The poor rabbit chased by Python and Anaconda :p

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Australia covid 19 Track

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Symbols count in article: 1.7k Reading time ≈ 2 mins. 
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import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import matplotlib.ticker as ticker
import calendar
%matplotlib inline

create a past data base

daily diagnosis table

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def create_daily_case(readfromfile = False):
    '''
    create a data table from previous day file, or from oldest file
    '''
    if readfromfile == True:
        with open('newest_daily.csv') as f:
            olddailydf = pd.read_csv(f,header = 0)
    else:
        with open('ausvirus.csv') as f:
            datadf = pd.read_csv(f,header = 0)
            newdf = datadf.transpose().iloc[0:24,]
            drange = pd.date_range('20200301','20200324',freq='D')
            newdf.index = drange[::-1]
            columnlist = ['NSW','VIC','QLD','WA','SA','TAS','ACT','NT']
            newdf.columns = columnlist
            newdf = newdf.fillna(0).astype(int)
            newdf = newdf.iloc[1:,][::-1]
            newdf['AUS'] = newdf.sum(axis=1).values
            optdf = newdf
    return optdf
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newdf = create_daily_case(readfromfile = False)
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def plot_daily_new_cases(newdf):
    '''
    plot australia daily new coronavirus cases
    '''
    plotdf = newdf.reset_index().melt(id_vars = 'index')
    sns.set(style='darkgrid', palette='deep', font='sans-serif', font_scale=2,
            color_codes=True, rc={"lines.linewidth": 6,'lines.markersize': 14})
    fig,ax = plt.subplots(figsize=(24,10))
    ax = sns.lineplot(x='index',y='value',hue='variable',data=plotdf, marker='o', dashes=True)
    ax.set(title="Australia Daily New Covid-19 Cases")
    ax.xaxis.set_major_locator(ticker.MultipleLocator(1))
    ax.set_xlabel("Date",fontsize=30)
    ax.set_ylabel("Number of Cases",fontsize=40)
    ax.xaxis.set_tick_params(labelsize = 16,rotation=15)

    item = plotdf.groupby('variable')
    palette = sns.color_palette('deep').as_hex()

    for i in range(newdf.shape[1]):
        curdf = newdf.iloc[:,i].to_frame().reset_index().values
        for x,y in curdf:
            ax.text(x,y,f'{y:d}',color=palette[i])


plot_daily_new_cases(newdf)

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