{
 "metadata": {
  "name": "",
  "signature": "sha256:3c972a8d25d3c4e3dee34035fc64c1d94ca60a988b96a6aee969248392b205c6"
 },
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 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This short script converts the Excel files from the supplementary materials of Schich et al. to CSV text files (compressed with gzip).\n",
      "\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "\n",
      "fnames = [\"SchichDataS1_FB.xlsx\", \"SchichDataS2_AKL.xlsx\",\n",
      "          \"SchichDataS3_ULAN.xlsx\", \"SchichDataS4_WCEN.xlsx\"]\n",
      "\n",
      "for fi in fnames:\n",
      "    print fi\n",
      "    data = pd.read_excel(fi)\n",
      "    data = data.convert_objects(convert_numeric=True)\n",
      "    out_name = fi.replace(\".xlsx\", \".csv.gz\")\n",
      "    out = gzip.open(out_name, \"w\")\n",
      "    data.to_csv(out, encoding=\"utf-8\")\n",
      "    out.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}