How to check if Pandas column has value from list of string?

In pandas library, we create the data in the form of rows and columns. The columns can be of string data type. The list of strings means the list containing the string elements.

Pandas is one of the libraries in python which is abbreviated as Python Data Analysis Library. It is used to perform data analysis, data cleaning, data manipulations and scientific calculations. The data in pandas library is represented in columns and rows. It has many functions and modules which are used to perform data analysis and manipulations.

Python provides different ways to check if pandas column has value from list of string type. Let’s see each way one by one.

Using dataframe() function

Firstly, let’s create the sample data frame with the columns and rows. The following is the code.

import pandas as pd
dic = {"Name":["Anil","Srivatsav","Prasad","Mitra"],
      "Class":[10,30,20,50],
      "subject":["python","Java","c","Android"]}
data = pd.DataFrame(dic)
print(data.head())

Output

Following is the data frame created with pandas –

        Name  Class  subject
0       Anil     10   python
1  Srivatsav     30     Java
2     Prasad     20        c
3      Mitra     50  Android

Using the isin() function

The isin() is a function available in pandas library which is used to check whether the elements in the DataFrame or Series are present in the given list or, tuple or, array objects. Following is the syntax for using the isin() function.

DataFrame.isin(elements)

Example

In this example, we will apply the isin() function on a desired column by passing list of strings as the input arguments.

import pandas as pd
dic = {"Name":["Anil","Srivatsav","Prasad","Mitra"],
      "Class":[10,30,20,50],
      "subject":["python","Java","c","Android"]}
data = pd.DataFrame(dic)
data.isin(["Anil","Srivatsav","Java"])
print(data.head())

Output

The output of program above is given below –

        Name  Class  subject
0       Anil     10   python
1  Srivatsav     30     Java
2     Prasad     20        c
3      Mitra     50  Android

Using numpy isin() function

The NumPy library provides the function isin() which is as similar to the isin() function of the pandas library. We can pass any python object such as list, tuple or array objects etc., and check if the contents of the given object exists in the current data set.

np.isin(DataFrame,elements)

Where,

• numpy and pandas are the libraries

• isin is the function available in numpy

• elements are the input data

• DataFrame is the 2-d labeled data

Example

In this example, we will use the isin() function of the NumPy library to check if pandas column has value from list of strings.

import pandas as pd
import numpy as np
dic = {"Name":["Anil","Srivatsav","Prasad","Mitra"],
      "Class":[10,30,20,50],
      "subject":["python","Java","c","Android"]}
data = pd.DataFrame(dic)
output = np.isin(data["Name"],["Anil","Srivatsav"])
print(output)

Output

Following is the output of the isin function of the Numpy library.

[ True  True False False]

Example

Let’s see another example to check if pandas column has value from list of strings using the isin() function of NumPy library.

import pandas as pd
import numpy as np
dic = {"Name":["Anil","Srivatsav","Prasad","Mitra"],
      "Class":[10,30,20,50],
      "subject":["python","Java","c","Android"]}
data = pd.DataFrame(dic)
output = np.isin([data["Name"],data["subject"]],["Anil","Srivatsav"])
print(output)

Output

 [[ True  True False False]
 [False False False False]]