{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "d = {'AÑO': [2001, 2003, 2003, 2001],\n",
    "     'SEXO': ['MASCULINO', 'FEMENINO', 'FEMENINO', 'FEMENINO'],\n",
    "     'GENERO MUSICAL': ['BACHATA, SALSA', 'POP, SALSA', 'POP', 'POP, COUNTRY']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AÑO</th>\n",
       "      <th>GENERO MUSICAL</th>\n",
       "      <th>SEXO</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2001</td>\n",
       "      <td>BACHATA, SALSA</td>\n",
       "      <td>MASCULINO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2003</td>\n",
       "      <td>POP, SALSA</td>\n",
       "      <td>FEMENINO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2003</td>\n",
       "      <td>POP</td>\n",
       "      <td>FEMENINO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2001</td>\n",
       "      <td>POP, COUNTRY</td>\n",
       "      <td>FEMENINO</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    AÑO  GENERO MUSICAL       SEXO\n",
       "0  2001  BACHATA, SALSA  MASCULINO\n",
       "1  2003      POP, SALSA   FEMENINO\n",
       "2  2003             POP   FEMENINO\n",
       "3  2001    POP, COUNTRY   FEMENINO"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genero_data = pd.DataFrame(d)\n",
    "genero_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "POP         3\n",
       " SALSA      2\n",
       "BACHATA     1\n",
       " COUNTRY    1\n",
       "Name: GENERO, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "musica = genero_data['GENERO MUSICAL'].str.split(',').apply(pd.Series, 1).stack()\n",
    "musica.index = musica.index.droplevel(-1)\n",
    "musica.name='GENERO'\n",
    "pd.value_counts(musica)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AÑO</th>\n",
       "      <th>SEXO</th>\n",
       "      <th>GENERO</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2001</td>\n",
       "      <td>MASCULINO</td>\n",
       "      <td>BACHATA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2001</td>\n",
       "      <td>MASCULINO</td>\n",
       "      <td>SALSA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2003</td>\n",
       "      <td>FEMENINO</td>\n",
       "      <td>POP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2003</td>\n",
       "      <td>FEMENINO</td>\n",
       "      <td>SALSA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2003</td>\n",
       "      <td>FEMENINO</td>\n",
       "      <td>POP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2001</td>\n",
       "      <td>FEMENINO</td>\n",
       "      <td>POP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2001</td>\n",
       "      <td>FEMENINO</td>\n",
       "      <td>COUNTRY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    AÑO       SEXO    GENERO\n",
       "0  2001  MASCULINO   BACHATA\n",
       "0  2001  MASCULINO     SALSA\n",
       "1  2003   FEMENINO       POP\n",
       "1  2003   FEMENINO     SALSA\n",
       "2  2003   FEMENINO       POP\n",
       "3  2001   FEMENINO       POP\n",
       "3  2001   FEMENINO   COUNTRY"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "del genero_data['GENERO MUSICAL']\n",
    "genero_data = genero_data.join(musica)\n",
    "genero_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "POP         3\n",
       " SALSA      2\n",
       "BACHATA     1\n",
       " COUNTRY    1\n",
       "Name: GENERO, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.value_counts(genero_data['GENERO'])"
   ]
  }
 ],
 "metadata": {
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   "display_name": "Python 3",
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   "name": "python3"
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  "language_info": {
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   "file_extension": ".py",
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