Processing basecase_10000_scenarios_pf5 to regional aggregated.ipynb

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   "source": [
    "import pandas as pd"
   ]
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   "cell_type": "code",
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   "metadata": {
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     "end_time": "2021-06-04T11:43:15.391505Z",
     "start_time": "2021-06-04T11:43:15.175992Z"
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   "source": [
    "experiments = pd.read_csv('Outcomes/Experiments_from_Exploration_10000scenarios_pf5.csv')\n",
    "outcomes = pd.read_csv('Outcomes/Outcomes_from_Exploration_10000scenarios_pf5.csv')"
   ]
  },
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   "source": [
    "outcomes_of_interest = outcomes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
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   "source": [
    "for n in range(1,6):\n",
    "    outcomes_of_interest[f'A.{n}_Expected Total Damage'] = 0\n",
    "    outcomes_of_interest[f'A.{n}_Total Dike Investment Costs'] = 0\n",
    "    outcomes_of_interest[f'A.{n}_Total Expected Number of Deaths'] = 0\n",
    "    \n",
    "    for i in range(3):\n",
    "        outcomes_of_interest[f'A.{n}_Expected Total Damage'] += outcomes_of_interest[f'A.{n}_Expected Annual Damage {i}']\n",
    "        outcomes_of_interest[f'A.{n}_Total Dike Investment Costs'] += outcomes_of_interest[f'A.{n}_Dike Investment Costs {i}']\n",
    "        outcomes_of_interest[f'A.{n}_Total Expected Number of Deaths'] += outcomes_of_interest[f'A.{n}_Expected Number of Deaths {i}']\n",
    "    n+=1\n",
    "\n",
    "outcomes_of_interest['RfR Total Costs'] = 0\n",
    "outcomes_of_interest['Total Expected Evacuation Costs'] = 0\n",
    "outcomes_of_interest['Other Areas Total Number of Deaths'] = 0  \n",
    "outcomes_of_interest['Other Areas Total Dike Investment Costs'] = 0\n",
    "outcomes_of_interest['Other Areas Total Damage'] = 0\n",
    "\n",
    "\n",
    "for i in range(3):\n",
    "    outcomes_of_interest['RfR Total Costs'] += outcomes_of_interest[f'RfR Total Costs {i}']\n",
    "    outcomes_of_interest['Total Expected Evacuation Costs'] += outcomes_of_interest[f'Expected Evacuation Costs {i}']\n",
    "\n",
    "for n in range(1,5):\n",
    "    outcomes_of_interest['Other Areas Total Number of Deaths'] += outcomes_of_interest[f'A.{n}_Total Expected Number of Deaths']\n",
    "    outcomes_of_interest['Other Areas Total Dike Investment Costs'] += outcomes_of_interest[f'A.{n}_Total Dike Investment Costs']\n",
    "    outcomes_of_interest['Other Areas Total Damage'] += outcomes_of_interest[f'A.{n}_Expected Total Damage']\n",
    "    \n",
    "outcomes_totals = outcomes_of_interest.iloc[:,-17::]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-04T11:46:07.435110Z",
     "start_time": "2021-06-04T11:46:06.434445Z"
    }
   },
   "outputs": [],
   "source": [
    "outcomes_of_interest.to_csv('Outcomes/Proccesed_basecase_district_aggregated_10000scenarios_pf5.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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