Remove redundant variable

plot.py

@@ -38,7 +38,6 @@ timestamp = datetime.datetime.today().strftime("%Y-%m-%d")
 
 df = pd.read_csv("corona.csv", sep=",", header=0, parse_dates=["date"]).set_index('date')
 
-df_actual_infected = df[['actual infected']].dropna()
 df_estimates       = df[['exponential estimate', 'gompertz estimate']]
 
 fig = plt.figure()
@@ -57,7 +56,7 @@ linewidth=0.5
 infected_to_severe = dead / infected * severe_cases_rate_percent / mortality_rate_percent
 infected_to_medically_relevant = dead / infected * medically_relevant_cases_percent / mortality_rate_percent
 
-ax1.plot(df_actual_infected['actual infected'], color='g', label="Nachgewiesene Infizierte -> " + data_source, marker='2', markersize=4, linestyle="None", linewidth=linewidth)
+ax1.plot(df['actual infected'], color='g', label="Nachgewiesene Infizierte -> " + data_source, marker='2', markersize=4, linestyle="None", linewidth=linewidth)
 ax1.plot(df['gompertz estimate'], color='g', label="Schätzung Infizierte -> Gompertz-Kurve\n" + str(recovery_period) + " Tage bis Genesung, Sättigung bei " + str(saturation_percentage) + "%", linewidth=linewidth)
 ax1.plot(df['gompertz estimate'] * infected_to_severe, color='b', label="Schätzung: schwere Fälle (" + str(severe_cases_rate_percent) + "%)", linestyle="dotted", linewidth=linewidth)
 ax1.plot(df['gompertz estimate'] * infected_to_medically_relevant, color='b', label="Schätzung: auf Behandlung angewiesene Fälle (" + str(medically_relevant_cases_percent) + "%)", linestyle="dashdot", linewidth=linewidth)