Pandas DataFrame.isin()

by Online Tutorials Library July 14, 2022

Pandas DataFrame.isin()

The main task of the DataFrame.isin() method is to select the rows having a particular (or multiple) values in a particular column.

Syntax

Parameter

values : It can be DataFrame, Series, Iterable, or dict and returns a boolean value.

It returns a true value if all the labels match. If it consists of a Series, then it will be the index.

If it consists of a dict, then the keys must be the column names and must be matched.

If it consists of a DataFrame, then both the index and column labels must be matched.

Example1:

  import pandas as pd  #initializing dataframe  info = pd.DataFrame({‘x’: [1, 2], ‘y’: [3, 7]})  #check if the values of info are in the range(1,6)  p = info.isin(range(1,8))  print(‘DataFramen———–n’,info)  print(‘nDataFrame.isin(range(1,6))n———–n’,p)  

Output:

DataFrame  -----------  xy  0  1  3  1  2  7    DataFrame.isin(range(1,6))  -----------  xy  0  TrueTrue  1  TrueTrue

Example2:

  import pandas as pd   data = pd.DataFrame({      ‘EmpCode’: [‘Emp001’, ‘Emp002’, ‘Emp003’, ‘Emp004’, ‘Emp005’],      ‘Name’: [‘Parker’, ‘Smith’, ‘Jones’, ‘Terry’, ‘Palin’],      ‘Occupation’: [‘Tester’, ‘Developer’, ‘Statistician’,                     ‘Tester’, ‘Developer’],      ‘Date Of Join’: [‘2019-01-17’, ‘2019-01-26’, ‘2019-01-29’, ‘2019-02-02’,                       ‘2019-02-11’],      ‘Age’: [29, 22, 25, 38, 27]})    print(“nUseisin operatorn”)  print(data.loc[data[‘Occupation’].isin([‘Tester’,’Developer’])])  print(“nMultiple Conditionsn”)  print(data.loc[(data[‘Occupation’] == ‘Tester’) |                      (data[‘Name’] == ‘John’) &                      (data[‘Age’] < 27)])  

Output:

Use isin operator    EmpCodeNameOccupation                Date Of Join       Age  0  Emp001      Parker     Tester            2019-01-17     29  1  Emp002      Smith    Developer       2019-01-26     22  3  Emp004     Terry       Tester            2019-02-02   38  4  Emp005     Palin    Developer         2019-02-11   27    Multiple Conditions    EmpCode         Name      Occupation      Date Of Join    Age  0  Emp001      Parker     Tester           2019-01-17     29  3  Emp004      Terry       Tester           2019-02-02     38

Next TopicDataFrame.loc[]

Pandas DataFrame.isin()

Pandas DataFrame.isin()

Syntax

Parameter

Example1:

Example2:

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