DataFrame.ne(other, axis=’columns’, level=None)

# importing pandas as pd
import pandas as pd
 
# Creating the first dataframe
df1=pd.DataFrame({"A":[14,4,5,4,1],
                  "B":[5,2,54,3,2],
                  "C":[20,20,7,3,8],
                  "D":[14,3,6,2,6]})
 
# Print the dataframe
df1

# importing pandas as pd
import pandas as pd
 
# create series
sr = pd.Series([3, 2, 4, 5, 6])
 
# Print series
sr

# evaluate inequality over the index axis
df.ne(sr, axis = 0)

# importing pandas as pd
import pandas as pd
 
# Creating the first dataframe
df1=pd.DataFrame({"A":[14,4,5,4,1],
                  "B":[5,2,54,3,2],
                  "C":[20,20,7,3,8],
                  "D":[14,3,6,2,6]})
 
# Creating the second dataframe with <code>Na</code> value
df2=pd.DataFrame({"A":[12,4,5,None,1],
                  "B":[7,2,54,3,None],
                  "C":[20,16,11,3,8],
                  "D":[14,3,None,2,6]})
 
# Print the second dataframe
df2

# passing df2 to check for inequality with the df1 dataframe.
d1f.ne(df2)