0302 - Data Types.ipynb

{
 "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": [
    "my_series = pd.Series([23, 54, 62, 25])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    23\n",
       "1    54\n",
       "2    62\n",
       "3    25\n",
       "dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "eu_loans = pd.read_csv('data/eu_revolving_loans.csv', header=[1,2,3],\n",
    "                      skiprows=1, index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                                  Collection:                                 Period\\Unit:        \n",
       "Austria                           End of period (E)                           [Percent per annum ]    float64\n",
       "Belgium                           End of period (E)                           [Percent per annum ]    float64\n",
       "Cyprus                            End of period (E)                           [Percent per annum ]    float64\n",
       "Germany                           End of period (E)                           [Percent per annum ]    float64\n",
       "Estonia                           End of period (E)                           [Percent per annum ]     object\n",
       "Spain                             End of period (E)                           [Percent per annum ]    float64\n",
       "Finland                           End of period (E)                           [Percent per annum ]    float64\n",
       "France                            End of period (E)                           [Percent per annum ]    float64\n",
       "Greece (GR)                       End of period (E)                           [Percent per annum ]    float64\n",
       "Ireland                           End of period (E)                           [Percent per annum ]    float64\n",
       "Italy                             End of period (E)                           [Percent per annum ]    float64\n",
       "Lithuania                         End of period (E)                           [Percent per annum ]    float64\n",
       "Luxembourg                        End of period (E)                           [Percent per annum ]    float64\n",
       "Latvia                            End of period (E)                           [Percent per annum ]    float64\n",
       "Malta                             End of period (E)                           [Percent per annum ]     object\n",
       "Netherlands                       End of period (E)                           [Percent per annum ]    float64\n",
       "Portugal                          End of period (E)                           [Percent per annum ]    float64\n",
       "Slovenia                          End of period (E)                           [Percent per annum ]     object\n",
       "Slovakia                          End of period (E)                           [Percent per annum ]     object\n",
       "Euro area (changing composition)  Average of observations through period (A)  [Percent per annum ]    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eu_loans.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "could not convert string to float: -",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-6-ea89e219219d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0meu_loans\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Slovenia'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfloat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/Users/kjam/.virtualenvs/oreilly_class/lib/python2.7/site-packages/pandas/core/generic.pyc\u001b[0m in \u001b[0;36mastype\u001b[0;34m(self, dtype, copy, raise_on_error, **kwargs)\u001b[0m\n\u001b[1;32m   2945\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2946\u001b[0m         mgr = self._data.astype(dtype=dtype, copy=copy,\n\u001b[0;32m-> 2947\u001b[0;31m                                 raise_on_error=raise_on_error, **kwargs)\n\u001b[0m\u001b[1;32m   2948\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_constructor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmgr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__finalize__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2949\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/kjam/.virtualenvs/oreilly_class/lib/python2.7/site-packages/pandas/core/internals.pyc\u001b[0m in \u001b[0;36mastype\u001b[0;34m(self, dtype, **kwargs)\u001b[0m\n\u001b[1;32m   2871\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2872\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2873\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'astype'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2874\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2875\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mconvert\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/kjam/.virtualenvs/oreilly_class/lib/python2.7/site-packages/pandas/core/internals.pyc\u001b[0m in \u001b[0;36mapply\u001b[0;34m(self, f, axes, filter, do_integrity_check, consolidate, **kwargs)\u001b[0m\n\u001b[1;32m   2830\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2831\u001b[0m             \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'mgr'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2832\u001b[0;31m             \u001b[0mapplied\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2833\u001b[0m             \u001b[0mresult_blocks\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_extend_blocks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mapplied\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresult_blocks\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2834\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/kjam/.virtualenvs/oreilly_class/lib/python2.7/site-packages/pandas/core/internals.pyc\u001b[0m in \u001b[0;36mastype\u001b[0;34m(self, dtype, copy, raise_on_error, values, **kwargs)\u001b[0m\n\u001b[1;32m    420\u001b[0m                **kwargs):\n\u001b[1;32m    421\u001b[0m         return self._astype(dtype, copy=copy, raise_on_error=raise_on_error,\n\u001b[0;32m--> 422\u001b[0;31m                             values=values, **kwargs)\n\u001b[0m\u001b[1;32m    423\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    424\u001b[0m     def _astype(self, dtype, copy=False, raise_on_error=True, values=None,\n",
      "\u001b[0;32m/Users/kjam/.virtualenvs/oreilly_class/lib/python2.7/site-packages/pandas/core/internals.pyc\u001b[0m in \u001b[0;36m_astype\u001b[0;34m(self, dtype, copy, raise_on_error, values, klass, mgr, **kwargs)\u001b[0m\n\u001b[1;32m    463\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    464\u001b[0m                 \u001b[0;31m# _astype_nansafe works fine with 1-d only\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 465\u001b[0;31m                 \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_astype_nansafe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    466\u001b[0m                 \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    467\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/kjam/.virtualenvs/oreilly_class/lib/python2.7/site-packages/pandas/core/common.pyc\u001b[0m in \u001b[0;36m_astype_nansafe\u001b[0;34m(arr, dtype, copy)\u001b[0m\n\u001b[1;32m   2629\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2630\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2631\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2632\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mview\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2633\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: could not convert string to float: -"
     ]
    }
   ],
   "source": [
    "eu_loans['Slovenia'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "eu_loans = pd.read_csv('data/eu_revolving_loans.csv', header=[1,2,3],\n",
    "                      index_col=0, skiprows=1, na_values=['-'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                                  Collection:                                 Period\\Unit:        \n",
       "Austria                           End of period (E)                           [Percent per annum ]    float64\n",
       "Belgium                           End of period (E)                           [Percent per annum ]    float64\n",
       "Cyprus                            End of period (E)                           [Percent per annum ]    float64\n",
       "Germany                           End of period (E)                           [Percent per annum ]    float64\n",
       "Estonia                           End of period (E)                           [Percent per annum ]    float64\n",
       "Spain                             End of period (E)                           [Percent per annum ]    float64\n",
       "Finland                           End of period (E)                           [Percent per annum ]    float64\n",
       "France                            End of period (E)                           [Percent per annum ]    float64\n",
       "Greece (GR)                       End of period (E)                           [Percent per annum ]    float64\n",
       "Ireland                           End of period (E)                           [Percent per annum ]    float64\n",
       "Italy                             End of period (E)                           [Percent per annum ]    float64\n",
       "Lithuania                         End of period (E)                           [Percent per annum ]    float64\n",
       "Luxembourg                        End of period (E)                           [Percent per annum ]    float64\n",
       "Latvia                            End of period (E)                           [Percent per annum ]    float64\n",
       "Malta                             End of period (E)                           [Percent per annum ]    float64\n",
       "Netherlands                       End of period (E)                           [Percent per annum ]    float64\n",
       "Portugal                          End of period (E)                           [Percent per annum ]    float64\n",
       "Slovenia                          End of period (E)                           [Percent per annum ]    float64\n",
       "Slovakia                          End of period (E)                           [Percent per annum ]    float64\n",
       "Euro area (changing composition)  Average of observations through period (A)  [Percent per annum ]    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eu_loans.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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