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Select a single column of data as a Series in Pandas
  • Last Updated : 01 Oct, 2020

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:

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# 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

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Output:



select-singly-column-pandas-1

Step 2: Selecting Column using dataframe.column name:

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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))

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Output:

single-column-pandas-dataframe-2

Step 3: Selecting column using dataframe[column_name]

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# 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))

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Output:

select-single-column-pandas-3

In the above two examples we have used pd.Series() to select a single column of a data frame as a series.

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