def mortality()

in api/streamlit_experiments/covid.py [0:0]

• 25 lines of code
• 2 McCabe index (conditional complexity)

def mortality(df):
    df["Mortality Rate"]=(df["Deaths"]/df["Confirmed"])*100
    df["Recovery Rate"]=(df["Recovered"]/df["Confirmed"])*100
    df["Active Cases"]=df["Confirmed"]-df["Recovered"]-df["Deaths"]
    df["Closed Cases"]=df["Recovered"]+df["Deaths"]

    st.write("Average Mortality Rate = ",f'{df["Mortality Rate"].mean():.2f}')
    st.write("Median Mortality Rate = ",f'{df["Mortality Rate"].median():.2f}')
    st.write("Average Recovery Rate = ",f'{df["Recovery Rate"].mean():.2f}')
    st.write("Median Recovery Rate = ",f'{df["Recovery Rate"].median():.2f}')

    #Plotting Mortality and Recovery Rate 
    fig = make_subplots(rows=2, cols=1,
                    subplot_titles=("Recovery Rate", "Mortatlity Rate"))
    fig.add_trace(
        go.Scatter(x=df.index, y=(df["Recovered"]/df["Confirmed"])*100,name="Recovery Rate"),
        row=1, col=1
    )
    fig.add_trace(
        go.Scatter(x=df.index, y=(df["Deaths"]/df["Confirmed"])*100,name="Mortality Rate"),
        row=2, col=1
    )
    fig.update_layout(height=1000,legend=dict(x=0,y=0.5,traceorder="normal"))
    fig.update_xaxes(title_text="Date", row=1, col=1)
    fig.update_yaxes(title_text="Recovery Rate", row=1, col=1)
    fig.update_xaxes(title_text="Date", row=1, col=2)
    fig.update_yaxes(title_text="Mortality Rate", row=1, col=2)

    st.write(fig)