26 Oct Delete rows/ columns in a Pandas DataFrame
The drop() method is used in Python to delete rows/ columns in a Pandas DataFrame. It is used to remove a particular row or column. Under the parameters of the drop() method, mention the column you want to delete with the axis.
We will now see two examples:
- Drop columns
- Drop rows
Drop columns using drop()
The columns are dropped using the column names. The axis is set to 1 since we want to drop a column. The columns axis can also be used for the drop() method to remove the specified column:
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axis='columns' or axis = 1 |
Let us see an example to drop columns using the drop() 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) # Drop a column using the drop() method # The marks column is deleted resDF = dataFrame.drop("marks", axis='columns') # DataFrame after dropping a 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 0 S01 Amit 1 1 S02 John 4 2 S03 Jacob 3 3 S04 David 5 4 S05 Steve 2 |
Drop rows using drop()
The rows are dropped using the index label set as a parameter of the drop() method. The rows of that particular label are removed. Set the axis to 0 since we want to drop a row. The rows axis i.e. index can also be used for the drop() method to remove the specified row:
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axis='index' Or axis = 0 |
Let us see an example of dropping a row using the drop() method. Here, the row with the 2nd index is removed:
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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) # Drop a row using the drop() method # The row with index 2 is removed resDF = dataFrame.drop(2, axis='index') # DataFrame after dropping a 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 0 S01 Amit 1 95 1 S02 John 4 70 3 S04 David 5 60 4 S05 Steve 2 90 |
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