geopandas.py

import geopandas as gpd
import numpy as np 
import pandas as pd 
import datetime as dt
import matplotlib.pyplot as plt

import plotly.express as px
import plotly.figure_factory as ff

def covid_plot(df, abs = True, Today=True, date=None):
    if df != 'deaths' and df != 'confirmed_cases':
        print('available option for df are: "deaths" or "confirmed_cases"')
    if df == 'deaths' or df == 'confirmed_cases':
        initial_data=dt.datetime(2020,1,23)

        us = pd.read_csv('covid19-data-from-john-hopkins-university/CONVENIENT_us_{}.csv'.format(df),low_memory=False).iloc[1:,1:]
        us = np.sum(us.astype(float),axis=1)
        us = us.rename('United States of America')
        
        data = dt.date.today().strftime("%d/%m/%Y")

        death = pd.read_csv('covid19-data-from-john-hopkins-university/CONVENIENT_global_{}.csv'.format(df))
        world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
        
        df_new=pd.DataFrame()
        states=['Australia','Canada','China','Denmark','France','Netherlands','United Kindom']
        
        for i in states:
            colonna = ([col for col in death.columns if i in col])
            df_new =  pd.concat([df_new,(np.sum(death[colonna].iloc[1:].astype(float),axis=1))],axis=1)
            death = death.drop(columns=colonna)
        df_new.columns = states
    
        death = death.drop(columns=['Country/Region'])
        death = pd.concat([death,df_new],axis=1)
        death = death.T 
        death = death.drop(columns=[0])

        death = death.append(us)
        state = death.index
        death.index = range(0,len(death))
        death['name']= state

        if Today==True and date==None:
            test = pd.merge(world,death.iloc[:,-2:],on=['name'],how='left')
            test.iloc[:,-1] = test.iloc[:,-1].apply(lambda x: float(x))
            
            if abs==False:
                population = test.iloc[:,0]
                population_mil=population//1000000
                test.iloc[:,-1] = test.iloc[:,-1] //population_mil

        if Today==True and date!=None:
            print('Choose only a date!')

        if Today==False:
            if date==None:
                 print('Either specifying a date or select Today = True to set date for today.')
        
        if date!=None:
            if type(date) != dt.datetime:
                print('be sure that date format is: "dt.datetime(YYYY,M,DD)"')

            if type(date) == dt.datetime:
                data = date
                index=((data-initial_data).days)
                if index < 0:
                    print('data are recorded starting from 2020,1,23; be sure to select a value after this date')
                if index >= 0:
                    data = (data.strftime("%d/%m/%Y"))
                    test = pd.merge(world,death[[index,'name']],on=['name'],how='left')
                    test.iloc[:,-1] = test.iloc[:,-1].apply(lambda x: float(x))
                
            if abs==False:
                population = test.iloc[:,0]
                population_mil=population//1000000
                test.iloc[:,-1] = test.iloc[:,-1] //population_mil


        if  df ==  'confirmed_cases':
            maxs=200000
            if abs==False:
                maxs=1000
        if  df == 'deaths':
            maxs=3500
            if abs==False:
                maxs=35

        ab = 'Absolute'
        if abs==False:
            ab= 'Relative'
            
        fig,ax=plt.subplots(figsize=(25,25))
        test.plot(column=test.iloc[:,-1],vmin=0,vmax=maxs,legend=True, 
              legend_kwds={
        'label': "number of {}".format(df),
        'orientation': "horizontal"},
              missing_kwds={
                'color':'lightgrey',
                'label':'Missing values'
              } , ax=ax
             )
        ax.set_title("{} world covid-19 {} in {}".format(ab,df,data), fontsize=25)