{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c9db7d7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib as plt\n",
    "import datetime as dt\n",
    "import os\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a5d5a7f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# All directories\n",
    "root       = \"C:/Users/freiste/OneDrive - Ilmatieteen laitos/Documents/IIASA YSSP 2023\"\n",
    "this_dir   =  os.getcwd()\n",
    "\n",
    "input_dir   = f\"{root}/03 - Research and ForgetMeNots\"\n",
    "output_dir = f\"{root}/02 - Data/AUT\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e931169f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add more historical data from Dokumentation der Waldschädigungsfaktoren\n",
    "\n",
    "file = 'Research_BWF_DokumentationDerWaldschädigungsfaktoren.xlsx'\n",
    "\n",
    "DWF = pd.read_excel(f\"{input_dir}/{file}\", header=0, sheet_name='DWF_HistoricalData', usecols='A:I', nrows=15)\n",
    "DWF = DWF.melt(id_vars='year').rename(columns={'variable':'district', 'value':'beetle_damage (Efm)'})\n",
    "DWF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9788e016",
   "metadata": {},
   "outputs": [],
   "source": [
    "DWF.to_csv(f\"{output_dir}/Data_BWF_DocumentationOfForestdamagefactors\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "941ff974",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8e5b672b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10db0a7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Opional: Combine with Annual Logging reports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ea5354fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Missing: load logging reports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e2478264",
   "metadata": {},
   "outputs": [],
   "source": [
    "def map_data_to_districts(col_nr, new_col_name):\n",
    "    map_dict          = lookup_table[[lookup_table.columns[0], lookup_table.columns[col_nr]]].set_index(lookup_table.columns[0]).to_dict()\n",
    "    \n",
    "    HEM[new_col_name] = HEM['district'].map(map_dict[list(map_dict.keys())[0]])\n",
    "\n",
    "col_nrs       = [1,2,3,4]\n",
    "new_col_names = ['state','totarea(km2)','pop(2023)','popdens(ppl/km2)']\n",
    "\n",
    "for c, col_nr in enumerate(col_nrs):\n",
    "    new_col_name = new_col_names[c]\n",
    "    map_data_to_districts(col_nr, new_col_name)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "031d1c34",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reorder columns\n",
    "HEM_order1 = ['year', 'state', 'district',\n",
    "               'totarea(km2)', 'pop(2023)', 'popdens(ppl/km2)',\n",
    "              'beetle_damage (Efm)', 'storm_damage (Efm)']\n",
    "HEM = HEM[HEM_order1]\n",
    "HEM = HEM.sort_values(['state', 'district', 'year'], ascending=(True, True, True)).reset_index(drop=True)"
   ]
  }
 ],
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