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.
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.
# Use the W array and G array to calculate win percentages
win_percs_np = calc_win_perc(baseball_df[____].____, baseball_df[____].____)