1.2. Gathering_Secondary set.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading Levada data sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_levada_data(url, indicators):\n",
    "    \n",
    "    \"\"\"\n",
    "    Loads data from levada website to dataframes\n",
    "    \n",
    "    Args: url - a string\n",
    "          indicators - a list of indicators on a page\n",
    "    \n",
    "    Returns: indicators_dict - a dictionary with dataframes,\n",
    "               where each dataframe contains info on one indicator\n",
    "    \"\"\"\n",
    "    \n",
    "    url = requests.get(url)\n",
    "    levada = pd.read_html(url.text)\n",
    "    \n",
    "    indicators_dict = {}\n",
    "    \n",
    "    for indx in range(len(indicators)):\n",
    "        \n",
    "        # dataframe with indicator series\n",
    "        # this dataframe has columns names: 0, 1, 2, 3\n",
    "        df = levada[2*indx + 1].T\n",
    "        \n",
    "        # rename columns using levada[2*indx]\n",
    "        df.rename(columns={0: \"Month.Year\",\n",
    "                           1: levada[2*indx].iloc[0, 0],\n",
    "                           2: levada[2*indx].iloc[1, 0],\n",
    "                           3: levada[2*indx].iloc[2, 0]},\n",
    "                  inplace=True)\n",
    "        \n",
    "        # column Month.Year is float (e.g. 1.2023), \n",
    "        # we need to extract Month and Year\n",
    "        df[\"Month\"] = df[\"Month.Year\"].astype('int')\n",
    "               \n",
    "        df[\"Year\"] = (df[\"Month.Year\"] * 10000).astype('int')\n",
    "        df[\"Year\"] = df[\"Year\"] % 10000\n",
    "        \n",
    "        df[\"Date\"] = pd.to_datetime(df['Year'].astype(str) \n",
    "                                   +df['Month'].astype(str), \n",
    "                                    format='%Y%m')\n",
    "                \n",
    "        indicators_dict[indicators[indx]] = df\n",
    "            \n",
    "    return indicators_dict       "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data sources"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Approval of the authorities\n",
    "authorities_url = \"https://www.levada.ru/en/ratings/\"\n",
    "\n",
    "# Indicators on the page\n",
    "authorities_approval_indicators = [\n",
    "    'putin',\n",
    "    'prime_minister',\n",
    "    'government'\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Attitudes towards countries\n",
    "countries_url = \"https://www.levada.ru/en/ratings/attitudes-towards-countries/\"\n",
    "\n",
    "# Indicators on the page\n",
    "countries_attitudes_indicators = [\n",
    "    'US',\n",
    "    'EU',\n",
    "    'Ukraine'\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Assessment of situation in the country\n",
    "situation_url = \"https://www.levada.ru/en/ratings/assessment-of-situation-in-the-country/\"\n",
    "\n",
    "# Indicators on the page\n",
    "situation_assessment_indicators = [\n",
    "    'russia_path'\n",
    "    ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Approval of the authorities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "authorities_approval = get_levada_data(authorities_url, authorities_approval_indicators)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Month.Year</th>\n",
       "      <th>Approve</th>\n",
       "      <th>Disapprove</th>\n",
       "      <th>No answer</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8.1999</td>\n",
       "      <td>31.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>8</td>\n",
       "      <td>1999</td>\n",
       "      <td>1999-08-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.1999</td>\n",
       "      <td>53.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>9</td>\n",
       "      <td>1999</td>\n",
       "      <td>1999-09-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.1999</td>\n",
       "      <td>65.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>10</td>\n",
       "      <td>1999</td>\n",
       "      <td>1999-10-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.1999</td>\n",
       "      <td>80.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11</td>\n",
       "      <td>1999</td>\n",
       "      <td>1999-11-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12.1999</td>\n",
       "      <td>79.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12</td>\n",
       "      <td>1999</td>\n",
       "      <td>1999-12-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>9.2022</td>\n",
       "      <td>77.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-09-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>276</th>\n",
       "      <td>10.2022</td>\n",
       "      <td>79.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-10-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>11.2022</td>\n",
       "      <td>79.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-11-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>278</th>\n",
       "      <td>12.2022</td>\n",
       "      <td>81.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-12-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>279</th>\n",
       "      <td>1.2023</td>\n",
       "      <td>82.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2023</td>\n",
       "      <td>2023-01-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>280 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Month.Year  Approve  Disapprove  No answer  Month  Year       Date\n",
       "0        8.1999     31.0        33.0       37.0      8  1999 1999-08-01\n",
       "1        9.1999     53.0        27.0       20.0      9  1999 1999-09-01\n",
       "2       10.1999     65.0        20.0       15.0     10  1999 1999-10-01\n",
       "3       11.1999     80.0        12.0        8.0     11  1999 1999-11-01\n",
       "4       12.1999     79.0        13.0        8.0     12  1999 1999-12-01\n",
       "..          ...      ...         ...        ...    ...   ...        ...\n",
       "275      9.2022     77.0        21.0        2.0      9  2022 2022-09-01\n",
       "276     10.2022     79.0        19.0        2.0     10  2022 2022-10-01\n",
       "277     11.2022     79.0        18.0        3.0     11  2022 2022-11-01\n",
       "278     12.2022     81.0        17.0        2.0     12  2022 2022-12-01\n",
       "279      1.2023     82.0        16.0        2.0      1  2023 2023-01-01\n",
       "\n",
       "[280 rows x 7 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "authorities_approval['putin']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save data to csv\n",
    "for indicator in authorities_approval_indicators:\n",
    "    authorities_approval[indicator].to_csv(indicator+\".csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Attitudes towards countries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "countries_attitudes = get_levada_data(countries_url, countries_attitudes_indicators)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Month.Year</th>\n",
       "      <th>Positive</th>\n",
       "      <th>Negative</th>\n",
       "      <th>Difficult to answer</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.1990</td>\n",
       "      <td>75.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1990</td>\n",
       "      <td>1990-04-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11.1991</td>\n",
       "      <td>80.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11</td>\n",
       "      <td>1991</td>\n",
       "      <td>1991-11-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.1992</td>\n",
       "      <td>74.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>8</td>\n",
       "      <td>1992</td>\n",
       "      <td>1992-08-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.1993</td>\n",
       "      <td>72.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1993</td>\n",
       "      <td>1993-04-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.1997</td>\n",
       "      <td>72.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1997</td>\n",
       "      <td>1997-03-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>2.2022</td>\n",
       "      <td>31.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-02-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>3.2022</td>\n",
       "      <td>17.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-03-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>5.2022</td>\n",
       "      <td>14.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-05-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>8.2022</td>\n",
       "      <td>19.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-08-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>11.2022</td>\n",
       "      <td>18.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-11-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>173 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Month.Year  Positive  Negative  Difficult to answer  Month  Year  \\\n",
       "0        4.1990      75.0       7.0                 19.0      4  1990   \n",
       "1       11.1991      80.0       6.0                 14.0     11  1991   \n",
       "2        8.1992      74.0       8.0                 20.0      8  1992   \n",
       "3        4.1993      72.0       7.0                 22.0      4  1993   \n",
       "4        3.1997      72.0      18.0                 10.0      3  1997   \n",
       "..          ...       ...       ...                  ...    ...   ...   \n",
       "168      2.2022      31.0      55.0                 13.0      2  2022   \n",
       "169      3.2022      17.0      72.0                 11.0      3  2022   \n",
       "170      5.2022      14.0      75.0                 11.0      5  2022   \n",
       "171      8.2022      19.0      71.0                 10.0      8  2022   \n",
       "172     11.2022      18.0      73.0                  9.0     11  2022   \n",
       "\n",
       "          Date  \n",
       "0   1990-04-01  \n",
       "1   1991-11-01  \n",
       "2   1992-08-01  \n",
       "3   1993-04-01  \n",
       "4   1997-03-01  \n",
       "..         ...  \n",
       "168 2022-02-01  \n",
       "169 2022-03-01  \n",
       "170 2022-05-01  \n",
       "171 2022-08-01  \n",
       "172 2022-11-01  \n",
       "\n",
       "[173 rows x 7 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countries_attitudes['US']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save data to csv\n",
    "for indicator in countries_attitudes_indicators:\n",
    "    countries_attitudes[indicator].to_csv(indicator+\".csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Assessment of situation in the country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "situation_assessment = get_levada_data(situation_url, situation_assessment_indicators)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Month.Year</th>\n",
       "      <th>In the right direction</th>\n",
       "      <th>On the wrong track</th>\n",
       "      <th>Difficult to answer</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.1996</td>\n",
       "      <td>32.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7</td>\n",
       "      <td>1996</td>\n",
       "      <td>1996-07-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.1996</td>\n",
       "      <td>21.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>9</td>\n",
       "      <td>1996</td>\n",
       "      <td>1996-09-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11.1996</td>\n",
       "      <td>16.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>11</td>\n",
       "      <td>1996</td>\n",
       "      <td>1996-11-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.1997</td>\n",
       "      <td>22.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1997</td>\n",
       "      <td>1997-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.1997</td>\n",
       "      <td>14.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1997</td>\n",
       "      <td>1997-02-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>306</th>\n",
       "      <td>9.2022</td>\n",
       "      <td>60.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-09-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>10.2022</td>\n",
       "      <td>64.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-10-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>308</th>\n",
       "      <td>11.2022</td>\n",
       "      <td>61.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-11-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>309</th>\n",
       "      <td>12.2022</td>\n",
       "      <td>63.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>12</td>\n",
       "      <td>2022</td>\n",
       "      <td>2022-12-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>310</th>\n",
       "      <td>1.2023</td>\n",
       "      <td>66.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2023</td>\n",
       "      <td>2023-01-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>311 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Month.Year  In the right direction  On the wrong track  \\\n",
       "0        7.1996                    32.0                45.0   \n",
       "1        9.1996                    21.0                58.0   \n",
       "2       11.1996                    16.0                60.0   \n",
       "3        1.1997                    22.0                63.0   \n",
       "4        2.1997                    14.0                69.0   \n",
       "..          ...                     ...                 ...   \n",
       "306      9.2022                    60.0                27.0   \n",
       "307     10.2022                    64.0                24.0   \n",
       "308     11.2022                    61.0                27.0   \n",
       "309     12.2022                    63.0                24.0   \n",
       "310      1.2023                    66.0                24.0   \n",
       "\n",
       "     Difficult to answer  Month  Year       Date  \n",
       "0                   23.0      7  1996 1996-07-01  \n",
       "1                   22.0      9  1996 1996-09-01  \n",
       "2                   24.0     11  1996 1996-11-01  \n",
       "3                   16.0      1  1997 1997-01-01  \n",
       "4                   17.0      2  1997 1997-02-01  \n",
       "..                   ...    ...   ...        ...  \n",
       "306                 12.0      9  2022 2022-09-01  \n",
       "307                 12.0     10  2022 2022-10-01  \n",
       "308                 12.0     11  2022 2022-11-01  \n",
       "309                 13.0     12  2022 2022-12-01  \n",
       "310                 10.0      1  2023 2023-01-01  \n",
       "\n",
       "[311 rows x 7 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "situation_assessment['russia_path']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save to csv\n",
    "indicator = 'russia_path'\n",
    "situation_assessment[indicator].to_csv(indicator+\".csv\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}