0         0         0         0         0         0         0  \n",
       "2494         0         0         0         0         0         0         0  \n",
       "2495         0         1         0         0         0         0         0  \n",
       "2496         0         0         0         0         0         0         0  \n",
       "2497        27         7         4        14        12         9         0  \n",
       "2498         0         0         0         0         0         0         0  \n",
       "2499         0         0         0         0         0         0         0  \n",
       "2500         0         1         2         0         0         0         0  \n",
       "2501         0         0         0         1         0         0         0  \n",
       "2502         0         0         0         0         0         0         0  \n",
       "2503         0         0         0         0         0         0         0  \n",
       "2504         0         0         0         0         0         0         0  \n",
       "2505         0         0         0         0         0         0         0  \n",
       "2506         0         0         0         0         0         0         0  \n",
       "2507         0         0         0         0         0         0         0  \n",
       "2508         0         0         0         0         0         0         0  \n",
       "2509         0         0         0         0         0         0         0  \n",
       "2510         0         0         0         0         0         0         0  \n",
       "\n",
       "[2511 rows x 255 columns]>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tara_taxonomy.lookup('Pseu')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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