2_hydro_data_xlsx_to_csv.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "280b6632",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import libraries\n",
    "import xlrd\n",
    "import openpyxl\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5b718938",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Name of selected of data:\n",
      "=====================================\n",
      "stations_yearstart_yearend_source\n",
      "=====================================\n",
      "Stations:\n",
      "ansongo: a\n",
      "kandadji: k\n",
      "niamey: n\n",
      "=====================================\n",
      "Years:\n",
      "1981\n",
      "2000\n",
      "2010\n",
      "2020\n",
      "=====================================\n",
      "Source:\n",
      "M. Bernard (AGHRYMET): be\n",
      "M. Hamatan (AGHRYMET): ha\n",
      "M. Bachir (ABN): ba\n",
      "=====================================\n"
     ]
    }
   ],
   "source": [
    "# label of data\n",
    "print(\"\"\"Name of selected of data:\n",
    "=====================================\n",
    "stations_yearstart_yearend_source\n",
    "=====================================\n",
    "Stations:\n",
    "ansongo: a\n",
    "kandadji: k\n",
    "niamey: n\n",
    "=====================================\n",
    "Years:\n",
    "1981\n",
    "2000\n",
    "2010\n",
    "2020\n",
    "=====================================\n",
    "Source:\n",
    "M. Bernard (AGHRYMET): be\n",
    "M. Hamatan (AGHRYMET): ha\n",
    "M. Bachir (ABN): ba\n",
    "=====================================\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3aec1ab1",
   "metadata": {},
   "source": [
    "## Load hydro data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "764133be",
   "metadata": {},
   "outputs": [],
   "source": [
    "# loaded data\n",
    "# rename headers\n",
    "# drop useless rows at head (optimal)\n",
    "# drop useless rows at tail (optimal)\n",
    "# replace -9999.0 by NaN (optimal)\n",
    "# split columns of dataframe (optimal)\n",
    "# set date in datetime\n",
    "# delete double dates (optimal)\n",
    "# set index and drop index column (optimal)\n",
    "# view dataframe\n",
    "# save data to csv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdf8b16f",
   "metadata": {},
   "source": [
    "### Bernard AGRHYMET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c6701073",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\wascal-gsp\\anaconda3\\envs\\tf\\lib\\site-packages\\ipykernel_launcher.py:11: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  # This is added back by InteractiveShellApp.init_path()\n",
      "C:\\Users\\wascal-gsp\\anaconda3\\envs\\tf\\lib\\site-packages\\ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  if sys.path[0] == '':\n",
      "C:\\Users\\wascal-gsp\\anaconda3\\envs\\tf\\lib\\site-packages\\ipykernel_launcher.py:13: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  del sys.path[0]\n"
     ]
    }
   ],
   "source": [
    "akn_1981_2016_be = pd.read_excel('./hydro_data/Ansongo_Kandadji_Niamey_Debits_journaliers_real_bernard_agrhymet.xlsx', engine='openpyxl')\n",
    "\n",
    "akn_1981_2016_be = akn_1981_2016_be.drop(akn_1981_2016_be.index[13051:13088])\n",
    "akn_1981_2016_be = akn_1981_2016_be.replace(-9999.0, np.nan)\n",
    "akn_1981_2016_be = akn_1981_2016_be.rename(columns={'DATE':'Date'})\n",
    "\n",
    "a_1981_2016_be = akn_1981_2016_be[['Date', 'Ansongo']]\n",
    "k_1981_2016_be = akn_1981_2016_be[['Date', 'Kandadji']]\n",
    "n_1981_2016_be = akn_1981_2016_be[['Date', 'Niamey']]\n",
    "\n",
    "a_1981_2016_be['Date'] = pd.to_datetime(akn_1981_2016_be['Date'], infer_datetime_format=True) \n",
    "k_1981_2016_be['Date'] = pd.to_datetime(akn_1981_2016_be['Date'], infer_datetime_format=True)  \n",
    "n_1981_2016_be['Date'] = pd.to_datetime(akn_1981_2016_be['Date'], infer_datetime_format=True) \n",
    "#akn_1981_2016_be = pd.to_datetime(akn_1981_2016_be.pop('Date'), infer_datetime_format=True)\n",
    "\n",
    "#akn_1981_2016_be\n",
    "#a_1981_2016_be\n",
    "#k_1981_2016_be\n",
    "#n_1981_2016_be\n",
    "\n",
    "#a_1981_2016_be.to_csv('./hydro_data/csv/a_1981_2016_be.csv', index=False)\n",
    "#k_1981_2016_be.to_csv('./hydro_data/csv/k_1981_2016_be.csv', index=False)\n",
    "#n_1981_2016_be.to_csv('./hydro_data/csv/n_1981_2016_be.csv', index=False)\n",
    "#akn_1981_2016_be.to_csv('./hydro_data/csv/akn_1981_2016_be.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "434734e9",
   "metadata": {},
   "source": [
    "### Hamatan AGRHYMET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2356dcbb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Ansongo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1981-06-01</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1981-06-02</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1981-06-03</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1981-06-04</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1981-06-05</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10801</th>\n",
       "      <td>2010-12-27</td>\n",
       "      <td>1751.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10802</th>\n",
       "      <td>2010-12-28</td>\n",
       "      <td>1753.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10803</th>\n",
       "      <td>2010-12-29</td>\n",
       "      <td>1752.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10804</th>\n",
       "      <td>2010-12-30</td>\n",
       "      <td>1749.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10805</th>\n",
       "      <td>2010-12-31</td>\n",
       "      <td>1743.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10806 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date  Ansongo\n",
       "0     1981-06-01     14.0\n",
       "1     1981-06-02     13.0\n",
       "2     1981-06-03     13.0\n",
       "3     1981-06-04     13.0\n",
       "4     1981-06-05     13.0\n",
       "...          ...      ...\n",
       "10801 2010-12-27   1751.0\n",
       "10802 2010-12-28   1753.0\n",
       "10803 2010-12-29   1752.0\n",
       "10804 2010-12-30   1749.0\n",
       "10805 2010-12-31   1743.0\n",
       "\n",
       "[10806 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_1981_2010_ha = pd.read_excel('./hydro_data/Qj_Ansongo_1981-2010_real_hamatan_agrhymet.xlsx', engine='openpyxl')\n",
    "\n",
    "a_1981_2010_ha = a_1981_2010_ha.rename(columns={'Data':'Ansongo'})\n",
    "a_1981_2010_ha['Date'] = pd.to_datetime(a_1981_2010_ha['Date'], infer_datetime_format=True)\n",
    "\n",
    "a_1981_2010_ha\n",
    "\n",
    "#a_1981_2010_ha.to_csv('./hydro_data/csv/a_1981_2010_ha.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1a54f588",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Kandadji</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1981-01-01</td>\n",
       "      <td>1470.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1981-01-02</td>\n",
       "      <td>1460.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1981-01-03</td>\n",
       "      <td>1450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1981-01-04</td>\n",
       "      <td>1440.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1981-01-05</td>\n",
       "      <td>1440.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10952</th>\n",
       "      <td>2010-12-27</td>\n",
       "      <td>570.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10953</th>\n",
       "      <td>2010-12-28</td>\n",
       "      <td>571.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10954</th>\n",
       "      <td>2010-12-29</td>\n",
       "      <td>571.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10955</th>\n",
       "      <td>2010-12-30</td>\n",
       "      <td>571.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10956</th>\n",
       "      <td>2010-12-31</td>\n",
       "      <td>572.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10957 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date  Kandadji\n",
       "0     1981-01-01    1470.0\n",
       "1     1981-01-02    1460.0\n",
       "2     1981-01-03    1450.0\n",
       "3     1981-01-04    1440.0\n",
       "4     1981-01-05    1440.0\n",
       "...          ...       ...\n",
       "10952 2010-12-27     570.0\n",
       "10953 2010-12-28     571.0\n",
       "10954 2010-12-29     571.0\n",
       "10955 2010-12-30     571.0\n",
       "10956 2010-12-31     572.0\n",
       "\n",
       "[10957 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k_1981_2010_ha = pd.read_excel('./hydro_data/Qj_Kandadji_1981-2010_real_hamatan_agrhymet.xlsx', engine='openpyxl')\n",
    "\n",
    "k_1981_2010_ha = k_1981_2010_ha.rename(columns={'date':'Date', 'Qj':'Kandadji'})\n",
    "k_1981_2010_ha['Date'] = pd.to_datetime(k_1981_2010_ha['Date'], infer_datetime_format=True)\n",
    "\n",
    "k_1981_2010_ha\n",
    "\n",
    "#k_1981_2010_ha.to_csv('./hydro_data/csv/k_1981_2010_ha.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a2d8adca",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Niamey</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1981-05-01</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1981-05-02</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1981-05-03</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1981-05-04</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1981-05-05</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10952</th>\n",
       "      <td>2011-04-26</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10953</th>\n",
       "      <td>2011-04-27</td>\n",
       "      <td>189.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10954</th>\n",
       "      <td>2011-04-28</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10955</th>\n",
       "      <td>2011-04-29</td>\n",
       "      <td>177.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10956</th>\n",
       "      <td>2011-04-30</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10957 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date  Niamey\n",
       "0     1981-05-01     NaN\n",
       "1     1981-05-02     NaN\n",
       "2     1981-05-03     NaN\n",
       "3     1981-05-04     NaN\n",
       "4     1981-05-05     NaN\n",
       "...          ...     ...\n",
       "10952 2011-04-26   196.0\n",
       "10953 2011-04-27   189.0\n",
       "10954 2011-04-28   183.0\n",
       "10955 2011-04-29   177.0\n",
       "10956 2011-04-30   175.0\n",
       "\n",
       "[10957 rows x 2 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_1981_2011_ha = pd.read_excel('./hydro_data/Qj_Niamey_1981-2010_real_hamatan_agrhymet_modif.xlsx', engine='openpyxl')\n",
    "\n",
    "n_1981_2011_ha['Date'] = pd.to_datetime(n_1981_2011_ha['Date'], infer_datetime_format=True)\n",
    "\n",
    "n_1981_2011_ha\n",
    "\n",
    "#n_1981_2010_ha.to_csv('./hydro_data/csv/n_1981_2010_ha.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dca1390a",
   "metadata": {},
   "source": [
    "### Bachir AGRHYMET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a6c93cee",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Ansongo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1980-01-01</td>\n",
       "      <td>1885.2</td>\n",
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       "      <th>1</th>\n",
       "      <td>1980-01-02</td>\n",
       "      <td>1885.2</td>\n",
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       "      <th>2</th>\n",
       "      <td>1980-01-03</td>\n",
       "      <td>1885.2</td>\n",
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       "      <th>3</th>\n",
       "      <td>1980-01-04</td>\n",
       "      <td>1885.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1980-01-05</td>\n",
       "      <td>1886.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <th>10599</th>\n",
       "      <td>2010-12-27</td>\n",
       "      <td>1881.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10600</th>\n",
       "      <td>2010-12-28</td>\n",
       "      <td>1881.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10601</th>\n",
       "      <td>2010-12-29</td>\n",
       "      <td>1881.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10602</th>\n",
       "      <td>2010-12-30</td>\n",
       "      <td>1887.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10603</th>\n",
       "      <td>2010-12-31</td>\n",
       "      <td>1892.96</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10604 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date  Ansongo\n",
       "0     1980-01-01   1885.2\n",
       "1     1980-01-02   1885.2\n",
       "2     1980-01-03   1885.2\n",
       "3     1980-01-04   1885.2\n",
       "4     1980-01-05  1886.93\n",
       "...          ...      ...\n",
       "10599 2010-12-27  1881.63\n",
       "10600 2010-12-28  1881.63\n",
       "10601 2010-12-29  1881.63\n",
       "10602 2010-12-30   1887.3\n",
       "10603 2010-12-31  1892.96\n",
       "\n",
       "[10604 rows x 2 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_1980_2010_ba = pd.read_excel('./hydro_data/Niamey-Ansongo_1980-2010_bachir_abn.xlsx', sheet_name='Ansongo_1980-2010', engine='openpyxl')\n",
    "\n",
    "a_1980_2010_ba = a_1980_2010_ba.rename(columns={\"Débit (m3/s)\":'Ansongo'})\n",
    "\n",
    "a_1980_2010_ba = a_1980_2010_ba.drop([0])\n",
    "a_1980_2010_ba = a_1980_2010_ba.drop(a_1980_2010_ba.index[10604:22689])\n",
    "a_1980_2010_ba = a_1980_2010_ba.reset_index().drop('index', axis=1)\n",
    "\n",
    "a_1980_2010_ba['Date'] = pd.to_datetime(a_1980_2010_ba['Date'], infer_datetime_format=True)\n",
    "\n",
    "a_1980_2010_ba\n",
    "\n",
    "#a_1980_2010_ba.to_csv('./hydro_data/csv/a_1980_2010_ba.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1c109a68",
   "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>Date</th>\n",
       "      <th>Ansongo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2000-01-01</td>\n",
       "      <td>1870.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2000-01-02</td>\n",
       "      <td>1870.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2000-01-03</td>\n",
       "      <td>1870.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2000-01-04</td>\n",
       "      <td>1870.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2000-01-05</td>\n",
       "      <td>1881.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7271</th>\n",
       "      <td>2020-08-27</td>\n",
       "      <td>892.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7272</th>\n",
       "      <td>2020-08-28</td>\n",
       "      <td>906.632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7273</th>\n",
       "      <td>2020-08-29</td>\n",
       "      <td>930.251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7274</th>\n",
       "      <td>2020-08-30</td>\n",
       "      <td>958.861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7275</th>\n",
       "      <td>2020-08-31</td>\n",
       "      <td>983.815</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7276 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date  Ansongo\n",
       "0    2000-01-01  1870.29\n",
       "1    2000-01-02  1870.29\n",
       "2    2000-01-03  1870.29\n",
       "3    2000-01-04   1870.5\n",
       "4    2000-01-05  1881.27\n",
       "...         ...      ...\n",
       "7271 2020-08-27   892.46\n",
       "7272 2020-08-28  906.632\n",
       "7273 2020-08-29  930.251\n",
       "7274 2020-08-30  958.861\n",
       "7275 2020-08-31  983.815\n",
       "\n",
       "[7276 rows x 2 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_2000_2020_ba = pd.read_excel('./hydro_data/Débits_Ansongo_2000-2020_bachir_abn.xlsx', engine='openpyxl')\n",
    "\n",
    "a_2000_2020_ba = a_2000_2020_ba.rename(columns={\"Débits à la station d'Ansongo\":'Date', \"Unnamed: 1\":'Ansongo'})\n",
    "\n",
    "a_2000_2020_ba = a_2000_2020_ba.drop([0,1])\n",
    "a_2000_2020_ba = a_2000_2020_ba.drop(a_2000_2020_ba.index[7276:7550])\n",
    "a_2000_2020_ba = a_2000_2020_ba.reset_index().drop('index', axis=1)\n",
    "\n",
    "a_2000_2020_ba['Date'] = pd.to_datetime(a_2000_2020_ba['Date'], infer_datetime_format=True)\n",
    "\n",
    "a_2000_2020_ba\n",
    "\n",
    "#a_2000_2020_ba.to_csv('./hydro_data/csv/a_2000_2020_ba.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3a26eb15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        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>Date</th>\n",
       "      <th>Kandadji</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1980-01-02</td>\n",
       "      <td>1851.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1980-01-03</td>\n",
       "      <td>1851.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1980-01-04</td>\n",
       "      <td>1841.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1980-01-05</td>\n",
       "      <td>1841.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1980-01-06</td>\n",
       "      <td>1832.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9898</th>\n",
       "      <td>2010-12-27</td>\n",
       "      <td>1841.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9899</th>\n",
       "      <td>2010-12-28</td>\n",
       "      <td>1851.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9900</th>\n",
       "      <td>2010-12-29</td>\n",
       "      <td>1851.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9901</th>\n",
       "      <td>2010-12-30</td>\n",
       "      <td>1851.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9902</th>\n",
       "      <td>2010-12-31</td>\n",
       "      <td>1860.64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9903 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date Kandadji\n",
       "0    1980-01-02  1851.28\n",
       "1    1980-01-03  1851.28\n",
       "2    1980-01-04  1841.91\n",
       "3    1980-01-05  1841.91\n",
       "4    1980-01-06  1832.55\n",
       "...         ...      ...\n",
       "9898 2010-12-27  1841.91\n",
       "9899 2010-12-28  1851.28\n",
       "9900 2010-12-29  1851.28\n",
       "9901 2010-12-30  1851.28\n",
       "9902 2010-12-31  1860.64\n",
       "\n",
       "[9903 rows x 2 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k_1980_2010_ba = pd.read_excel('./hydro_data/Débit_Kandadji_1980-2010_bachir_abn.xlsx', \n",
    "                               names=['Date', 'Kandadji'], engine='openpyxl')\n",
    "\n",
    "k_1980_2010_ba = k_1980_2010_ba.drop(k_1980_2010_ba.index[9903:11338])\n",
    "\n",
    "k_1980_2010_ba['Date'] = pd.to_datetime(k_1980_2010_ba['Date'], infer_datetime_format=True)\n",
    "\n",
    "k_1980_2010_ba\n",
    "\n",
    "#k_1980_2010_ba.to_csv('./hydro_data/csv/k_1980_2010_ba.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bc9340fd",
   "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",
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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>Date</th>\n",
       "      <th>Kandadji</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2000-01-01</td>\n",
       "      <td>1860.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2000-01-02</td>\n",
       "      <td>1841.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2000-01-03</td>\n",
       "      <td>1860.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2000-01-04</td>\n",
       "      <td>1870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2000-01-05</td>\n",
       "      <td>1860.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6610</th>\n",
       "      <td>2020-02-19</td>\n",
       "      <td>1224.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6611</th>\n",
       "      <td>2020-02-20</td>\n",
       "      <td>1192.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6612</th>\n",
       "      <td>2020-02-21</td>\n",
       "      <td>1168.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6613</th>\n",
       "      <td>2020-02-22</td>\n",
       "      <td>1145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6614</th>\n",
       "      <td>2020-02-23</td>\n",
       "      <td>1145</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6615 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date Kandadji\n",
       "0    2000-01-01  1860.64\n",
       "1    2000-01-02  1841.91\n",
       "2    2000-01-03  1860.64\n",
       "3    2000-01-04     1870\n",
       "4    2000-01-05  1860.64\n",
       "...         ...      ...\n",
       "6610 2020-02-19  1224.17\n",
       "6611 2020-02-20   1192.5\n",
       "6612 2020-02-21  1168.75\n",
       "6613 2020-02-22     1145\n",
       "6614 2020-02-23     1145\n",
       "\n",
       "[6615 rows x 2 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k_2000_2020_ba = pd.read_excel('./hydro_data/Niamey_Kandadji_2000-2020_bachir_abn.xlsx', sheet_name='Kandadji', engine='openpyxl')\n",
    "\n",
    "k_2000_2020_ba = k_2000_2020_ba.rename(columns={\"Débits (m3/s)\":'Kandadji'})\n",
    "\n",
    "k_2000_2020_ba = k_2000_2020_ba.drop([0])\n",
    "k_2000_2020_ba = k_2000_2020_ba.drop(k_2000_2020_ba.index[6615:14241])\n",
    "k_2000_2020_ba = k_2000_2020_ba.reset_index().drop('index', axis=1)\n",
    "\n",
    "k_2000_2020_ba = k_2000_2020_ba.drop(['Unnamed: 2', 'Unnamed: 3', 'Unnamed: 4', 'Unnamed: 5', 'Unnamed: 6',\n",
    "                                      'Unnamed: 7', 'Unnamed: 8', 'Unnamed: 9'], axis='columns')\n",
    "\n",
    "k_2000_2020_ba['Date'] = pd.to_datetime(k_2000_2020_ba['Date'], infer_datetime_format=True)\n",
    "\n",
    "k_2000_2020_ba\n",
    "\n",
    "#k_2000_2020_ba.to_csv('./hydro_data/csv/k_2000_2020_ba.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9eab786c",
   "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>Date</th>\n",
       "      <th>Niamey</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1980-01-01</td>\n",
       "      <td>1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1980-01-02</td>\n",
       "      <td>1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1980-01-03</td>\n",
       "      <td>1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1980-01-04</td>\n",
       "      <td>1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1980-01-05</td>\n",
       "      <td>1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11291</th>\n",
       "      <td>2010-12-27</td>\n",
       "      <td>1668.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11292</th>\n",
       "      <td>2010-12-28</td>\n",
       "      <td>1676.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11293</th>\n",
       "      <td>2010-12-29</td>\n",
       "      <td>1684.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11294</th>\n",
       "      <td>2010-12-30</td>\n",
       "      <td>1684.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11295</th>\n",
       "      <td>2010-12-31</td>\n",
       "      <td>1684.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11296 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date  Niamey\n",
       "0     1980-01-01    1945\n",
       "1     1980-01-02    1945\n",
       "2     1980-01-03    1945\n",
       "3     1980-01-04    1945\n",
       "4     1980-01-05    1945\n",
       "...          ...     ...\n",
       "11291 2010-12-27  1668.8\n",
       "11292 2010-12-28  1676.6\n",
       "11293 2010-12-29  1684.4\n",
       "11294 2010-12-30  1684.4\n",
       "11295 2010-12-31  1684.4\n",
       "\n",
       "[11296 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_1980_2010_ba = pd.read_excel('./hydro_data/Niamey-Ansongo_1980-2010_bachir_abn.xlsx', sheet_name=\"Niamey 1980-2010\", engine='openpyxl')\n",
    "\n",
    "n_1980_2010_ba = n_1980_2010_ba.rename(columns={\"Débit (m3/s)\":'Niamey'})\n",
    "\n",
    "n_1980_2010_ba = n_1980_2010_ba.drop([0])\n",
    "n_1980_2010_ba = n_1980_2010_ba.reset_index().drop('index', axis=1)\n",
    "\n",
    "n_1980_2010_ba['Date'] = pd.to_datetime(n_1980_2010_ba['Date'], infer_datetime_format=True)\n",
    "\n",
    "n_1980_2010_ba\n",
    "\n",
    "#n_1980_2010_ba.to_csv('./hydro_data/csv/n_1980_2010_ba.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "33e841ec",
   "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>Date</th>\n",
       "      <th>Niamey</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2002-02-06</td>\n",
       "      <td>1250.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2002-02-07</td>\n",
       "      <td>1232.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2002-02-08</td>\n",
       "      <td>1208.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2002-02-09</td>\n",
       "      <td>1185.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2002-02-10</td>\n",
       "      <td>1161.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6899</th>\n",
       "      <td>2020-12-27</td>\n",
       "      <td>2037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6900</th>\n",
       "      <td>2020-12-28</td>\n",
       "      <td>2046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6901</th>\n",
       "      <td>2020-12-29</td>\n",
       "      <td>2055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6902</th>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>2064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6903</th>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>2064</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6904 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date   Niamey\n",
       "0    2002-02-06  1250.27\n",
       "1    2002-02-07  1232.27\n",
       "2    2002-02-08   1208.8\n",
       "3    2002-02-09  1185.33\n",
       "4    2002-02-10  1161.87\n",
       "...         ...      ...\n",
       "6899 2020-12-27     2037\n",
       "6900 2020-12-28     2046\n",
       "6901 2020-12-29     2055\n",
       "6902 2020-12-30     2064\n",
       "6903 2020-12-31     2064\n",
       "\n",
       "[6904 rows x 2 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_2002_2020_ba = pd.read_excel('./hydro_data/Niamey_Kandadji_2000-2020_bachir_abn.xlsx', sheet_name='Niamey', engine='openpyxl')\n",
    "\n",
    "n_2002_2020_ba = n_2002_2020_ba.rename(columns={\"Débits (m3/s)\":'Niamey'})\n",
    "\n",
    "n_2002_2020_ba = n_2002_2020_ba.drop([0])\n",
    "n_2002_2020_ba = n_2002_2020_ba.drop(n_2002_2020_ba.index[6904:6931])\n",
    "n_2002_2020_ba = n_2002_2020_ba.reset_index().drop('index', axis=1)\n",
    "\n",
    "n_2002_2020_ba['Date'] = pd.to_datetime(n_2002_2020_ba['Date'], infer_datetime_format=True)\n",
    "\n",
    "n_2002_2020_ba\n",
    "\n",
    "#n_2002_2020_ba.to_csv('./hydro_data/csv/n_2002_2020_ba.csv', index=False)"
   ]
  }
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