Pandas to_list – Pandas: Convert a dataframe column into a list using Series.to_list() or numpy.ndarray.tolist() in python

Get a list of a specified column of a Pandas DataFrame

Pandas to_list: This article is all about how to get a list of a specified column of a Pandas DataFrame using different methods.

Lets create a dataframe which we will use in this article.

import pandas as pd 
students = [('juli', 34, 'Sydney', 155),
           ('Ravi', 31, 'Delhi', 177.5),
           ('Aaman', 16, 'Mumbai', 81),
           ('Mohit', 31, 'Delhi', 167),
           ('Veena', 12, 'Delhi', 144),
           ('Shan', 35, 'Mumbai', 135),
           ('Sradha', 35, 'Colombo', 111)
           ]

student_df = pd.DataFrame(students, columns=['Name', 'Age', 'City', 'Score'])
print(student_df)

Output:

        Name    Age   City             Score
0      Julie      34     Sydney         155.0
1     Ravi       31      Delhi            177.5
2     Aman    16     Mumbai         81.0
3     Mohit    31     Delhi             167.0
4     Veena    12     Delhi             144.0
5      Shan     35    Mumbai         135.0
6     Sradha   35   Colombo        111.0

• Pandas: Select first or last N rows in a Dataframe using head() & tail()
• Get Rows And Columns Names In Dataframe Using Python
• Pandas : Convert a DataFrame into a list of rows or columns in python | (list of lists)

Now we are going to fetch a single column

There are different ways to do that.

using Series.to_list()

Numpy ndarray to dataframe: We will use the same example we use above in this article.We select the column ‘Name’ .We will use [] that gives a series object.Series.to_list()  this function we use provided by the Series class to convert the series object and return a list.

import pandas as pd 
students = [('juli', 34, 'Sydney', 155),
           ('Ravi', 31, 'Delhi', 177.5),
           ('Aaman', 16, 'Mumbai', 81),
           ('Mohit', 31, 'Delhi', 167),
           ('Veena', 12, 'Delhi', 144),
           ('Shan', 35, 'Mumbai', 135),
           ('Sradha', 35, 'Colombo', 111)
           ]

student_df = pd.DataFrame(students, columns=['Name', 'Age', 'City', 'Score'])
list_of_names = student_df['Name'].to_list()
print('List of Names: ', list_of_names)
print('Type of listOfNames: ', type(list_of_names))

Output:

RESTART: C:/Users/HP/Desktop/article2.py
List of Names: ['juli', 'Ravi', 'Aaman', 'Mohit', 'Veena', 'Shan', 'Sradha']
Type of listOfNames: <class 'list'>

So in above example you have seen its working…let me explain in brief..

We have first select the column ‘Name’ from the dataframe using [] operator,it returns a series object names, and we have confirmed that by printing its type.

We used [] operator that gives a series object.Series.to_list()  this function we use provided by the series class to convert the series object and return a list.

This is how we converted a dataframe column into a list.

using numpy.ndarray.tolist()

From the give dataframe we will select the column “Name” using a [] operator that returns a Series object and uses

Series.Values to get a NumPy array from the series object. Next, we will use the function tolist() provided by NumPy array to convert it to a list.

import pandas as pd 
students = [('juli', 34, 'Sydney', 155),
           ('Ravi', 31, 'Delhi', 177.5),
           ('Aaman', 16, 'Mumbai', 81),
           ('Mohit', 31, 'Delhi', 167),
           ('Veena', 12, 'Delhi', 144),
           ('Shan', 35, 'Mumbai', 135),
           ('Sradha', 35, 'Colombo', 111)
           ]

student_df = pd.DataFrame(students, columns=['Name', 'Age', 'City', 'Score'])
list_of_names = student_df['Name'].values.tolist()
print('List of Names: ', list_of_names)
print('Type of listOfNames: ', type(list_of_names))

Output:

RESTART: C:/Users/HP/Desktop/article2.py
List of Names: ['juli', 'Ravi', 'Aaman', 'Mohit', 'Veena', 'Shan', 'Sradha']
Type of listOfNames: <class 'list'>
>>>

So now we are going to show you its working,

We converted the column ‘Name’ into a list in a single line.Select the column ‘Name’ from the dataframe using [] operator,

From Series.Values get a Numpy array

import pandas as pd 
students = [('juli', 34, 'Sydney', 155),
           ('Ravi', 31, 'Delhi', 177.5),
           ('Aaman', 16, 'Mumbai', 81),
           ('Mohit', 31, 'Delhi', 167),
           ('Veena', 12, 'Delhi', 144),
           ('Shan', 35, 'Mumbai', 135),
           ('Sradha', 35, 'Colombo', 111)
           ]

student_df = pd.DataFrame(students, columns=['Name', 'Age', 'City', 'Score'])
names = student_df['Name'].values
print('Numpy array: ', names)
print('Type of namesAsNumpy: ', type(names))

Output:

Numpy array: ['juli' 'Ravi' 'Aaman' 'Mohit' 'Veena' 'Shan' 'Sradha']
Type of namesAsNumpy: <class 'numpy.ndarray'>

Numpy array provides a function tolist() to convert its contents to a list.

This is how we selected our column ‘Name’ from Dataframe as a Numpy array and then turned it to a list.

Conclusion:

In this article i have shown you that how to get a list of a specified column of a Pandas DataFrame using different methods.Enjoy learning guys.Thank you!