Data Handling using Pandas - II | Class 12 Informatics Practices Notes
By ConceptScroll Team · Published on 17 July 2026 · 2 min read
Data Handling using Pandas - II – this guide gives you a concise, exam-ready overview of Data Handling using Pandas - II from Class 12 Informatics Practices, written by ConceptScroll editors and reviewed against the latest NCERT textbook.
3.4 SORTING A DATAFRAME
Sorting is the process of arranging data elements in a specified order, either ascending or descending. Pandas provides the sort_values() function to sort DataFrame data based on one or more columns. The syntax is DataFrame.sort_values(by, axis=0, ascending=True), where 'by' specifies the column(s) to sort on, 'axis' indicates sorting direction (0 for rows, 1 for columns), and 'ascending' determines order. Sorting is useful for organizing data, such as listing students alphabetically or ranking marks. The chapter demonstrates sorting the student marks DataFrame by 'Name' to arrange students alphabetically. Sorting can also be applied to filtered data, such as marks in a particular unit test, and can be done on multiple columns to resolve ties (e.g., sorting by Science marks and then Hindi marks). Sorting helps in data analysis by enabling easy identification of top or bottom performers and organizing data for reporting.
📊 Diagram: 12149CH03
🔗 Connection: Prepares for understanding grouping data and applying group-wise operations.
Frequently asked questions
Which of the following is False about main modules?
Other main modules can import main modules
What is the primary purpose of the Pandas library in Python when working with data?
To perform efficient data manipulation and analysis on structured data
Which of the following methods in Pandas is used to remove rows or columns containing missing values represented as NaN?
dropna()
Which Pandas method replaces missing values in a DataFrame with a specified value such as zero, mean, or median?
fillna()
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