Comparing column values of Python Pandas Dataframe

You can use list comprehension with compare all values without actual, which is removed by drop:

df1 = pd.concat([df.drop(i) == x for i, x in enumerate(df.values)], keys=df.index) print (df1) A B 0 1 False False 2 True False 3 True True 4 False False 1 0 False False 2 False True 3 False False 4 True True 2 0 True False 1 False True 3 True False 4 False True 3 0 True True 1 False False 2 True False 4 False False 4 0 False False 1 True True 2 False True 3 False False 

Detail:

In list comprehesnion create list of DataFrames:

print ([df.drop(i) == x for i, x in enumerate(df.values)]) [ A B 1 False False 2 True False 3 True True 4 False False, A B 0 False False 2 False True 3 False False 4 True True, A B 0 True False 1 False True 3 True False 4 False True, A B 0 True True 1 False False 2 True False 4 False False, A B 0 False False 1 True True 2 False True 3 False False] 

which are joined together by concat and parameter keys for MultiIndex if necessary, then is possible select each small DataFrame by loc:

print (df1.loc[0]) A B 1 False False 2 True False 3 True True 4 False False 

df_final = pd.DataFrame() # Iterate all columns for column in df.columns.tolist(): # For the iterated column, iterate the line for line in range(len(df[column])): info = "column: " + str(column) + " - line: " + str(line) # Check if the cells below are equals to the iterated cell answer = df.loc[df.index > line,column] == df.loc[df.index == line,column].values[0] # Display the result print(info) print(answer) # Add the result in a dataframe for line in range(len(answer)): df_final = df_final.append([[ info, answer.index[line], answer.values[line] ]]) # Display the resulting dataframe df_final.columns = ["position", "index", "check"] print(df_final)