CODEWITHSUNDEEP
pythonpandasdataframe
Economist Learning Python
Economist Learning Python

Reputation: 366

Pandas: Replace value in column by using another column, if condition is true

I have the following dataframe:

df = pd.DataFrame({'ISIN': ['A1kT23', '4523', 'B333', '49O33'], 'Name': ['Example A', 'Name Xy', 'Example B', 'Test123'], 'Sector_x': ['test1', 'test2', 'test3', 'test4'],  'Sector_y': ['abc', '', '', 'xyz']})

I would like to replace value in column Sector_y by using column Sector_x, if Sector_y = ''

so that I get the following result:

df = pd.DataFrame({'ISIN': ['A1kT23', '4523', 'B333', '49O33'], 'Name': ['Example A', 'Name Xy', 'Example B', 'Test123'], 'Sector_x': ['test1', 'test2', 'test3', 'test4'],  'Sector_y': ['abc', 'test2', 'test3', 'xyz']})

I tried using the code

df['Sector_y'] = np.where('',['Sector_x'],['Sector_y'])

but didn't deliver the result I wanted.

Any suggestions how to solve the problem?

Upvotes: 0

Views: 6055

Answers (3)

jfaccioni
jfaccioni

Reputation: 7509

Another option is to use apply row-wise, and simply compare string across columns using the or operator (taking advantage from the fact that empty strings evaluate to False):

df['Sector_y'] = df.apply(lambda row: row['Sector_y'] or row['Sector_x'], axis=1)

output:

     ISIN       Name Sector_x Sector_y
0  A1kT23  Example A    test1      abc
1    4523    Name Xy    test2    test2
2    B333  Example B    test3    test3
3   49O33    Test123    test4      xyz

Upvotes: -1

BENY
BENY

Reputation: 323226

Fix np.where

df['Sector_y'] = np.where(df['Sector_y'] =='', df['Sector_x'], df['Sector_y'])

Upvotes: 1

SeaBean
SeaBean

Reputation: 23217

You can use .loc to specify the filtering condition and specify the target column Sector_y and assign with values from column Sector_x, as follows:

df.loc[df['Sector_y'] =='', 'Sector_y'] = df['Sector_x']

Result:

print(df)

     ISIN       Name Sector_x Sector_y
0  A1kT23  Example A    test1      abc
1    4523    Name Xy    test2    test2
2    B333  Example B    test3    test3
3   49O33    Test123    test4      xyz

Upvotes: 3

Related Questions