Pandas
Handle structured data efficiently using Pandas for data cleaning, transformation, analysis, and visualization.
Apply Simple Function
Create a new column with score percentages (score/100).
Basic Pivot Table
Create a pivot table showing total revenue by product and month.
Calculate Mean Score
Calculate and print the average score of all students.
Calculate Total Inventory Value
Calculate total value (price * stock) for each product.
Count Non-Null Values
Count non-null values in each column of the products DataFrame.
Filter with Multiple Conditions
Show students who are 18 years old AND have grade 'A'.
Get DataFrame Shape
Print the shape (rows, columns) of the students DataFrame.
Select Cell by Row/Column
Select the salary of employee at index 1 (second row).
Select Columns by Position
Select first 2 columns of the employees DataFrame.
Select Multiple Columns
Select and display just the 'name' and 'grade' columns.
Select Row by Index
Select and display the row at index 2 from the employees DataFrame.
Select Single Column
Select and display just the 'name' column from the students DataFrame.
Select Specific Rows and Columns
Select name and price for first 2 products.
Show Data Types
Display the data types of each column in the products DataFrame.