{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# Preparing climate file for CIM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "  Script prepared by Dr. Dasaraden Mauree                 \n",
    "  Contact: EPFL                                           \n",
    "  dasaraden.mauree@epfl.ch / dasaraden.mauree@gmail.com \n",
    "                                                         \n",
    "   use this script to read the standard climate file from\n",
    "   Meteonorm for CitySim and save new file for CIM. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#importing necessary packages\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Opening file and saving in array\n",
    "meteonorm=pd.read_csv(\"Ecublens.cli\", header=\"infer\", sep=\"\\s+\", encoding = \"ISO-8859-1\", skiprows=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Selecting columns and saving in file for CIM\n",
    "cim=meteonorm[['Ta','FF','DD','RH']]\n",
    "cim.to_csv(r'for_cim.cli', header=None, sep=' ', mode='a', index=False)"
   ]
  }
 ],
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