In this article, we’ll see how to get all values of a column in a pandas dataframe in the form of a list. This can be very useful in many situations, suppose we have to get the marks of all the students in a particular subject, get the phone numbers of all the employees, etc. Let’s see how we can achieve this with the help of some examples.
Pandas Get a List of Particular Column Values
Below are the ways by which we can get a list of particular column values:
- Using tolist()
- Using get()
- Using .loc[]
Example 1: Get a List of a Particular Column Using tolist() Method
In this example, a Pandas DataFrame is created from a dictionary, containing ‘Name’ and ‘Marks’ columns. The values of the ‘Marks’ column are extracted into a Python list using tolist()
.
# import pandas libraey import pandas as pd
# dictionary dict = { 'Name' : [ 'Martha' , 'Tim' ,
'Rob' , 'Georgia' ],
'Marks' : [ 87 , 91 ,
97 , 95 ]}
# create a dataframe object df = pd.DataFrame( dict )
# show the dataframe print (df)
# list of values of 'Marks' column marks_list = df[ 'Marks' ].tolist()
# show the list print (marks_list)
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Output:
Name Marks
0 Martha 87
1 Tim 91
2 Rob 97
3 Georgia 95
[87, 91, 97, 95]
Example: Iterate over Columns of a Pandas Dataframe
In this example, a Pandas DataFrame is created from a dictionary with ‘Name’ and ‘Marks’ columns. The code iterates through each column, and for each column, it prints the list of values obtained by applying the tolist()
method.
# import pandas library import pandas as pd
# dictionary dict = { 'Name' : [ 'Martha' , 'Tim' ,
'Rob' , 'Georgia' ],
'Marks' : [ 87 , 91 ,
97 , 95 ]}
# create a dataframe object df = pd.DataFrame( dict )
# show the dataframe print (df)
# iterating over and calling tolist() # method for each column for i in list (df):
# show the list of values
print (df[i].tolist())
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Output:
Name Marks
0 Martha 87
1 Tim 91
2 Rob 97
3 Georgia 95
['Martha', 'Tim', 'Rob', 'Georgia']
[87, 91, 97, 95]
Example 2: Pandas Get a List of a Particular Column Value Using get() Method
In this example, a Pandas DataFrame is formed from a dictionary, and the code uses the get()
method to extract the ‘Marks’ column, converting it into a Python list with the tolist()
method, followed by printing the resulting list.
# import pandas libraey import pandas as pd
# dictionary dict = { 'Name' : [ 'Martha' , 'Tim' ,
'Rob' , 'Georgia' ],
'Marks' : [ 87 , 91 ,
97 , 95 ]}
# create a dataframe object df = pd.DataFrame( dict )
# show the dataframe print (df)
# Using get() to get a list of values from the 'Marks' column marks_column = df.get( 'Marks' )
# Convert the Pandas Series to a Python list marks_list_using_get = marks_column.tolist()
# Show the list print (marks_list_using_get)
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Output
Name Marks
0 Martha 87
1 Tim 91
2 Rob 97
3 Georgia 95
[87, 91, 97, 95]
Example 3: Python Pandas Get a List of Particular Column Values Using .loc[] Method
In this example, a Pandas DataFrame is created from a dictionary with ‘Name’ and ‘Marks’ columns. The code utilizes the .loc[]
method to extract and print the list of values from the ‘Marks’ column.
# import pandas library import pandas as pd
# dictionary dict = { 'Name' : [ 'Martha' , 'Tim' ,
'Rob' , 'Georgia' ],
'Marks' : [ 87 , 91 ,
97 , 95 ]}
# create a dataframe object df = pd.DataFrame( dict )
# show the dataframe print (df)
# Using .loc[] to get a list of values from the 'Marks' column marks_list_using_loc = df.loc[:, 'Marks' ].tolist()
# Show the list print (marks_list_using_loc)
|
Output:
Name Marks
0 Martha 87
1 Tim 91
2 Rob 97
3 Georgia 95
[87, 91, 97, 95]