Create pandas dataframe with multiple dataframes

Question

I\'ve a csv file like this:

Fruit_Type;Fruit_Color;Fruit_Description
Apple;Green,Red,Yellow;Just an apple
Banana;Green,Yellow;Just a Banana
Orange;Red,Yellow;Jus         


        

Answer 1

I suggest use str.get_dummies:

df = df.join(df.pop('Fruit_Color').str.get_dummies(','))
print (df)
  Fruit_Type Fruit_Description  Green  Red  Yellow
0      Apple     Just an apple      1    1       1
1     Banana     Just a Banana      1    0       1
2     Orange    Just an Orange      0    1       1
3      Grape      Just a Grape      0    0       0

Answer 2

You can create the columns using assign:

df.assign(
   green=lambda d: d['Fruit_color'].str.contains('Green', case=True),
   red=lambda d: d['Fruit_color'].str.contains('Red', case=True),
   yellow=lambda d: d['Fruit_color'].str.contains('Yellow', case=True),
)

This results in a new dataframe with three additional columns of Booleans, namely "green", "red" and "yellow".

To detect a row with no known colour, you can also assign other_color=lambda d: ~(d['green'] | d['red'] | d['yellow']).

Another possibility is to use pandas.concat to concatenate multiple dataframes, but it's less elegant than the above solution.