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!
CodePudding user response：
You can simply use 
CodePudding user response：
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')
CodePudding user response：
Use isin:
df_eq['Column1'].isin(df_eq['Column2']).replace({True:'Yes', False:'No'})
CodePudding user response：
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)