Knowing the index of a data frame

[Ivannovix]

Good morning, this is my first message in the forum so Hi .
I have a doubt and I don't know how to proceed, I'm trying to compare two columns in two different data frames.

import pandas as pd
import numpy as np
from sklearn import linear_model
from sklearn import model_selection
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.metrics import accuracy_score
import matplotlib.pyplot as plt
import seaborn as sb


df = pd.read_csv(r"Prueba1CSV.csv", sep=";")
df1= pd.read_csv(r"Prueba2CSV.csv", sep=";")


    def is_in_column(data, values):
        if data in values:
            return True
        else:
            return False
        

df['Present_in_other'] = df[Cabeza].apply(is_in_column, values=df1[Cabeza2].tolist())
df3=df[df['Present_in_other']==False]

The problem is that now what I'm returning in "is_in_column" is True and what I want to return is the index in which it founds the coincidence.

Maybe it's very easy but I don't know how to do it.

Thanks,
Iván

[klllmmm]

Once you read the source data CSV files you can create indexes, so you can see the index in resultant tables.

df = df.rename_axis('df_index').reset_index()
df1 = df1.rename_axis('df2_index').reset_index()