Data Handling using Pandas - II | Class 12 Informatics Practices Notes

3.2 DESCRIPTIVE STATISTICS

Descriptive statistics provide quantitative summaries of data, helping to understand its main characteristics. In Pandas, several statistical functions can be applied to DataFrames to obtain insights such as maximum, minimum, count, sum, mean, median, mode, quartiles, variance, and standard deviation. These functions can be applied column-wise or row-wise, depending on the axis parameter. For example, df.max() returns the maximum value in each column by default (axis=0), while df.max(axis=1) returns the maximum value in each row. The chapter uses the student marks DataFrame to demonstrate these functions. Calculating maximum and minimum values helps identify top and bottom scores. Summation and mean provide total and average marks respectively. Median gives the middle value, useful when data is skewed. Mode identifies the most frequently occurring value. Quartiles divide data into four equal parts, assisting in understanding data distribution. Variance and standard deviation measure data spread around the mean. Pandas also offers the describe() function that summarizes many descriptive statistics in one call, including count, mean, std, min, quartiles, and max. These statistical tools are fundamental for analyzing and interpreting datasets effectively.

📊 Diagram: 12149CH03

🧪 Activity: Activity 3.1: Write Python statements to print the sum of English marks scored by Mishti; Activity 3.2: Find the median of the values of the rows of the DataFrame; Activity 3.3: Calculate the mode of marks scored in Maths; Activity 3.4: Find the variance and standard deviation of given exam scores.

🔗 Connection: Prepares for understanding data aggregation and grouping techniques in the next sections.