I have a dataframe that contains a column which is a categorical variable like so: df = pd.DataFrame({'category': ['A', 'C', 'B', 'B', 'A', 'D']}) I wish to create a columnn for each category where if it is a member of the category it has a 1 and otherwise a 0. I am currently doing this like so for each category: df['A'] = np.where(df['category']=='A', 1,0) df['B'] = np.where(df['category']=='B', 1,0) ... This works, but is there a better/more efficient way to do this? Continue reading...
