Sometimes we have two or more series and we have to find all those elements that are present in one series but not in other. We can do this easily, using the Bitwise NOT operator along with the pandas.isin() function.
Example 1: Taking two Integer Series
Python3
# Importing pandas library import pandas as pd # Creating 2 pandas Series ps1 = pd.Series([2, 4, 8, 20, 10, 47, 99]) ps2 = pd.Series([1, 3, 6, 4, 10, 99, 50]) print("Series1:") print(ps1) print("\nSeries2:") print(ps2) # Using Bitwise NOT operator along # with pandas.isin() print("\nItems of ps1 not present in ps2:") res = ps1[~ps1.isin(ps2)] print(res) |
Output:
In the above example, we take 2 pandas series of int type ‘ps1‘ and ‘ps2‘ and find all those elements of ps1 that are not present in ps2.
Example 2: Taking two Floating point Series
Python3
# Importing pandas library import pandas as pd # Creating 2 pandas Series ps1 = pd.Series([2.8, 4.5, 8.0, 2.2, 10.1, 4.7, 9.9]) ps2 = pd.Series([1.4, 2.8, 4.7, 4.8, 10.1, 9.9, 50.12]) print("Series1:") print(ps1) print("\nSeries2:") print(ps2) # Using Bitwise NOT operator along # with pandas.isin() print("\nItems of ps1 not present in ps2:") res = ps1[~ps1.isin(ps2)] print(res) |
Output:
In the above example, we take 2 pandas series of float type ‘ps1‘ and ‘ps2‘ and find all those elements of ps1 that are not present in ps2.
Example 3: Taking two String Series
Python3
# Importing pandas library import pandas as pd # Creating 2 pandas Series ps1 = pd.Series(['Monu', 'Sonu', 'Tonu', 'Nonu', 'Ronu', 'Bonu']) ps2 = pd.Series(['Sweetu', 'Tweetu', 'Nonu', 'Micku', 'Bonu', 'Kicku']) print("Series1:") print(ps1) print("\nSeries2:") print(ps2) # Using Bitwise NOT operator along with # pandas.isin() print("\nItems of ps1 not present in ps2:") res = ps1[~ps1.isin(ps2)] print(res) |
Output:
In the above example, we take 2 pandas series of string type ‘ps1‘ and ‘ps2‘ and find all those elements of ps1 that are not present in ps2.
