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Exercise

Replacing .iloc with underlying arrays

Now that you have a better grasp on a DataFrame's internals let's update one of your previous analyses to leverage a DataFrame's underlying arrays. You'll revisit the win percentage calculations you performed row by row with the .iloc method:

def calc_win_perc(wins, games_played):
    win_perc = wins / games_played
    return np.round(win_perc,2)

win_percs_list = []

for i in range(len(baseball_df)):
    row = baseball_df.iloc[i]

    wins = row['W']
    games_played = row['G']

    win_perc = calc_win_perc(wins, games_played)

    win_percs_list.append(win_perc)

baseball_df['WP'] = win_percs_list

Let's update this analysis to use arrays instead of the .iloc method. A DataFrame (baseball_df) has been loaded into your session.

Instructions 1/3

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  • Use the right method to collect the underlying 'W' and 'G' arrays of baseball_df and pass them directly into the calc_win_perc() function. Store the result as a variable called win_percs_np.