Bringing it all together: Predict win percentage

A pandas DataFrame (baseball_df) has been loaded into your session. For convenience, a dictionary describing each column within baseball_df has been printed into your console. You can reference these descriptions throughout the exercise.

You'd like to attempt to predict a team's win percentage for a given season by using the team's total runs scored in a season ('RS') and total runs allowed in a season ('RA') with the following function:

def predict_win_perc(RS, RA):
    prediction = RS ** 2 / (RS ** 2 + RA ** 2)
    return np.round(prediction, 2)

Let's compare the approaches you've learned to calculate a predicted win percentage for each season (or row) in your DataFrame.

Bu egzersiz

Writing Efficient Python Code

kursunun bir parçasıdır

Kursu Görüntüle

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

win_perc_preds_loop = []

# Use a loop and .itertuples() to collect each row's predicted win percentage
for ____ in baseball_df.____():
    runs_scored = ____.____
    runs_allowed = ____.____
    win_perc_pred = predict_win_perc(____, ____)
    win_perc_preds_loop.append(____)

Kodu Düzenle ve Çalıştır