447 lines
17 KiB
Python
447 lines
17 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Project: Analyse worldwide COVID-19 Data and provide graphs etc.
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@author Patrick Müller
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"""
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import numpy as np
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import pandas as pd
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import matplotlib.pyplot as plt
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import tkinter as tk
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import random
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"""
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Fields in csv:
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dateRep
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day
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month
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year
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cases
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deaths
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countriesAndTerritories
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geoId
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countryterritoryCode
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popData2019
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"""
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from datetime import datetime, timedelta
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class Analyser:
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def __init__(self):
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# Pandas Settings
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pd.set_option('display.max_row', 50)
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pd.set_option('display.max_column', 10)
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self.df = pd.read_csv('statsfile.csv')
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self.df['dateRep'] = pd.to_datetime(self.df['dateRep'], format='%d/%m/%Y')
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# Calculate total Numbers for each country
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self.df['totalCases'] = 0
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self.df['totalDeaths'] = 0
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self.df['deathRate'] = 0
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for country in self.df['countriesAndTerritories'].unique():
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countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
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countryData = countryData.sort_values('dateRep')
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countryData['totalCases'] = countryData['cases'].cumsum()
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countryData['totalDeaths'] = countryData['deaths'].cumsum()
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countryData['deathRate'] = countryData['totalDeaths'] / countryData['totalCases'] * 100
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self.df.update(countryData)
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print('DEBUG: Analyser initialized')
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def getAvailableCountries(self):
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sorted = self.df.sort_values('countriesAndTerritories')
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return sorted['countriesAndTerritories'].unique()
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def getAvailableDates(self):
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retList = []
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for date in self.df['dateRep'].unique():
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# To only get the substring in the format YYYY-MM-DD
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retList.append(str(date)[:10])
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retList.sort()
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return retList
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def getCasesGraph(self, country, start_date='2019-12-31', end_date=datetime.now().strftime('%Y-%m-%d'),
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plotDpi=200.0, showPlot=False) -> str:
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"""
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Get a graph with the absolute number of cases by day for the entered country
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:param country: The country you wish to get the graph for
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:param start_date: The start date of the graph
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:param end_date: The end date of the graph
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:param showPlot: Whether to show the plot or only return the file path
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:return: The path for the picture of the graph
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"""
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if country in self.getAvailableCountries():
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fig = plt.figure()
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fig.dpi = plotDpi
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ax = fig.add_subplot(111)
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plt.title(('Total cases in ' + country))
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countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
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countryData = countryData.sort_values('dateRep')
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countryData['7-Day-Mean'] = countryData['totalCases'].rolling(7).mean()
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mask = (countryData['dateRep'] >= start_date) & (countryData['dateRep'] <= end_date)
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countryTimeData = countryData.loc[mask]
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countryTimeData.plot(ax=ax, x='dateRep', y='totalCases')
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countryTimeData.plot(ax=ax, x='dateRep', y='7-Day-Mean')
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if showPlot:
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plt.show(block=True)
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filePath = ('graphs/casesGraph_' + country + '_' + datetime.now().strftime('%Y-%m-%d'))
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fig.savefig(filePath)
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plt.close(fig)
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return filePath
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else:
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print('Unknown country')
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return '-1'
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def getCaseIncreaseGraph(self, country, start_date='2019-12-31', end_date=datetime.now().strftime('%Y-%m-%d'),
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plotDpi=200.0, showPlot=False) -> str:
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"""
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Get a graph with the daily increase number of cases for the entered country
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:param country: The country you wish to get the graph for
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:param start_date: The start date of the graph
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:param end_date: The end date of the graph
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:param showPlot: Whether to show the plot or only return the file path
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:return: The path for the picture of the graph
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"""
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if country in self.getAvailableCountries():
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fig = plt.figure()
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fig.dpi = plotDpi
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ax = fig.add_subplot(111)
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plt.title(('Daily new cases in ' + country))
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countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
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countryData = countryData.sort_values('dateRep')
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countryData['7-Day-Mean'] = countryData['cases'].rolling(7).mean()
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mask = (countryData['dateRep'] >= start_date) & (countryData['dateRep'] <= end_date)
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countryTimeData = countryData.loc[mask]
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countryTimeData.plot(ax=ax, x='dateRep', y='cases')
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countryTimeData.plot(ax=ax, x='dateRep', y='7-Day-Mean')
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if showPlot:
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plt.show(block=True)
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filePath = ('graphs/casesIncreaseGraph_' + country + '_' + datetime.now().strftime('%Y-%m-%d'))
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fig.savefig(filePath)
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plt.close(fig)
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return filePath
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else:
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print('Unknown country')
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return '-1'
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def getTotalCases(self, country, date=datetime.now().strftime('%Y-%m-%d')) -> int:
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"""
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Get the total cases for the entered country and date
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:param country: The country you want the case number for. Access available countries via getAvailableCountries()
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:param date: The date for which the case number is returned. Standard is the current date. Format YYYY-MM-DD
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:return: The case number
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"""
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countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
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mask = (countryData['dateRep'] <= date)
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countryTimeData = countryData.loc[mask]
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return countryTimeData['cases'].sum()
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def getDeathGraph(self, country, start_date='2019-12-31', end_date=datetime.now().strftime('%Y-%m-%d'),
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plotDpi=200.0, showPlot=False) -> str:
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"""
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Get a graph with the absolute number of cases by day for the entered country
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:param country: The country you wish to get the graph for
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:param start_date: The start date of the graph
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:param end_date: The end date of the graph
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:param showPlot: Whether to show the plot or only return the file path
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:return: The path for the picture of the graph
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"""
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if country in self.getAvailableCountries():
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fig = plt.figure()
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fig.dpi = plotDpi
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ax = fig.add_subplot(111)
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plt.title(('Total deaths in ' + country))
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countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
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countryData = countryData.sort_values('dateRep')
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countryData['7-Day-Mean'] = countryData['totalDeaths'].rolling(7).mean()
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mask = (countryData['dateRep'] >= start_date) & (countryData['dateRep'] <= end_date)
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countryTimeData = countryData.loc[mask]
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countryTimeData.plot(ax=ax, x='dateRep', y='totalDeaths')
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countryTimeData.plot(ax=ax, x='dateRep', y='7-Day-Mean')
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if showPlot:
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plt.show(block=True)
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filePath = ('graphs/deathsGraph_' + country + '_' + datetime.now().strftime('%Y-%m-%d'))
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fig.savefig(filePath)
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plt.close(fig)
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return filePath
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else:
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print('Unknown country')
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return '-1'
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def getDeathIncreaseGraph(self, country, start_date='2019-12-31', end_date=datetime.now().strftime('%Y-%m-%d'),
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plotDpi=200.0, showPlot=False) -> str:
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"""
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Get a graph with the daily increase number of cases for the entered country
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:param country: The country you wish to get the graph for
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:param start_date: The start date of the graph
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:param end_date: The end date of the graph
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:param showPlot: Whether to show the plot or only return the file path
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:return: The path for the picture of the graph
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"""
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if country in self.getAvailableCountries():
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fig = plt.figure()
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fig.dpi = plotDpi
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ax = fig.add_subplot(111)
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plt.title(('Daily new deaths in ' + country))
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countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
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countryData = countryData.sort_values('dateRep')
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countryData['7-Day-Mean'] = countryData['deaths'].rolling(7).mean()
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mask = (countryData['dateRep'] >= start_date) & (countryData['dateRep'] <= end_date)
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countryTimeData = countryData.loc[mask]
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countryTimeData.plot(ax=ax, x='dateRep', y='deaths')
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countryTimeData.plot(ax=ax, x='dateRep', y='7-Day-Mean')
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if showPlot:
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plt.show(block=True)
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filePath = ('graphs/deathsIncreaseGraph_' + country + '_' + datetime.now().strftime('%Y-%m-%d'))
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fig.savefig(filePath)
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plt.close(fig)
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return filePath
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else:
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print('Unknown country')
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return '-1'
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def getTotalDeaths(self, country, date=datetime.now().strftime('%Y-%m-%d')) -> int:
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"""
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Get the total deaths for the entered country and date
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:param country: The country you want the case number for. Access available countries via getAvailableCountries()
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:param date: The date for which the case number is returned. Standard is the current date. Format YYYY-MM-DD
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:return: The case number
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"""
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countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
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mask = (countryData['dateRep'] <= date)
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countryTimeData = countryData.loc[mask]
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return countryTimeData['deaths'].sum()
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def getDailyDeathRateGraph(self, country, start_date='2019-12-31', end_date=datetime.now().strftime('%Y-%m-%d'),
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plotDpi=200.0, showPlot=False) -> str:
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"""
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Get a graph with the daily increase number of cases for the entered country
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:param country: The country you wish to get the graph for
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:param start_date: The start date of the graph
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:param end_date: The end date of the graph
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:param showPlot: Whether to show the plot or only return the file path
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:return: The path for the picture of the graph
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"""
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if country in self.getAvailableCountries():
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fig = plt.figure()
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fig.dpi = plotDpi
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ax = fig.add_subplot(111)
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plt.title(('Daily death rate in ' + country) + ' in %')
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countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
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countryData = countryData.sort_values('dateRep')
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countryData['7-Day-Mean'] = countryData['deathRate'].rolling(7).mean()
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mask = (countryData['dateRep'] >= start_date) & (countryData['dateRep'] <= end_date)
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countryTimeData = countryData.loc[mask]
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countryTimeData.plot(ax=ax, x='dateRep', y='deathRate')
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countryTimeData.plot(ax=ax, x='dateRep', y='7-Day-Mean')
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if showPlot:
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plt.show(block=True)
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filePath = ('graphs/dailyDeathRateGraph_' + country + '_' + datetime.now().strftime('%Y-%m-%d'))
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fig.savefig(filePath)
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plt.close(fig)
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return filePath
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else:
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print('Unknown country')
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return '-1'
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def getDeathRate(self, country, date=datetime.now().strftime('%Y-%m-%d')) -> int:
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"""
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Get the death rate for the entered country and date
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:param country: The country you want the case number for. Access available countries via getAvailableCountries()
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:param date: The date for which the case number is returned. Standard is the current date. Format YYYY-MM-DD
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:return: The case number
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"""
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countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
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mask = (countryData['dateRep'] <= date)
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countryTimeData = countryData.loc[mask]
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return (countryTimeData['deaths'].sum() / countryTimeData['cases'].sum() * 100)
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def getIsItOverGraph(self, country, plotDpi=200.0, showPlot=False) -> str:
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"""
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Get a logarhytmic graph that shows easily if the exponential growth has stopped.
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:param country: The country to be compared. TODO: Change to a list of countries
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:param showPlot: If a plot is to be shown in the console
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:return: The file path for the plot
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"""
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countryString = country
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fig = plt.figure()
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fig.dpi = plotDpi
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ax = fig.add_subplot(111)
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plt.title('Is it going to end soon in ' + countryString + '?')
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ax.set_ylabel('Case Increase')
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ax.set_xlabel('Total Cases')
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for index, country in enumerate([country, 'China', 'South_Korea'], start=1):
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countryTimeData = self.df[self.df['countriesAndTerritories'].isin([country])]
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countryTimeData = countryTimeData.sort_values('dateRep')
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countryTimeData[country] = countryTimeData['cases'].rolling(7).mean()
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try:
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countryTimeData.plot(ax=ax, x='totalCases', y=country, loglog=True)
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except:
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print('Error occured')
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if showPlot:
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plt.show(block=True)
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filePath = ('graphs/isItOverGraph_' + countryString + '_' + datetime.now().strftime('%Y-%m-%d'))
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fig.savefig(filePath)
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plt.close()
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return filePath
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def getIncreasePercentageGraph(self, country, start_date='2019-12-31', end_date=datetime.now().strftime('%Y-%m-%d'),
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plotDpi=200.0, showPlot=False) -> str:
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fig = plt.figure()
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fig.dpi = plotDpi
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ax = fig.add_subplot(111)
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plt.title('Daily Percentage of Case Increase in ' + country)
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countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
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countryData = countryData.sort_values('dateRep')
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countryData['increasePercentage'] = countryData['cases'] / countryData['totalCases'] * 100
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countryData['7-Day-Mean'] = countryData['increasePercentage'].rolling(7).mean()
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mask = (countryData['dateRep'] >= start_date) & (countryData['dateRep'] <= end_date)
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countryTimeData = countryData.loc[mask]
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countryTimeData.plot(ax=ax, x='dateRep', y='increasePercentage')
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countryTimeData.plot(ax=ax, x='dateRep', y='7-Day-Mean')
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if showPlot:
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plt.show(block=True)
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filePath = ('graphs/increasePercentageGraph_' + country + '_' + datetime.now().strftime('%Y-%m-%d'))
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fig.savefig(filePath)
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plt.close()
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return filePath
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def getCasesPerMillionGraph(self, country, plotDpi=200.0, showPlot=False) -> str:
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fig = plt.figure()
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fig.dpi = plotDpi
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ax = fig.add_subplot(111)
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plt.title('Cases per Million Citizens in ' + country + ' compared to top 20')
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date = self.getAvailableDates()[len(self.getAvailableDates())-1]
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timeData = self.df
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mask = (timeData['dateRep'] == date)
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timeData = timeData.loc[mask]
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timeData = timeData.sort_values('countriesAndTerritories')
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timeData['casesPerMillion'] = ((timeData['totalCases'] / timeData['popData2019']) * 1000000)
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largestData = timeData.nlargest(20, 'casesPerMillion')
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if country not in largestData['countriesAndTerritories'].unique():
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largestData = largestData.append(timeData.loc[timeData['countriesAndTerritories'] == country])
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largestData = largestData.reset_index()
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largestData.plot.bar(ax=ax, x="countriesAndTerritories", y="casesPerMillion")
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# Highlight the selected country
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for ticks in ax.xaxis.get_major_ticks():
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if ticks.label1.get_text() == country:
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index = largestData.index[largestData['countriesAndTerritories'] == country]
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ax.patches[int(index.values[0])].set_facecolor('r')
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if showPlot:
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plt.show(block=True)
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filePath = ('graphs/casesPerMillionGraph_' + country + '_' + datetime.now().strftime('%Y-%m-%d'))
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fig.savefig(filePath)
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plt.close()
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return filePath
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def getDeathsPerMillionGraph(self, country, plotDpi=200.0, showPlot=False) -> str:
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fig = plt.figure()
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fig.dpi = plotDpi
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ax = fig.add_subplot(111)
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plt.title('Deaths per Million Citizens in ' + country + ' compared to top 20')
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date = self.getAvailableDates()[len(self.getAvailableDates())-1]
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timeData = self.df
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mask = (timeData['dateRep'] == date)
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timeData = timeData.loc[mask]
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timeData = timeData.sort_values('countriesAndTerritories')
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timeData['deathsPerMillion'] = ((timeData['totalDeaths'] / timeData['popData2019']) * 1000000)
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largestData = timeData.nlargest(20, 'deathsPerMillion')
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if country not in largestData['countriesAndTerritories'].unique():
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largestData = largestData.append(timeData.loc[timeData['countriesAndTerritories'] == country])
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largestData = largestData.reset_index()
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largestData.plot.bar(ax=ax, x="countriesAndTerritories", y="deathsPerMillion")
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# Highlight the selected country
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for ticks in ax.xaxis.get_major_ticks():
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if ticks.label1.get_text() == country:
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index = largestData.index[largestData['countriesAndTerritories'] == country]
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ax.patches[int(index.values[0])].set_facecolor('r')
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if showPlot:
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plt.show(block=True)
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filePath = ('graphs/deathsPerMillionGraph_' + country + '_' + datetime.now().strftime('%Y-%m-%d'))
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fig.savefig(filePath)
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plt.close()
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return filePath
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def getDoubleRateCompareGraph(self, country, plotDpi=200.0, showPlot=False) -> str:
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fig = plt.figure()
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fig.dpi = plotDpi
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ax = fig.add_subplot(111)
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plt.title('Double Rate Forecast vs Reality in ' + country)
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data = self.df
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mask = (data['countriesAndTerritories'] == country)
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data = data.loc[mask]
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data = data.sort_values('dateRep')
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data['doubleRateForecast'] = data['totalCases'] / data['cases']
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data['doubleRateReality'] = None
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data = data.reset_index()
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for index in data.index.values:
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indexData = data.iloc[index]
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# If there are cases in this country already
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if indexData['totalCases'] > 0:
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double = int(indexData['totalCases']) * 2
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doubleDay = data.loc[(data['totalCases'] >= double)]
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# If there is a day with double the value of cases
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if len(doubleDay['dateRep'].unique()) > 0:
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doubleDay = doubleDay.loc[(doubleDay['dateRep'] == doubleDay['dateRep'].unique()[0])]
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indexDayDatetime = datetime.strptime(str(indexData['dateRep'])[:10], '%Y-%m-%d')
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doubleDayDatetime = datetime.strptime(str(doubleDay['dateRep'].values)[2:12], '%Y-%m-%d')
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difference = (doubleDayDatetime - indexDayDatetime).days
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copyData = data.loc[(data['dateRep'] == indexData['dateRep'])]
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copyData['doubleRateReality'] = difference
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data.update(copyData)
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data.plot(ax=ax, x='dateRep', y='doubleRateForecast')
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data.plot(ax=ax, x='dateRep', y='doubleRateReality')
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if showPlot:
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plt.show(block=True)
|
|
filePath = ('graphs/doubleRateCompareGraph_' + country + '_' + datetime.now().strftime('%Y-%m-%d'))
|
|
fig.savefig(filePath)
|
|
plt.close()
|
|
|
|
return filePath |