26 Oct Add a new column to Pandas DataFrame
In this lesson, we will learn how to add a new column to Pandas DataFrame in Python. We will insert a column to an already created DataFrame. Let us see various ways to achieve this:
- Add a new column using the insert() method
- Assign a new column using the assign() method
Add a new column using insert()
To insert a new column into a DataFrame, use the insert() method. We can set the location, name, and the values as a parameter:
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dataFrame.insert(2, "roll", [101, 102, 103, 104, 105]) |
The 1st parameter of the insert() is the location you want the new column. The 2nd is the name of the new column and 3rd are the values of the new column.
Let us see an example of adding a new column to a Pandas DataFrame using the insert() method:
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import pandas as pd # Dataset data = { 'id': ["S01", "S02", "S03", "S04", "S05"], 'student': ["Amit", "John", "Jacob", "David", "Steve"], 'rank': [1, 4, 3, 5, 2], 'marks': [95, 70, 80, 60, 90] } dataFrame = pd.DataFrame(data) print("Student Records\n\n",dataFrame) # Insert a new column using the insert() method # The location set is 2 i.e. 2nd index i.e. 3rd position dataFrame.insert(2, "roll", [101, 102, 103, 104, 105]) # DataFrame after adding a new column print("\nUpdated DataFrame:\n",dataFrame) |
Output
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Student Records id student rank marks 0 S01 Amit 1 95 1 S02 John 4 70 2 S03 Jacob 3 80 3 S04 David 5 60 4 S05 Steve 2 90 Updated DataFrame: id student roll rank marks 0 S01 Amit 101 1 95 1 S02 John 102 4 70 2 S03 Jacob 103 3 80 3 S04 David 104 5 60 4 S05 Steve 105 2 90 |
Assign a new column using assign()
To assign new columns to an already created Pandas DataFrame, use the assign() method. It adds a new column to the end. Set the new column with the column name as a parameter of the assign() method:
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resDF = dataFrame.assign(roll = [101, 102, 103, 104, 105]) |
Let us see an example of adding a new column to a Pandas Dataframe using the assign() method:
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import pandas as pd # Dataset data = { 'id': ["S01", "S02", "S03", "S04", "S05"], 'student': ["Amit", "John", "Jacob", "David", "Steve"], 'rank': [1, 4, 3, 5, 2], 'marks': [95, 70, 80, 60, 90] } dataFrame = pd.DataFrame(data) print("Student Records\n\n",dataFrame) # Insert a new column using the assign() method # It automatically gets inserted at the end resDF = dataFrame.assign(roll = [101, 102, 103, 104, 105]) # DataFrame after adding a new column print("\nUpdated DataFrame:\n",resDF) |
Output
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Student Records id student rank marks 0 S01 Amit 1 95 1 S02 John 4 70 2 S03 Jacob 3 80 3 S04 David 5 60 4 S05 Steve 2 90 Updated DataFrame: id student rank marks roll 0 S01 Amit 1 95 101 1 S02 John 4 70 102 2 S03 Jacob 3 80 103 3 S04 David 5 60 104 4 S05 Steve 2 90 105 |
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