Select a single column of data as a Series in Pandas
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 |
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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)) |
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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)) |
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Output:
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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