Fill DataFrame Column depends on condition-CodePudding

I have the following DataFrame:

Fruit	Color
Apple
Orange
Pear
Peach

How can I fill the second column that depends on the 'Fruit' column value?

For instance, if the fruit is 'Apple', then the second column should be 'Red', if the fruit is Orange, then the color should be 'Orange' and so on.

I have tried to use If statment, but it doesnt work.

import pandas as pd

d = {'Fruit': ['Apple', 'Orange', 'Pear', 'Peach'], 'Color': ['','','','']}
df = pd.DataFrame(data=d)
df

CodePudding user response：

You can simply use pandas.Series.map :

dico = {'Apple': 'Red', 'Orange': 'Orange', 'Pear': 'Green', 'Peach': 'Rose'}

df['Color'] = df['Fruit'].map(dico)

# Output :

print(df)

    Fruit   Color
0   Apple     Red
1  Orange  Orange
2    Pear   Green
3   Peach    Rose

CodePudding user response：

(pd.DataFrame()
 .assign(fruit=['Apple', 'Orange', 'Pear', 'Peach'])
 .assign(color=lambda x: np.select([x.fruit == 'Apple',
                                    x.fruit == 'Orange',
                                    x.fruit == 'Pear',
                                    x.fruit == 'Peach'],
                                   ['Green',
                                    'Orange',
                                    'Dark green',
                                    'Pink'],
                                    default='blue')
        )                                                           
)

CodePudding user response：

you could use apply and a map

import pandas as pd

d = {'Fruit': ['Apple', 'Orange', 'Pear', 'Peach'], 'Color': ['','','','']}
df = pd.DataFrame(data=d)

mapa = {'Apple':'red', 'Orange':'orange', 'Pear':'green', 'Peach':'light-orange'}
df.Color = df.Fruit.apply(lambda x: mapa[x])
df