{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import json\n", "\n", "with open(\"predictions.json\") as f:\n", " api = json.loads(f.read())\n", "\n", "api['TT'] = {}\n", "for state in api:\n", " if state == 'TT':\n", " continue\n", " for date in api[state]:\n", " api['TT'][date] = api['TT'].get(date, {'delta':{}, 'total':{}})\n", " for k in ['delta', 'total']:\n", " api['TT'][date][k]['confirmed'] = api['TT'][date][k].get('confirmed', 0) + api[state][date][k]['confirmed']\n", " api['TT'][date][k]['deceased'] = api['TT'][date][k].get('deceased', 0) + api[state][date][k]['deceased']\n", " api['TT'][date][k]['recovered'] = api['TT'][date][k].get('recovered', 0) + api[state][date][k]['recovered']\n", " api['TT'][date][k]['active'] = api['TT'][date][k].get('active', 0) + api[state][date][k]['active']\n", "\n", "with open(\"predictions_tt.json\", \"w\") as f:\n", " f.write(json.dumps(api, sort_keys=True))" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 4 }