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| indiapopulation=1380004385 | |
| fmodel=population[population.Confirmed>=50] | |
| fmodel['day_count']=list(range(1,len(fmodel)+1)) | |
| fmodel['increase'] = (fmodel.Confirmed-fmodel.Confirmed.shift(1)).fillna(0).astype(int) | |
| fmodel['increaserate']=(fmodel['increase']/fmodel["Confirmed"]) | |
| fmodel['Active']=fmodel['Confirmed']-fmodel['Deceased']-fmodel['Recovered'] | |
| xdata = np.array(list(abs(fmodel.day_count))) | |
| ydata = np.array(list(abs(fmodel.Active))) | |
| cof,cov = curve_fit(sigmoid, xdata, ydata, method='trf',bounds=([0.,0., 0.],[indiapopulation,1, 100.])) | |
| x = np.linspace(-1, fmodel.day_count.max()+20, 20) | |
| y = sigmoid(x,cof[0],cof[1],cof[2]) | |
| fig = go.Figure() | |
| fig.add_trace(go.Scatter(x=x, y=y, | |
| mode="lines+text", | |
| name='Active Cases Approx', | |
| marker_color='orange', | |
| )) | |
| fig.add_trace(go.Scatter(x=xdata, y=ydata, | |
| mode="markers", | |
| name='Active Cases', | |
| marker_color='Green', | |
| marker_line_width=2, marker_size=10 | |
| )) | |
| fig | |
| fig.update_layout( | |
| title='Daily Active Cases in India is approx '+ str(int(cof[0])) +', Active cases curve started flatten from day ' + str(int(cof[2])) +" and will flatten by day "+str(round(int(cof[2])*2.5)), | |
| template='gridon', font=dict( | |
| family="Courier New, monospace", | |
| size=10, | |
| color="blue" | |
| )) | |
| fig.show() | |
| #Total Active Case | |
| print(round(fmodel.Active.sum()+((fmodel.day_count.max()+40-fmodel.day_count.max())*y[11:20].mean()))) |
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