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Exercise

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.

Instructions 1/4
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  • Use a for loop and .itertuples() to predict the win percentage for each row of baseball_df with the predict_win_perc() function. Save each row's predicted win percentage as win_perc_pred and append each to the win_perc_preds_loop list.
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