tests/example-structure-popdata.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example notebook: Structure with pop assignments\n",
    "\n",
    "This notebook shows how to use the `ipyrad.analysis` toolkit to generate structure input files that use population information. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Required software"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# conda install ipyrad -c ipyrad\n",
    "# conda install structure clumpp -c ipyrad\n",
    "# conda install toytree -c eaton-lab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import ipyrad.analysis as ipa\n",
    "import toyplot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a structure analysis object\n",
    "If you include a 'mapfile' then we will use locus information to subsample just a single SNP from each locus so that the resulting data file will meet the expectations of structure that SNPs are \"unlinked\". If you create multiple replicates files using different random seeds then different SNPs will be selected in each rep. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "s = ipa.structure(\n",
    "        name=\"test\", \n",
    "        workdir=\"analysis-structure\",\n",
    "        data=\"analysis-ipyrad/ped_min10_outfiles/ped_min10.str\",\n",
    "        mapfile=\"analysis-ipyrad/ped_min10_outfiles/ped_min10.snps.map\",\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Set params for the structure analysis\n",
    "These values are used to generate the \"mainparams\" and \"extraparams\" files for structure. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "burnin             1000                \n",
       "extracols          0                   \n",
       "label              1                   \n",
       "locdata            0                   \n",
       "mapdistances       0                   \n",
       "markernames        0                   \n",
       "markovphase        0                   \n",
       "missing            -9                  \n",
       "notambiguous       -999                \n",
       "numreps            5000                \n",
       "onerowperind       0                   \n",
       "phased             0                   \n",
       "phaseinfo          0                   \n",
       "phenotype          0                   \n",
       "ploidy             2                   \n",
       "popdata            1                   \n",
       "popflag            1                   \n",
       "recessivealleles   0                   "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## set run parameters (you probably want to run >10X this long)\n",
    "s.mainparams.burnin = 1000\n",
    "s.mainparams.numreps = 5000\n",
    "\n",
    "## tell structure to expect popdata & popflag\n",
    "s.mainparams.popdata = 1\n",
    "s.mainparams.popflag = 1\n",
    "\n",
    "## print all mainparams\n",
    "s.mainparams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "admburnin           500                 \n",
       "alpha               1.0                 \n",
       "alphamax            10.0                \n",
       "alphapriora         1.0                 \n",
       "alphapriorb         2.0                 \n",
       "alphapropsd         0.025               \n",
       "ancestdist          0                   \n",
       "ancestpint          0.9                 \n",
       "computeprob         1                   \n",
       "echodata            0                   \n",
       "fpriormean          0.01                \n",
       "fpriorsd            0.05                \n",
       "freqscorr           1                   \n",
       "gensback            2                   \n",
       "inferalpha          1                   \n",
       "inferlambda         0                   \n",
       "intermedsave        0                   \n",
       "lambda_             1.0                 \n",
       "linkage             0                   \n",
       "locispop            0                   \n",
       "locprior            0                   \n",
       "locpriorinit        1.0                 \n",
       "log10rmax           1.0                 \n",
       "log10rmin           -4.0                \n",
       "log10rpropsd        0.1                 \n",
       "log10rstart         -2.0                \n",
       "maxlocprior         20.0                \n",
       "metrofreq           10                  \n",
       "migrprior           0.01                \n",
       "noadmix             0                   \n",
       "numboxes            1000                \n",
       "onefst              0                   \n",
       "pfrompopflagonly    0                   \n",
       "popalphas           0                   \n",
       "popspecificlambda   0                   \n",
       "printlambda         1                   \n",
       "printlikes          0                   \n",
       "printnet            1                   \n",
       "printqhat           0                   \n",
       "printqsum           1                   \n",
       "randomize           0                   \n",
       "reporthitrate       0                   \n",
       "seed                12345               \n",
       "sitebysite          0                   \n",
       "startatpopinfo      0                   \n",
       "unifprioralpha      1                   \n",
       "updatefreq          10000               \n",
       "usepopinfo          1                   "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## tell structure to use popinfo\n",
    "s.extraparams.usepopinfo = 1\n",
    "\n",
    "## print all other extraparams\n",
    "s.extraparams"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### By default the 'header' of the str file is empty"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>labels</th>\n",
       "      <th>popdata</th>\n",
       "      <th>popflag</th>\n",
       "      <th>locdata</th>\n",
       "      <th>phenotype</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>29154_superba</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>30556_thamno</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30686_cyathophylla</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>32082_przewalskii</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>33413_thamno</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>33588_przewalskii</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>35236_rex</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>35855_rex</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>38362_rex</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>39618_rex</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>40578_rex</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>41478_cyathophylloides</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>41954_cyathophylloides</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    labels popdata popflag locdata phenotype\n",
       "0            29154_superba                                  \n",
       "1             30556_thamno                                  \n",
       "2       30686_cyathophylla                                  \n",
       "3        32082_przewalskii                                  \n",
       "4             33413_thamno                                  \n",
       "5        33588_przewalskii                                  \n",
       "6                35236_rex                                  \n",
       "7                35855_rex                                  \n",
       "8                38362_rex                                  \n",
       "9                39618_rex                                  \n",
       "10               40578_rex                                  \n",
       "11  41478_cyathophylloides                                  \n",
       "12  41954_cyathophylloides                                  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.header"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### You can fill it in by filling the header attribute lists\n",
    "`popdata` is the *a priori* population assignment of an individual to a population. Assignments should be non-zero integers (e.g., 1, 2, 3). Zero is reserved to mean that there is no *a priori* assignment. `popflag` indicates whether or not to use the population assignment in the analysis (1) or to leave it to be inferred (0). So in the example below seven samples have assigned populations (popflag=1), and six samples will have their population assignments inferred (popflag=0). The popdata information will only be used for the seven individuals with assigned pops. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>labels</th>\n",
       "      <th>popdata</th>\n",
       "      <th>popflag</th>\n",
       "      <th>locdata</th>\n",
       "      <th>phenotype</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>29154_superba</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>30556_thamno</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30686_cyathophylla</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>32082_przewalskii</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>33413_thamno</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>33588_przewalskii</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>35236_rex</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>35855_rex</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>38362_rex</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>39618_rex</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>40578_rex</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>41478_cyathophylloides</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>41954_cyathophylloides</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    labels popdata popflag locdata phenotype\n",
       "0            29154_superba       1       1                  \n",
       "1             30556_thamno       3       1                  \n",
       "2       30686_cyathophylla       1       0                  \n",
       "3        32082_przewalskii       2       0                  \n",
       "4             33413_thamno       3       0                  \n",
       "5        33588_przewalskii       2       0                  \n",
       "6                35236_rex       3       0                  \n",
       "7                35855_rex       3       0                  \n",
       "8                38362_rex       3       1                  \n",
       "9                39618_rex       3       1                  \n",
       "10               40578_rex       3       1                  \n",
       "11  41478_cyathophylloides       1       1                  \n",
       "12  41954_cyathophylloides       1       1                  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## assign popdata and popflag by entering a list of values\n",
    "s.popdata = [1, 3, 1, 2, 3, 2, 3, 3, 3, 3, 3, 1, 1]\n",
    "s.popflag = [1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1]\n",
    "\n",
    "## print the header information\n",
    "s.header"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Write the input files and run STRUCTURE\n",
    "This will write the `.str` file (and subsample SNPs if you included a mapfile) with the header information included, and it will write a mainparams and extraparams file with the parameter settings that we entered above. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('/home/deren/Documents/ipyrad/tests/analysis-structure/tmp-test-3-1.mainparams.txt',\n",
       " '/home/deren/Documents/ipyrad/tests/analysis-structure/tmp-test-3-1.extraparams.txt',\n",
       " '/home/deren/Documents/ipyrad/tests/analysis-structure/tmp-test-3-1.strfile.txt')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## writes three input files and then call structure yourself\n",
    "s.write_structure_files(kpop=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Or, submit jobs directly to the cluster\n",
    "If you start an ipcluster instance (see other tutorials) you can submit structure jobs directly to the cluster and easily collect the results, like below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "connected to 40 cores\n"
     ]
    }
   ],
   "source": [
    "## connect to a running ipcluster instance\n",
    "import ipyparallel as ipp\n",
    "ipyclient = ipp.Client()\n",
    "print \"connected to {} cores\".format(len(ipyclient))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "submitted 3 structure jobs [test-K-3]\n"
     ]
    }
   ],
   "source": [
    "## submit job replicates to ipyclient\n",
    "s.run(kpop=3, nreps=3, ipyclient=ipyclient)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## wait for jobs to finish\n",
    "ipyclient.wait()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Collect results and plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "mean scores across 3 replicates.\n"
     ]
    }
   ],
   "source": [
    "## get table of summarized results\n",
    "table = s.get_clumpp_table(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## reorder table by membership in groups\n",
    "table.sort_values(by=[0, 1, 2], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
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       "              popup.style.top = (e.clientY - 20) + \"px\";\n",
       "              popup.style.visibility = \"visible\";\n",
       "              e.stopPropagation();\n",
       "              e.preventDefault();\n",
       "            }\n",
       "\n",
       "          }\n",
       "\n",
       "          for(var i = 0; i != data_tables.length; ++i)\n",
       "          {\n",
       "            var data_table = data_tables[i];\n",
       "            var event_target = document.querySelector(\"#\" + data_table.id);\n",
       "            event_target.oncontextmenu = open_popup(data_table);\n",
       "          }\n",
       "        })();\n",
       "        </script><script>\n",
       "        (function()\n",
       "        {\n",
       "            function _sign(x)\n",
       "            {\n",
       "                return x < 0 ? -1 : x > 0 ? 1 : 0;\n",
       "            }\n",
       "\n",
       "            function _mix(a, b, amount)\n",
       "            {\n",
       "                return ((1.0 - amount) * a) + (amount * b);\n",
       "            }\n",
       "\n",
       "            function _log(x, base)\n",
       "            {\n",
       "                return Math.log(Math.abs(x)) / Math.log(base);\n",
       "            }\n",
       "\n",
       "            function _in_range(a, x, b)\n",
       "            {\n",
       "                var left = Math.min(a, b);\n",
       "                var right = Math.max(a, b);\n",
       "                return left <= x && x <= right;\n",
       "            }\n",
       "\n",
       "            function inside(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(_in_range(segment.range.min, range, segment.range.max))\n",
       "                        return true;\n",
       "                }\n",
       "                return false;\n",
       "            }\n",
       "\n",
       "            function to_domain(range, projection)\n",
       "            {\n",
       "                for(var i = 0; i != projection.length; ++i)\n",
       "                {\n",
       "                    var segment = projection[i];\n",
       "                    if(_in_range(segment.range.bounds.min, range, segment.range.bounds.max))\n",
       "                    {\n",
       "                        if(segment.scale == \"linear\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            return _mix(segment.domain.min, segment.domain.max, amount)\n",
       "                        }\n",
       "                        else if(segment.scale[0] == \"log\")\n",
       "                        {\n",
       "                            var amount = (range - segment.range.min) / (segment.range.max - segment.range.min);\n",
       "                            var base = segment.scale[1];\n",
       "                            return _sign(segment.domain.min) * Math.pow(base, _mix(_log(segment.domain.min, base), _log(segment.domain.max, base), amount));\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            function display_coordinates(e)\n",
       "            {\n",
       "                var current = svg.createSVGPoint();\n",
       "                current.x = e.clientX;\n",
       "                current.y = e.clientY;\n",
       "\n",
       "                for(var axis_id in axes)\n",
       "                {\n",
       "                    var axis = document.querySelector(\"#\" + axis_id);\n",
       "                    var coordinates = axis.querySelector(\".toyplot-coordinates-Axis-coordinates\");\n",
       "                    if(coordinates)\n",
       "                    {\n",
       "                        var projection = axes[axis_id];\n",
       "                        var local = current.matrixTransform(axis.getScreenCTM().inverse());\n",
       "                        if(inside(local.x, projection))\n",
       "                        {\n",
       "                            var domain = to_domain(local.x, projection);\n",
       "                            coordinates.style.visibility = \"visible\";\n",
       "                            coordinates.setAttribute(\"transform\", \"translate(\" + local.x + \")\");\n",
       "                            var text = coordinates.querySelector(\"text\");\n",
       "                            text.textContent = domain.toFixed(2);\n",
       "                        }\n",
       "                        else\n",
       "                        {\n",
       "                            coordinates.style.visibility= \"hidden\";\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            }\n",
       "\n",
       "            var root_id = \"tb03b2f7c67c84fb5aa393b8565449b65\";\n",
       "            var axes = {\"t1171f437b88b481199d3711037f0688b\": [{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 12.5, \"min\": -0.5}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 425.0, \"min\": 0.0}, \"scale\": \"linear\"}], \"t9cc292278783425db7193d96f51399bf\": [{\"domain\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 1.0, \"min\": 0.0}, \"range\": {\"bounds\": {\"max\": Infinity, \"min\": -Infinity}, \"max\": 87.5, \"min\": 0.0}, \"scale\": \"linear\"}]};\n",
       "\n",
       "            var svg = document.querySelector(\"#\" + root_id + \" svg\");\n",
       "            svg.addEventListener(\"click\", display_coordinates);\n",
       "        })();\n",
       "        </script></div></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## build barplot\n",
    "canvas = toyplot.Canvas(width=500, height=250)\n",
    "axes = canvas.cartesian(bounds=(\"10%\", \"90%\", \"10%\", \"45%\"))\n",
    "axes.bars(table)\n",
    "\n",
    "## add labels to x-axis\n",
    "ticklabels = [i for i in table.index.tolist()]\n",
    "axes.x.ticks.locator = toyplot.locator.Explicit(labels=ticklabels)\n",
    "axes.x.ticks.labels.angle = -60\n",
    "axes.x.ticks.show = True\n",
    "axes.x.ticks.labels.offset = 10\n",
    "axes.x.ticks.labels.style = {\"font-size\": \"12px\"}"
   ]
  }
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