Duración estudios de doctorado UdeA

doctoradoudea.ipynb

{
 "metadata": {
  "name": "Estudiantes de doctorado"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": "Estudiantes de doctorado"
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "def read_google_cvs(gss_url=\"http://spreadsheets.google.com\",\\\n    gss_format=\"csv\",\\\n    gss_key=\"0AuLa_xuSIEvxdERYSGVQWDBTX1NCN19QMXVpb0lhWXc\",\\\n    gss_sheet=0,\\\n    gss_query=\"select B,D,E,F,I where (H contains 'GFIF') order by D desc\",\\\n    gss_keep_default_na=False\n    ):\n    import urllib\n    import pandas as pd\n    \"\"\"\n    read a google spreadsheet in cvs format and return a pandas DataFrame object.\n       ....\n       gss_keep_default_na: (False) Blank values are filled with NaN\n    \"\"\"\n    issn_url=\"%s/tq?tqx=out:%s&tq=%s&key=%s&gid=%s\" %(gss_url,\\\n                                           gss_format,\\\n                                           gss_query,\\\n                                           gss_key,\\\n                                           str(gss_sheet))\n \n    gfile=urllib.urlopen(issn_url)\n    return pd.read_csv(gfile,keep_default_na=gss_keep_default_na)",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": "Estudiantes"
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "dfd=read_google_cvs(gss_key=\"0AuLa_xuSIEvxdERYSGVQWDBTX1NCN19QMXVpb0lhWXc\",gss_query=\"select *\",gss_sheet=2)\ndfd.columns",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": "Index([u'Unnamed: 0', u'ESTUDIANTE', u'C\u00e9dula', u'Fecha de ingreso', u'Fecha de graduaci\u00f3n', u'Estado', u'INSTITUTO', u'GRUPO', u'ASESOR', u'CORREO', u'NOMBRE TESIS', u'Fecha de sustentaci\u00f3n', u'ESTANTE', u'SIGNATURA', u'Distinci\u00f3n', u'Becado de', u'Situaci\u00f3n', u'Proyecto ID', u'Pasant\u00eda', u'Doble titulaci\u00f3n', u'Estado Laboral'], dtype='object')"
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "Replace second semester by 0.5 years, e.g: 2012-1 -> 2012 and 2012-2 -> 2012.5"
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "dfd['A\u00f1o de ingreso']=dfd['Fecha de ingreso'].replace('','0').replace('null','0').str.replace('-1','').str.replace('-2','.5').astype('float')\ndfd['A\u00f1o de graduaci\u00f3n']=dfd['Fecha de graduaci\u00f3n'].replace('','0').replace('null','0').str.replace('-1','').str.replace('-2','.5').astype('float').values",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "dfd=dfd[dfd['A\u00f1o de ingreso']>=2004]\ndfg=dfd[dfd['Estado']=='Graduado'].reset_index(drop=True)\ndfg['Duraci\u00f3n']=(dfg['A\u00f1o de graduaci\u00f3n']-dfg['A\u00f1o de ingreso'])\ndfg=dfg.sort('Duraci\u00f3n').reset_index(drop=True)\ndfg=dfg.replace(2.5,3)\ndfg['Duraci\u00f3n'].value_counts().plot(kind='barh', rot=0)",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": "<matplotlib.axes.AxesSubplot at 0x7fcca176b690>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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bb76pffv2qaioSJFIRAcPHpzJQwIA7hB7rQDW4zryIGOvFQAIAQa5ZxzTBfjMMV2AjxzT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\n",
       "text": "<matplotlib.figure.Figure at 0x7fcca19bdd50>"
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "print 'A\u00f1os |', 'N\u00famero de estudiantes graduados'\ndfg['Duraci\u00f3n'].value_counts()",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "A\u00f1os | N\u00famero de estudiantes graduados\n"
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 53,
       "text": "3.0    6\n4.5    4\n3.5    3\n5.5    2\n6.0    1\n4.0    1\ndtype: int64"
      }
     ],
     "prompt_number": 53
    }
   ],
   "metadata": {}
  }
 ]
}