{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:17:33.633218Z",
     "start_time": "2024-04-30T14:17:33.629178Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "       SBD  Year  Toan   Van  Ly  Hoa  Sinh  Ngoai ngu  Lich su  Dia ly  GDCD  \\\n0  1000001  2022   8.4  8.50 NaN  NaN   NaN        9.2     6.75    6.00  9.00   \n1  1000002  2022   7.2  8.50 NaN  NaN   NaN        9.2     8.75    6.50  8.50   \n2  1000003  2022   NaN  6.50 NaN  NaN   NaN        NaN     9.25    7.50   NaN   \n3  1000004  2022   7.8  8.25 NaN  NaN   NaN        7.8     4.50    6.25  8.25   \n4  1000005  2022   7.2  8.00 NaN  NaN   NaN        7.8     4.75    6.75  8.25   \n\n   MaTinh  \n0       1  \n1       1  \n2       1  \n3       1  \n4       1  ",
      "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>SBD</th>\n      <th>Year</th>\n      <th>Toan</th>\n      <th>Van</th>\n      <th>Ly</th>\n      <th>Hoa</th>\n      <th>Sinh</th>\n      <th>Ngoai ngu</th>\n      <th>Lich su</th>\n      <th>Dia ly</th>\n      <th>GDCD</th>\n      <th>MaTinh</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1000001</td>\n      <td>2022</td>\n      <td>8.4</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>6.75</td>\n      <td>6.00</td>\n      <td>9.00</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1000002</td>\n      <td>2022</td>\n      <td>7.2</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>8.75</td>\n      <td>6.50</td>\n      <td>8.50</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1000003</td>\n      <td>2022</td>\n      <td>NaN</td>\n      <td>6.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.25</td>\n      <td>7.50</td>\n      <td>NaN</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1000004</td>\n      <td>2022</td>\n      <td>7.8</td>\n      <td>8.25</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.50</td>\n      <td>6.25</td>\n      <td>8.25</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1000005</td>\n      <td>2022</td>\n      <td>7.2</td>\n      <td>8.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.75</td>\n      <td>6.75</td>\n      <td>8.25</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('data/2023.csv')\n",
    "df.head()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:26:25.961690Z",
     "start_time": "2024-04-30T14:26:25.510287Z"
    }
   },
   "id": "87c419d6429c43c7",
   "execution_count": 91
  },
  {
   "cell_type": "code",
   "outputs": [],
   "source": [
    "df.rename(columns={'sbd':'SBD','toan':'Toan','ngu_van':'Van','ngoai_ngu':'Ngoai ngu','vat_li':'Ly','hoa_hoc':'Hoa','sinh_hoc':'Sinh','lich_su':'Lich su','dia_li':'Dia ly','gdcd':'GDCD'},inplace=True)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:26:26.022927Z",
     "start_time": "2024-04-30T14:26:26.017855Z"
    }
   },
   "id": "eeaba2eae3ecb057",
   "execution_count": 92
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "              SBD  Year  Toan   Van   Ly   Hoa  Sinh  Ngoai ngu  Lich su  \\\n0         1000001  2022   8.4  8.50  NaN   NaN   NaN        9.2     6.75   \n1         1000002  2022   7.2  8.50  NaN   NaN   NaN        9.2     8.75   \n2         1000003  2022   NaN  6.50  NaN   NaN   NaN        NaN     9.25   \n3         1000004  2022   7.8  8.25  NaN   NaN   NaN        7.8     4.50   \n4         1000005  2022   7.2  8.00  NaN   NaN   NaN        7.8     4.75   \n...           ...   ...   ...   ...  ...   ...   ...        ...      ...   \n1022055  64006933  2022   7.8  6.75  NaN   NaN   NaN        5.4     8.50   \n1022056  64006934  2022   7.4  7.50  6.0  5.75  6.25        6.0      NaN   \n1022057  64006935  2022   6.4  7.00  NaN   NaN   NaN        3.0     5.50   \n1022058  64006936  2022   6.6  7.00  NaN   NaN   NaN        5.8     6.50   \n1022059  64006937  2022   NaN  5.00  NaN   NaN   NaN        NaN     4.25   \n\n         Dia ly  GDCD  MaTinh  \n0          6.00  9.00       1  \n1          6.50  8.50       1  \n2          7.50   NaN       1  \n3          6.25  8.25       1  \n4          6.75  8.25       1  \n...         ...   ...     ...  \n1022055    7.75  9.75      64  \n1022056     NaN   NaN      64  \n1022057    5.75  7.25      64  \n1022058    6.50  9.25      64  \n1022059    4.75   NaN      64  \n\n[1022060 rows x 12 columns]",
      "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>SBD</th>\n      <th>Year</th>\n      <th>Toan</th>\n      <th>Van</th>\n      <th>Ly</th>\n      <th>Hoa</th>\n      <th>Sinh</th>\n      <th>Ngoai ngu</th>\n      <th>Lich su</th>\n      <th>Dia ly</th>\n      <th>GDCD</th>\n      <th>MaTinh</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1000001</td>\n      <td>2022</td>\n      <td>8.4</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>6.75</td>\n      <td>6.00</td>\n      <td>9.00</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1000002</td>\n      <td>2022</td>\n      <td>7.2</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>8.75</td>\n      <td>6.50</td>\n      <td>8.50</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1000003</td>\n      <td>2022</td>\n      <td>NaN</td>\n      <td>6.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.25</td>\n      <td>7.50</td>\n      <td>NaN</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1000004</td>\n      <td>2022</td>\n      <td>7.8</td>\n      <td>8.25</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.50</td>\n      <td>6.25</td>\n      <td>8.25</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1000005</td>\n      <td>2022</td>\n      <td>7.2</td>\n      <td>8.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.75</td>\n      <td>6.75</td>\n      <td>8.25</td>\n      <td>1</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      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>1022055</th>\n      <td>64006933</td>\n      <td>2022</td>\n      <td>7.8</td>\n      <td>6.75</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.4</td>\n      <td>8.50</td>\n      <td>7.75</td>\n      <td>9.75</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022056</th>\n      <td>64006934</td>\n      <td>2022</td>\n      <td>7.4</td>\n      <td>7.50</td>\n      <td>6.0</td>\n      <td>5.75</td>\n      <td>6.25</td>\n      <td>6.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022057</th>\n      <td>64006935</td>\n      <td>2022</td>\n      <td>6.4</td>\n      <td>7.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>3.0</td>\n      <td>5.50</td>\n      <td>5.75</td>\n      <td>7.25</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022058</th>\n      <td>64006936</td>\n      <td>2022</td>\n      <td>6.6</td>\n      <td>7.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.8</td>\n      <td>6.50</td>\n      <td>6.50</td>\n      <td>9.25</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022059</th>\n      <td>64006937</td>\n      <td>2022</td>\n      <td>NaN</td>\n      <td>5.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>4.25</td>\n      <td>4.75</td>\n      <td>NaN</td>\n      <td>64</td>\n    </tr>\n  </tbody>\n</table>\n<p>1022060 rows × 12 columns</p>\n</div>"
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:26:26.792751Z",
     "start_time": "2024-04-30T14:26:26.764707Z"
    }
   },
   "id": "af4ee84f2b53d9c1",
   "execution_count": 93
  },
  {
   "cell_type": "code",
   "outputs": [],
   "source": [
    "df.to_csv('data/2023.csv',index=False)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:26:31.703895Z",
     "start_time": "2024-04-30T14:26:28.009264Z"
    }
   },
   "id": "7381ba88b1bc5875",
   "execution_count": 94
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "              SBD  Year  Toan   Van   Ly   Hoa  Sinh  Ngoai ngu  Lich su  \\\n0         1000001  2022   8.4  8.50  NaN   NaN   NaN        9.2     6.75   \n1         1000002  2022   7.2  8.50  NaN   NaN   NaN        9.2     8.75   \n2         1000003  2022   NaN  6.50  NaN   NaN   NaN        NaN     9.25   \n3         1000004  2022   7.8  8.25  NaN   NaN   NaN        7.8     4.50   \n4         1000005  2022   7.2  8.00  NaN   NaN   NaN        7.8     4.75   \n...           ...   ...   ...   ...  ...   ...   ...        ...      ...   \n1022055  64006933  2022   7.8  6.75  NaN   NaN   NaN        5.4     8.50   \n1022056  64006934  2022   7.4  7.50  6.0  5.75  6.25        6.0      NaN   \n1022057  64006935  2022   6.4  7.00  NaN   NaN   NaN        3.0     5.50   \n1022058  64006936  2022   6.6  7.00  NaN   NaN   NaN        5.8     6.50   \n1022059  64006937  2022   NaN  5.00  NaN   NaN   NaN        NaN     4.25   \n\n         Dia ly  GDCD  MaTinh  \n0          6.00  9.00       1  \n1          6.50  8.50       1  \n2          7.50   NaN       1  \n3          6.25  8.25       1  \n4          6.75  8.25       1  \n...         ...   ...     ...  \n1022055    7.75  9.75      64  \n1022056     NaN   NaN      64  \n1022057    5.75  7.25      64  \n1022058    6.50  9.25      64  \n1022059    4.75   NaN      64  \n\n[1022060 rows x 12 columns]",
      "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>SBD</th>\n      <th>Year</th>\n      <th>Toan</th>\n      <th>Van</th>\n      <th>Ly</th>\n      <th>Hoa</th>\n      <th>Sinh</th>\n      <th>Ngoai ngu</th>\n      <th>Lich su</th>\n      <th>Dia ly</th>\n      <th>GDCD</th>\n      <th>MaTinh</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1000001</td>\n      <td>2022</td>\n      <td>8.4</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>6.75</td>\n      <td>6.00</td>\n      <td>9.00</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1000002</td>\n      <td>2022</td>\n      <td>7.2</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>8.75</td>\n      <td>6.50</td>\n      <td>8.50</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1000003</td>\n      <td>2022</td>\n      <td>NaN</td>\n      <td>6.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.25</td>\n      <td>7.50</td>\n      <td>NaN</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1000004</td>\n      <td>2022</td>\n      <td>7.8</td>\n      <td>8.25</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.50</td>\n      <td>6.25</td>\n      <td>8.25</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1000005</td>\n      <td>2022</td>\n      <td>7.2</td>\n      <td>8.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.75</td>\n      <td>6.75</td>\n      <td>8.25</td>\n      <td>1</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      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>1022055</th>\n      <td>64006933</td>\n      <td>2022</td>\n      <td>7.8</td>\n      <td>6.75</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.4</td>\n      <td>8.50</td>\n      <td>7.75</td>\n      <td>9.75</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022056</th>\n      <td>64006934</td>\n      <td>2022</td>\n      <td>7.4</td>\n      <td>7.50</td>\n      <td>6.0</td>\n      <td>5.75</td>\n      <td>6.25</td>\n      <td>6.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022057</th>\n      <td>64006935</td>\n      <td>2022</td>\n      <td>6.4</td>\n      <td>7.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>3.0</td>\n      <td>5.50</td>\n      <td>5.75</td>\n      <td>7.25</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022058</th>\n      <td>64006936</td>\n      <td>2022</td>\n      <td>6.6</td>\n      <td>7.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.8</td>\n      <td>6.50</td>\n      <td>6.50</td>\n      <td>9.25</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022059</th>\n      <td>64006937</td>\n      <td>2022</td>\n      <td>NaN</td>\n      <td>5.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>4.25</td>\n      <td>4.75</td>\n      <td>NaN</td>\n      <td>64</td>\n    </tr>\n  </tbody>\n</table>\n<p>1022060 rows × 12 columns</p>\n</div>"
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:26:32.671659Z",
     "start_time": "2024-04-30T14:26:32.656410Z"
    }
   },
   "id": "b966a61bc9ee9492",
   "execution_count": 95
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "              SBD  Year  Toan   Van   Ly   Hoa  Sinh  Ngoai ngu  Lich su  \\\n0         1000001  2023   8.4  8.50  NaN   NaN   NaN        9.2     6.75   \n1         1000002  2023   7.2  8.50  NaN   NaN   NaN        9.2     8.75   \n2         1000003  2023   NaN  6.50  NaN   NaN   NaN        NaN     9.25   \n3         1000004  2023   7.8  8.25  NaN   NaN   NaN        7.8     4.50   \n4         1000005  2023   7.2  8.00  NaN   NaN   NaN        7.8     4.75   \n...           ...   ...   ...   ...  ...   ...   ...        ...      ...   \n1022055  64006933  2023   7.8  6.75  NaN   NaN   NaN        5.4     8.50   \n1022056  64006934  2023   7.4  7.50  6.0  5.75  6.25        6.0      NaN   \n1022057  64006935  2023   6.4  7.00  NaN   NaN   NaN        3.0     5.50   \n1022058  64006936  2023   6.6  7.00  NaN   NaN   NaN        5.8     6.50   \n1022059  64006937  2023   NaN  5.00  NaN   NaN   NaN        NaN     4.25   \n\n         Dia ly  GDCD  MaTinh  \n0          6.00  9.00       1  \n1          6.50  8.50       1  \n2          7.50   NaN       1  \n3          6.25  8.25       1  \n4          6.75  8.25       1  \n...         ...   ...     ...  \n1022055    7.75  9.75      64  \n1022056     NaN   NaN      64  \n1022057    5.75  7.25      64  \n1022058    6.50  9.25      64  \n1022059    4.75   NaN      64  \n\n[1022060 rows x 12 columns]",
      "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>SBD</th>\n      <th>Year</th>\n      <th>Toan</th>\n      <th>Van</th>\n      <th>Ly</th>\n      <th>Hoa</th>\n      <th>Sinh</th>\n      <th>Ngoai ngu</th>\n      <th>Lich su</th>\n      <th>Dia ly</th>\n      <th>GDCD</th>\n      <th>MaTinh</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1000001</td>\n      <td>2023</td>\n      <td>8.4</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>6.75</td>\n      <td>6.00</td>\n      <td>9.00</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1000002</td>\n      <td>2023</td>\n      <td>7.2</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>8.75</td>\n      <td>6.50</td>\n      <td>8.50</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1000003</td>\n      <td>2023</td>\n      <td>NaN</td>\n      <td>6.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.25</td>\n      <td>7.50</td>\n      <td>NaN</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1000004</td>\n      <td>2023</td>\n      <td>7.8</td>\n      <td>8.25</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.50</td>\n      <td>6.25</td>\n      <td>8.25</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1000005</td>\n      <td>2023</td>\n      <td>7.2</td>\n      <td>8.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.75</td>\n      <td>6.75</td>\n      <td>8.25</td>\n      <td>1</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      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>1022055</th>\n      <td>64006933</td>\n      <td>2023</td>\n      <td>7.8</td>\n      <td>6.75</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.4</td>\n      <td>8.50</td>\n      <td>7.75</td>\n      <td>9.75</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022056</th>\n      <td>64006934</td>\n      <td>2023</td>\n      <td>7.4</td>\n      <td>7.50</td>\n      <td>6.0</td>\n      <td>5.75</td>\n      <td>6.25</td>\n      <td>6.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022057</th>\n      <td>64006935</td>\n      <td>2023</td>\n      <td>6.4</td>\n      <td>7.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>3.0</td>\n      <td>5.50</td>\n      <td>5.75</td>\n      <td>7.25</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022058</th>\n      <td>64006936</td>\n      <td>2023</td>\n      <td>6.6</td>\n      <td>7.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.8</td>\n      <td>6.50</td>\n      <td>6.50</td>\n      <td>9.25</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022059</th>\n      <td>64006937</td>\n      <td>2023</td>\n      <td>NaN</td>\n      <td>5.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>4.25</td>\n      <td>4.75</td>\n      <td>NaN</td>\n      <td>64</td>\n    </tr>\n  </tbody>\n</table>\n<p>1022060 rows × 12 columns</p>\n</div>"
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.assign(Year=2023)\n",
    "df"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:26:44.976827Z",
     "start_time": "2024-04-30T14:26:44.930869Z"
    }
   },
   "id": "900e6641d27e3088",
   "execution_count": 98
  },
  {
   "cell_type": "code",
   "outputs": [],
   "source": [
    "df.to_csv('data/2023.csv',index=False)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:26:49.959578Z",
     "start_time": "2024-04-30T14:26:46.456016Z"
    }
   },
   "id": "12e11e07fa727e48",
   "execution_count": 99
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "SBD               int64\nToan            float64\nVan             float64\nNgoai ngu       float64\nvat_li          float64\nHoa             float64\nSinh            float64\nLich su         float64\nDia ly          float64\nGDCD            float64\nma_ngoai_ngu     object\nYear              int64\nMaTinh            int64\ndtype: object"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T12:34:06.647891Z",
     "start_time": "2024-04-30T12:34:06.639239Z"
    }
   },
   "id": "2121a36203aea2f6",
   "execution_count": 17
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n"
     ]
    }
   ],
   "source": [
    "sbd_str = str(2000001)\n",
    "len(sbd_str[:6])\n",
    "print(sbd_str[:1])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:10:46.778010Z",
     "start_time": "2024-04-30T14:10:46.774354Z"
    }
   },
   "id": "7b3a1198b88b8942",
   "execution_count": 73
  },
  {
   "cell_type": "code",
   "outputs": [],
   "source": [
    "def get_province_code(sbd):\n",
    "    sbd_str = str(sbd)\n",
    "    if(len(sbd_str)==7):\n",
    "        return sbd_str[:1]\n",
    "    else:\n",
    "        return sbd_str[:2]\n",
    "        \n",
    "df['MaTinh'] = df['SBD'].apply(get_province_code)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:11:48.217361Z",
     "start_time": "2024-04-30T14:11:47.923886Z"
    }
   },
   "id": "b017ce0eb2bdc15f",
   "execution_count": 75
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "       SBD  Toan   Van  Ngoai ngu  Ly  Hoa  Sinh  Lich su  Dia ly  GDCD  \\\n0  1000001   8.4  8.50        9.2 NaN  NaN   NaN     6.75    6.00  9.00   \n1  1000002   7.2  8.50        9.2 NaN  NaN   NaN     8.75    6.50  8.50   \n2  1000003   NaN  6.50        NaN NaN  NaN   NaN     9.25    7.50   NaN   \n3  1000004   7.8  8.25        7.8 NaN  NaN   NaN     4.50    6.25  8.25   \n4  1000005   7.2  8.00        7.8 NaN  NaN   NaN     4.75    6.75  8.25   \n\n  ma_ngoai_ngu MaTinh  \n0           N1      1  \n1           N1      1  \n2          NaN      1  \n3           N1      1  \n4           N1      1  ",
      "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>SBD</th>\n      <th>Toan</th>\n      <th>Van</th>\n      <th>Ngoai ngu</th>\n      <th>Ly</th>\n      <th>Hoa</th>\n      <th>Sinh</th>\n      <th>Lich su</th>\n      <th>Dia ly</th>\n      <th>GDCD</th>\n      <th>ma_ngoai_ngu</th>\n      <th>MaTinh</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1000001</td>\n      <td>8.4</td>\n      <td>8.50</td>\n      <td>9.2</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>6.75</td>\n      <td>6.00</td>\n      <td>9.00</td>\n      <td>N1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1000002</td>\n      <td>7.2</td>\n      <td>8.50</td>\n      <td>9.2</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>8.75</td>\n      <td>6.50</td>\n      <td>8.50</td>\n      <td>N1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1000003</td>\n      <td>NaN</td>\n      <td>6.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.25</td>\n      <td>7.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1000004</td>\n      <td>7.8</td>\n      <td>8.25</td>\n      <td>7.8</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>4.50</td>\n      <td>6.25</td>\n      <td>8.25</td>\n      <td>N1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1000005</td>\n      <td>7.2</td>\n      <td>8.00</td>\n      <td>7.8</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>4.75</td>\n      <td>6.75</td>\n      <td>8.25</td>\n      <td>N1</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:12:05.610489Z",
     "start_time": "2024-04-30T14:12:05.597835Z"
    }
   },
   "id": "515e136f58e4c69b",
   "execution_count": 77
  },
  {
   "cell_type": "code",
   "outputs": [],
   "source": [
    "df.to_csv('data/2023.csv',index=False)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:15:32.253515Z",
     "start_time": "2024-04-30T14:15:29.200187Z"
    }
   },
   "id": "30fe858f2e263521",
   "execution_count": 78
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       SBD  Year  Toan   Van  Ly  Hoa  Sinh  Ngoai ngu  Lich su  Dia ly  GDCD  \\\n",
      "0  1000001  2022   8.4  8.50 NaN  NaN   NaN        9.2     6.75    6.00  9.00   \n",
      "1  1000002  2022   7.2  8.50 NaN  NaN   NaN        9.2     8.75    6.50  8.50   \n",
      "2  1000003  2022   NaN  6.50 NaN  NaN   NaN        NaN     9.25    7.50   NaN   \n",
      "3  1000004  2022   7.8  8.25 NaN  NaN   NaN        7.8     4.50    6.25  8.25   \n",
      "4  1000005  2022   7.2  8.00 NaN  NaN   NaN        7.8     4.75    6.75  8.25   \n",
      "\n",
      "   MaTinh ma_ngoai_ngu  \n",
      "0       1           N1  \n",
      "1       1           N1  \n",
      "2       1          NaN  \n",
      "3       1           N1  \n",
      "4       1           N1  \n"
     ]
    }
   ],
   "source": [
    "new_column_order = ['SBD', 'Year', 'Toan', 'Van', 'Ly', 'Hoa', 'Sinh', 'Ngoai ngu', 'Lich su', 'Dia ly', 'GDCD', 'MaTinh', 'ma_ngoai_ngu']\n",
    "\n",
    "df = df[new_column_order]\n",
    "\n",
    "print(df.head())"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:18:18.321251Z",
     "start_time": "2024-04-30T14:18:18.274248Z"
    }
   },
   "id": "216acc0f7a904835",
   "execution_count": 86
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "              SBD  Year  Toan   Van   Ly   Hoa  Sinh  Ngoai ngu  Lich su  \\\n0         1000001  2022   8.4  8.50  NaN   NaN   NaN        9.2     6.75   \n1         1000002  2022   7.2  8.50  NaN   NaN   NaN        9.2     8.75   \n2         1000003  2022   NaN  6.50  NaN   NaN   NaN        NaN     9.25   \n3         1000004  2022   7.8  8.25  NaN   NaN   NaN        7.8     4.50   \n4         1000005  2022   7.2  8.00  NaN   NaN   NaN        7.8     4.75   \n...           ...   ...   ...   ...  ...   ...   ...        ...      ...   \n1022055  64006933  2022   7.8  6.75  NaN   NaN   NaN        5.4     8.50   \n1022056  64006934  2022   7.4  7.50  6.0  5.75  6.25        6.0      NaN   \n1022057  64006935  2022   6.4  7.00  NaN   NaN   NaN        3.0     5.50   \n1022058  64006936  2022   6.6  7.00  NaN   NaN   NaN        5.8     6.50   \n1022059  64006937  2022   NaN  5.00  NaN   NaN   NaN        NaN     4.25   \n\n         Dia ly  GDCD  MaTinh ma_ngoai_ngu  \n0          6.00  9.00       1           N1  \n1          6.50  8.50       1           N1  \n2          7.50   NaN       1          NaN  \n3          6.25  8.25       1           N1  \n4          6.75  8.25       1           N1  \n...         ...   ...     ...          ...  \n1022055    7.75  9.75      64           N1  \n1022056     NaN   NaN      64           N1  \n1022057    5.75  7.25      64           N1  \n1022058    6.50  9.25      64           N1  \n1022059    4.75   NaN      64          NaN  \n\n[1022060 rows x 13 columns]",
      "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>SBD</th>\n      <th>Year</th>\n      <th>Toan</th>\n      <th>Van</th>\n      <th>Ly</th>\n      <th>Hoa</th>\n      <th>Sinh</th>\n      <th>Ngoai ngu</th>\n      <th>Lich su</th>\n      <th>Dia ly</th>\n      <th>GDCD</th>\n      <th>MaTinh</th>\n      <th>ma_ngoai_ngu</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1000001</td>\n      <td>2022</td>\n      <td>8.4</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>6.75</td>\n      <td>6.00</td>\n      <td>9.00</td>\n      <td>1</td>\n      <td>N1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1000002</td>\n      <td>2022</td>\n      <td>7.2</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>8.75</td>\n      <td>6.50</td>\n      <td>8.50</td>\n      <td>1</td>\n      <td>N1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1000003</td>\n      <td>2022</td>\n      <td>NaN</td>\n      <td>6.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.25</td>\n      <td>7.50</td>\n      <td>NaN</td>\n      <td>1</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1000004</td>\n      <td>2022</td>\n      <td>7.8</td>\n      <td>8.25</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.50</td>\n      <td>6.25</td>\n      <td>8.25</td>\n      <td>1</td>\n      <td>N1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1000005</td>\n      <td>2022</td>\n      <td>7.2</td>\n      <td>8.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.75</td>\n      <td>6.75</td>\n      <td>8.25</td>\n      <td>1</td>\n      <td>N1</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      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>1022055</th>\n      <td>64006933</td>\n      <td>2022</td>\n      <td>7.8</td>\n      <td>6.75</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.4</td>\n      <td>8.50</td>\n      <td>7.75</td>\n      <td>9.75</td>\n      <td>64</td>\n      <td>N1</td>\n    </tr>\n    <tr>\n      <th>1022056</th>\n      <td>64006934</td>\n      <td>2022</td>\n      <td>7.4</td>\n      <td>7.50</td>\n      <td>6.0</td>\n      <td>5.75</td>\n      <td>6.25</td>\n      <td>6.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>64</td>\n      <td>N1</td>\n    </tr>\n    <tr>\n      <th>1022057</th>\n      <td>64006935</td>\n      <td>2022</td>\n      <td>6.4</td>\n      <td>7.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>3.0</td>\n      <td>5.50</td>\n      <td>5.75</td>\n      <td>7.25</td>\n      <td>64</td>\n      <td>N1</td>\n    </tr>\n    <tr>\n      <th>1022058</th>\n      <td>64006936</td>\n      <td>2022</td>\n      <td>6.6</td>\n      <td>7.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.8</td>\n      <td>6.50</td>\n      <td>6.50</td>\n      <td>9.25</td>\n      <td>64</td>\n      <td>N1</td>\n    </tr>\n    <tr>\n      <th>1022059</th>\n      <td>64006937</td>\n      <td>2022</td>\n      <td>NaN</td>\n      <td>5.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>4.25</td>\n      <td>4.75</td>\n      <td>NaN</td>\n      <td>64</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n<p>1022060 rows × 13 columns</p>\n</div>"
     },
     "execution_count": 87,
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    "df"
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     "end_time": "2024-04-30T14:18:25.393362Z",
     "start_time": "2024-04-30T14:18:25.382952Z"
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   "id": "bdf730249480c3a1",
   "execution_count": 87
  },
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   "cell_type": "code",
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   "source": [
    "df=df.drop(columns=['ma_ngoai_ngu'],axis=1)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:18:47.869655Z",
     "start_time": "2024-04-30T14:18:47.837068Z"
    }
   },
   "id": "28f446b3294d3694",
   "execution_count": 88
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "              SBD  Year  Toan   Van   Ly   Hoa  Sinh  Ngoai ngu  Lich su  \\\n0         1000001  2022   8.4  8.50  NaN   NaN   NaN        9.2     6.75   \n1         1000002  2022   7.2  8.50  NaN   NaN   NaN        9.2     8.75   \n2         1000003  2022   NaN  6.50  NaN   NaN   NaN        NaN     9.25   \n3         1000004  2022   7.8  8.25  NaN   NaN   NaN        7.8     4.50   \n4         1000005  2022   7.2  8.00  NaN   NaN   NaN        7.8     4.75   \n...           ...   ...   ...   ...  ...   ...   ...        ...      ...   \n1022055  64006933  2022   7.8  6.75  NaN   NaN   NaN        5.4     8.50   \n1022056  64006934  2022   7.4  7.50  6.0  5.75  6.25        6.0      NaN   \n1022057  64006935  2022   6.4  7.00  NaN   NaN   NaN        3.0     5.50   \n1022058  64006936  2022   6.6  7.00  NaN   NaN   NaN        5.8     6.50   \n1022059  64006937  2022   NaN  5.00  NaN   NaN   NaN        NaN     4.25   \n\n         Dia ly  GDCD  MaTinh  \n0          6.00  9.00       1  \n1          6.50  8.50       1  \n2          7.50   NaN       1  \n3          6.25  8.25       1  \n4          6.75  8.25       1  \n...         ...   ...     ...  \n1022055    7.75  9.75      64  \n1022056     NaN   NaN      64  \n1022057    5.75  7.25      64  \n1022058    6.50  9.25      64  \n1022059    4.75   NaN      64  \n\n[1022060 rows x 12 columns]",
      "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>SBD</th>\n      <th>Year</th>\n      <th>Toan</th>\n      <th>Van</th>\n      <th>Ly</th>\n      <th>Hoa</th>\n      <th>Sinh</th>\n      <th>Ngoai ngu</th>\n      <th>Lich su</th>\n      <th>Dia ly</th>\n      <th>GDCD</th>\n      <th>MaTinh</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1000001</td>\n      <td>2022</td>\n      <td>8.4</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>6.75</td>\n      <td>6.00</td>\n      <td>9.00</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1000002</td>\n      <td>2022</td>\n      <td>7.2</td>\n      <td>8.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.2</td>\n      <td>8.75</td>\n      <td>6.50</td>\n      <td>8.50</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1000003</td>\n      <td>2022</td>\n      <td>NaN</td>\n      <td>6.50</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>9.25</td>\n      <td>7.50</td>\n      <td>NaN</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1000004</td>\n      <td>2022</td>\n      <td>7.8</td>\n      <td>8.25</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.50</td>\n      <td>6.25</td>\n      <td>8.25</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1000005</td>\n      <td>2022</td>\n      <td>7.2</td>\n      <td>8.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>7.8</td>\n      <td>4.75</td>\n      <td>6.75</td>\n      <td>8.25</td>\n      <td>1</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      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>1022055</th>\n      <td>64006933</td>\n      <td>2022</td>\n      <td>7.8</td>\n      <td>6.75</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.4</td>\n      <td>8.50</td>\n      <td>7.75</td>\n      <td>9.75</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022056</th>\n      <td>64006934</td>\n      <td>2022</td>\n      <td>7.4</td>\n      <td>7.50</td>\n      <td>6.0</td>\n      <td>5.75</td>\n      <td>6.25</td>\n      <td>6.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022057</th>\n      <td>64006935</td>\n      <td>2022</td>\n      <td>6.4</td>\n      <td>7.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>3.0</td>\n      <td>5.50</td>\n      <td>5.75</td>\n      <td>7.25</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022058</th>\n      <td>64006936</td>\n      <td>2022</td>\n      <td>6.6</td>\n      <td>7.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>5.8</td>\n      <td>6.50</td>\n      <td>6.50</td>\n      <td>9.25</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>1022059</th>\n      <td>64006937</td>\n      <td>2022</td>\n      <td>NaN</td>\n      <td>5.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>4.25</td>\n      <td>4.75</td>\n      <td>NaN</td>\n      <td>64</td>\n    </tr>\n  </tbody>\n</table>\n<p>1022060 rows × 12 columns</p>\n</div>"
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:18:49.898951Z",
     "start_time": "2024-04-30T14:18:49.889087Z"
    }
   },
   "id": "fe3254e3a718f7f6",
   "execution_count": 89
  },
  {
   "cell_type": "code",
   "outputs": [],
   "source": [
    "df.to_csv('data/2023.csv',index=False)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-30T14:19:20.824556Z",
     "start_time": "2024-04-30T14:19:17.362497Z"
    }
   },
   "id": "27c407a58e045190",
   "execution_count": 90
  },
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   "cell_type": "code",
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   },
   "id": "528e143bf5f95d4e"
  }
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