#!/usr/bin/python import requests import csv import datetime import os import matplotlib.pyplot as pp import numpy as np import sys import importlib sys.path.append(".") #### config # countries of interest countries = ["Germany", "Italy", "Spain", "Denmark", "China", "Japan", "South Korea", "Iran", "Belgium", "World"] # enabled plots plots = ["basics", "death_per_case", "normalized_to_first_death"] ### def get_data(): """fetch data from remote, cache locally and reorganize internal data not beautiful (at all), but effective!!""" dataurl = "https://covid.ourworldindata.org/data/full_data.csv" date = datetime.date.today() datafile = f"{date}-full-data.csv" if not os.path.isfile(datafile): r = requests.get(dataurl) with open(datafile, "wb") as f: f.write(r.content) else: print(f"file found: {datafile}") # processing data = {} with open(datafile, "r") as f: reader = csv.reader(f) for row in reader: date,location,new_cases,new_deaths,total_cases,total_deaths = row if location=="location": # table header continue if location not in data: data[location] = [] year, month, day = date.split("-") def toint(a): try: return int(a) except: return np.nan data[location].append([datetime.date(int(year), int(month), int(day)), new_cases, new_deaths, total_cases, total_deaths]) # reorganize data data2 = {} for loc in data: time = [] new_cases, new_deaths, total_cases, total_deaths = [], [], [], [] for entry in data[loc]: t_, new_cases_, new_deaths_, total_cases_, total_deaths_ = entry time.append(t_) new_cases.append(toint(new_cases_)) new_deaths.append(toint(new_deaths_)) total_cases.append(toint(total_cases_)) total_deaths.append(toint(total_deaths_)) data2[loc] = [time, new_cases, new_deaths, total_cases, total_deaths] return data2 data = get_data() for plot in plots: #try: i = importlib.import_module(plot) i.plot(data, countries) #except: # print(f"plotting {plot} failed")