With this DataFrame, how can I conditionally set rating to 0 when line_race is equal to zero?
line_track line_race rating foreign 25 MTH 10 84 False 26 MTH 6 88 False 27 TAM 5 87 False 28 GP 2 86 False 29 GP 7 59 False 30 LCH 0 103 True 31 LEO 0 125 True 32 YOR 0 126 True 33 ASC 0 124 True In other words, what is the proper way on a DataFrame to say if ColumnA = x then ColumnB = y else ColumnB = ColumnB
df.loc[df['line_race'] == 0, 'rating'] = 0 Use numpy.where to say if ColumnA = x then ColumnB = y else ColumnB = ColumnB:
df['rating'] = np.where(df['line_race']==0, 0, df['rating']) I have always used method given in Selected answer, today I faced a need where I need to Update column A, conditionally with derived values. the accepted answer shows "how to update column line_race to 0. Below is an example where you have to derive value to be updated with:
df.loc[df['line_race'].isna(), 'rating'] = ( (df['line_race'] - df['line_race2'])/df['line_race2'] ) Using this you can UPDATE dynamic values ONLY on Rows Matching a Condition.
