how_to_read_SPSS_sav_files_in_Python.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read .sav File using Pyreadstat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pyreadstat\n",
    "\n",
    "df, meta = pyreadstat.read_sav('./SimData/survey_1.sav')\n",
    "\n",
    "type(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>Day</th>\n",
       "      <th>Age</th>\n",
       "      <th>Response</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>John</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.348566</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>Billie</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.377047</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>Robert</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.274094</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.0</td>\n",
       "      <td>Don</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.415665</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>Joseph</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.503052</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID    Name     Day   Age  Response  Gender\n",
       "0  1.0    John  Fourth  23.0  0.348566     0.0\n",
       "1  2.0  Billie  Fourth  22.0  0.377047     0.0\n",
       "2  3.0  Robert  Fourth  20.0  0.274094     0.0\n",
       "3  4.0     Don  Fourth  27.0  0.415665     0.0\n",
       "4  5.0  Joseph  Fourth  21.0  0.503052     0.0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read SPSS File using Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>Day</th>\n",
       "      <th>Age</th>\n",
       "      <th>Response</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>196.0</td>\n",
       "      <td>Francisca</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.480961</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>197.0</td>\n",
       "      <td>Nia</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.419361</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>198.0</td>\n",
       "      <td>Christina</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.273347</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>199.0</td>\n",
       "      <td>Marta</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.375722</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>200.0</td>\n",
       "      <td>Julia</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.151065</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID       Name     Day   Age  Response  Gender\n",
       "195  196.0  Francisca  Fourth  27.0  0.480961     1.0\n",
       "196  197.0        Nia  Fourth  20.0  0.419361     1.0\n",
       "197  198.0  Christina  Fourth  29.0  0.273347     1.0\n",
       "198  199.0      Marta  Fourth  26.0  0.375722     1.0\n",
       "199  200.0      Julia  Fourth  25.0  0.151065     1.0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_spss('./SimData/survey_1.sav')\n",
    "\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Day</th>\n",
       "      <th>Age</th>\n",
       "      <th>Response</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.348566</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.377047</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.274094</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.0</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.415665</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>Fourth</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.503052</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID     Day   Age  Response  Gender\n",
       "0  1.0  Fourth  23.0  0.348566     0.0\n",
       "1  2.0  Fourth  22.0  0.377047     0.0\n",
       "2  3.0  Fourth  20.0  0.274094     0.0\n",
       "3  4.0  Fourth  27.0  0.415665     0.0\n",
       "4  5.0  Fourth  21.0  0.503052     0.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = ['ID', 'Day', 'Age', 'Response', 'Gender']\n",
    "df = pd.read_spss('./SimData/survey_1.sav', usecols=cols)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Write a .sav file using Pyreadstat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pyreadstat.write_sav(df, './SimData/survey_1_copy.sav')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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