Add an additional column to a panda dataframe comparing two columns

Question:

I have a dataframe (df) containing two columns:

Column 1 Column 2
Apple Banana
Chicken Chicken
Dragonfruit Egg
Fish Fish

What I want to do is create a third column that says whether the results in each column are the same. For instance:

Column 1 Column 2 Same
Apple Banana No
Chicken Chicken Yes
Dragonfruit Egg No
Fish Fish Yes

I’ve tried:
df['Same'] = df.apply(lambda row: row['Column A'] in row['Column B'],axis=1)

Which didn’t work.
I also tried to create a for loop but couldn’t even get close to it working.

Any help you can provide would be much appreciated!

Asked By: user19828448

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Source

Answers:

You can simply use np.where :

import numpy as np

df['Same'] = np.where(df['Column 1'] == df['Column 2'], 'Yes', 'No')

>>> print(df)

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Answered By: L'Artiste

In Pandas the == operator between Series returns a new Series

So you can use:

df['Same'] = df['Column A'] == df['Column B']
df['Same'] = df['Same'].replace(True, 'Yes').replace(False, 'No')
Answered By: tiger

Use isin:

df_eq['Column1'].isin(df_eq['Column2']).replace({True:'Yes', False:'No'})
Answered By: SomeDude

You could use the .apply(lambda) expression

df['Same'] = df.apply(lambda x: 'Yes' if x['Column 1']==x['Column 2'] else 'No', axis=1)
Answered By: Gold79