{

 "cells": [

  {

   "cell_type": "code",

   "execution_count": null,

   "metadata": {},

   "outputs": [],

   "source": [

    "import pandas as pd\n",

    "import numpy as np"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": null,

   "metadata": {},

   "outputs": [],

   "source": [

    "summary = pd.read_table('fastqc.txt', sep='\\t')"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": null,

   "metadata": {},

   "outputs": [],

   "source": [

    "summary.set_index('sample_id', inplace=True, drop=False)\n",

    "qc_status = summary.iloc[:, 9:].copy()\n",

    "qc_status.fillna('NA')\n",

    "qc_status = qc_status.astype('str')\n",

    "sample_ids = qc_status.index.values\n",

    "sections = qc_status.columns.values\n",

    "def style_func(val):\n",

    "    status, row, col = val.split('|')\n",

    "    row, col = int(row), int(col)\n",

    "    color = {'pass': 'green', 'fail': 'red', 'warn': 'orange'}.get(status, 'gray')\n",

    "    return '<a href=\"../fastqc/{sample_id}_fastqc.html#M{section}\" style=\"color: {color}\">{status}</a>'.format(\n",

    "        sample_id=sample_ids[row], color=color, status=status, section=col)\n",

    "\n",

    "pd.DataFrame(qc_status.values \\\n",

    "             + '|' + np.arange(qc_status.shape[0]).astype('str')[:, np.newaxis] \\\n",

    "             + '|' + np.arange(qc_status.shape[1]).astype('str')[np.newaxis, :],\n",

    "             index=qc_status.index, columns=qc_status.columns) \\\n",

    "    .style.format(style_func)"

   ]

  }

 ],

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   "name": "python3"

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  "laugnage_info": {

   "codemirror_mode": {

    "name": "ipython",

    "version": 3

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   "file_extension": ".py",

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