Class 6 Data Handling Worksheet – Bar Graphs, Pictographs & Data Interpretation

Master data handling for Class 6 with this worksheet - bar graphs, scaled pictographs, and real-world data interpretation. Includes practice questions to help your child organise, compare, and analyse data confidently.

What is Data Handling?

Data is a collection of information — numbers, measurements, observations — gathered to answer questions, spot patterns, and make decisions. Data Handling at Class 6 level means not just collecting and displaying data, but actively interpreting it.

We now work with bar graphs that require reading scales, pictographs with varying keys, and multi-step problems where we calculate totals, differences, and comparisons from the same data set.

Key Representations at This Level

Tally Marks: Used for quick data collection and recording during surveys.

Scaled Pictographs: Each symbol represents a fixed number of items. The key tells us the value of each symbol, and we must multiply accordingly.

Bar Graphs: Rectangular bars drawn against a scaled Y-axis. The height of each bar represents the value. Bar graphs make comparison across categories much easier than tables alone.

Solved Example

A bar graph shows vehicles passing a crossing in one hour: Cars (40), Bikes (30), Autos (20), Buses (10). The Y-axis is scaled from 0 to 50 in steps of 10.

How to Read and Analyse This

Read each bar against the Y-axis scale to find its value. Cars passed the most at 40. To find how many more cars than buses: 40 − 10 = 30. To find the total vehicles: 40 + 30 + 20 + 10 = 100. Bar graphs make these comparisons quick because the visual difference in bar height shows the gap at a glance.

Practice Problems

• A pictograph shows toys collected for donation over 4 days, where each symbol equals 5 toys. Find the day with the most collections, the total across all days, and individual day counts. → Reading Scaled Pictographs with Multi-step Questions
• Marks scored by 5 students are given as raw numbers. Arrange them in order, identify the highest scorer, and find the difference between highest and lowest. → Organising and Comparing Raw Data
• A class voted on favourite subjects. Organise into a tally chart, identify the most popular, calculate differences, and create a pictograph with a given scale. → Full Data Workflow
• A bar graph shows books in a library by category. Read values from the graph, find differences between categories, and calculate new totals after additions. → Reading and Extending Bar Graph Data
• A shopkeeper's daily cold drink sales are given for a full week. Identify the highest and lowest days, calculate combined totals for specific days, and find the weekly total. → Working with Larger Data Sets
• A fruit seller's daily sales are given. Calculate how many symbols each fruit needs for a pictograph, identify the top seller, and find differences between categories. → Designing a Pictograph from Data

Scoring Guide

• 35–40 marks: Excellent! You have mastered basic data handling. You are ready for Class 7 concepts like mean, median, and mode.
• 28–34 marks: Very Good! Practice more on creating bar graphs and interpreting pictographs with different scales.
• 20–27 marks: Good Effort! Focus on reading graph scales carefully and drawing bar graphs daily.
• 0–19 marks: Keep Trying! Review concepts carefully. Practice making tally charts and simple pictographs with everyday data.

Tips and Common Mistakes

Read the Y-axis scale before interpreting any bar graph. Misreading the scale is the single biggest source of errors at this level.

Always use a ruler when drawing bar graphs. Uneven bars make comparison unreliable and can cost marks.

Label everything — title, axes, and units. Forgetting labels is a common oversight in drawn graphs.

In pictographs, divide the total by the scale value to find how many symbols to draw. Doing this the wrong way around is a frequent mistake.

When a problem gives multiple parts, answer each one separately. Skipping a part because you think it is obvious still loses marks.

Check that bar widths are equal across a graph. Unequal widths make the graph misleading and incorrect.