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.
Deze oefening maakt deel uit van de cursus
Writing Efficient Python Code
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
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(____)