Get the index numbers of mismatching column values between to dataframes-CodePudding

I have two similar dataframes like this

Dataframe 1:

ID        classification
1         MISS
2         MISS
3         CORRECT
4         MISS
5         CORRECT

Dataframe 2:

ID        classification
1         CORRECT
2         CORRECT
3         MISS
4         MISS
5         CORRECT

I would like get the index numbers for each time there is a mismatch between values in the classification column between dataset 1 and dataset 2. The datasets are of similar length and the remaining columns are also equal to each other.

CodePudding user response：

Because same number of rows and same indices you can compare classification between both DataFrames for not equal by Series.ne and filter values in boolean indexing:

#ID is index
df1.index[df1['classification'].ne(df2['classification'])]

Or if ID in column:

df1.loc[df1['classification'].ne(df2['classification']), 'ID']

If not same number of rows use Series.map, here ID is column:

s = df2.set_index('ID')['classification']
df1.loc[df1['classification'].ne(df1['ID'].map(s)), 'ID']