story_bike_share_analyze_16.py

def logistic_growth(x, k, x0):
    return 1 / (1 + np.exp(-k*(x - x0)))
    
data['Cummulative Trips'] = data['Casual Trips'].cumsum()
data['Percentage Trips'] = data['Cummulative Trips'] / data['Casual Trips'].sum()

x = data['Mean Temp'].values
y = data['Percentage Trips'].values

popt, pcov = curve_fit(logistic_growth, x, y, maxfev=2000)
y_fit = logistic_growth(x, *popt)

kneedle = KneeLocator(x=x, y=y_fit, curve='convex', direction='increasing')
knee_start = kneedle.knee

print(knee_start)