CLASS 12 Worksheet: Dropping Rows and Columns in DataFrames WORKSHEET 5

Worksheet: Dropping Rows and Columns in DataFrames

Section A: Multiple Choice Questions (MCQs)

1. Which method is used to drop rows or columns from a DataFrame?

   • a) delete()
   • b) remove()
   • c) drop()
   • d) pop()

2. What parameter is used with the drop() method to specify whether you are dropping rows or columns?

   • a) axis
   • b) index
   • c) level
   • d) key

3. If you want to drop a row with label 'A', what would be the correct way to do this?

   • a) df.drop(columns='A')
   • b) df.drop(index='A')
   • c) df.drop(row='A')
   • d) df.drop(axis='A')

4. What does inplace=True do when used with the drop() method?

   • a) Returns a copy of the DataFrame
   • b) Modifies the original DataFrame without returning a copy
   • c) Drops the column/row permanently from memory
   • d) Creates a new DataFrame with the dropped rows/columns

5. How can you drop multiple columns at once from a DataFrame?

   • a) df.drop(columns=['col1', 'col2'])
   • b) df.drop(index=['col1', 'col2'])
   • c) df.drop(axis=1, labels=['col1', 'col2'])
   • d) df.drop(axis=0, labels=['col1', 'col2'])

Section B: Short Answer Questions

1. Dropping a Row: Given the following DataFrame, write the code to drop the row with the label '2'.

   import pandas as pd
   data = {'A': [1, 2, 3], 'B': [4, 5, 6]}
   df = pd.DataFrame(data, index=[0, 1, 2])

2. Dropping Multiple Rows: How would you drop multiple rows with labels '1' and '2' from a DataFrame? Write a code example.

3. Dropping Columns: Write a code snippet to drop the column 'B' from the following DataFrame:

   
   import pandas as pd
   data = {'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]}
   df = pd.DataFrame(data)

4. Inplace Operation: Explain the difference between using inplace=True and inplace=False when dropping rows or columns in a DataFrame.

5. Drop with Conditions: Suppose you have a DataFrame with a column 'Age', and you want to drop all rows where the 'Age' is less than 20. Write the Python code to achieve this.

Section C: Practical Task

1. Create a DataFrame with columns 'EmployeeID', 'Name', 'Department', and 'Salary' containing at least 6 rows of data. Write the Python code to:

   • Drop the row of an employee with EmployeeID: 103.
   • Drop the 'Department' column.

2. Using the DataFrame created in Task 1, drop all employees who belong to the 'HR' department and store the result in a new DataFrame.

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