In this article, we will discuss how to select a single column of data as a Series in Pandas.
For example, Suppose we have a data frame : Name Age MotherTongue Akash 21 Hindi Ashish 23 Marathi Diksha 21 Bhojpuri Radhika 20 Nepali Ayush 21 Punjabi
Now when we select column Mother Tongue as a Series we get the following output:
Hindi Marathi Bhojpuri Nepali Punjabi
Now let us try to implement this using Python:
Step1: Creating data frame:
# importing pandas as library import pandas as pd # creating data frame: df = pd.DataFrame({ 'name' : [ 'Akash' , 'Ayush' , 'Ashish' , 'Diksha' , 'Shivani' ], 'Age' : [ 21 , 25 , 23 , 22 , 18 ], 'MotherTongue' : [ 'Hindi' , 'English' , 'Marathi' , 'Bhojpuri' , 'Oriya' ]}) print ( "The original data frame" ) df |
Output:
Step 2: Selecting Column using dataframe.column name:
print ( "Selecting Single column value using dataframe.column name" ) series_one = pd.Series(df.Age) print (series_one) print ( "Type of selected one" ) print ( type (series_one)) |
Output:
Step 3: Selecting column using dataframe[column_name]
# using [] method print ( "Selecting Single column value using dataframe[column name]" ) series_one = pd.Series(df[ 'Age' ]) print (series_one) print ( "Type of selected one" ) print ( type (series_one)) |
Output:
In the above two examples we have used pd.Series() to select a single column of a data frame as a series.