Computer Science Grade 6 20 min

Data Visualization: Creating Charts and Graphs

Students will learn to create different types of charts and graphs (e.g., bar charts, pie charts, line graphs) to visualize data.

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Introduction & Learning Objectives

Learning Objectives Identify the key parts of a chart, including the title, axes, and labels. Explain the difference between a bar chart and a pie chart and when to use each. Translate a simple data set (like a list of favorites) into the information needed for a chart. Write simple, text-based commands (pseudo-code) to generate a bar chart. Analyze a chart to answer questions about the data it represents. Identify and correct common errors in a chart, such as missing labels or an incorrect title. Have you ever voted in a poll on YouTube or a game and seen the results pop up as a colorful chart? 📊 Let's learn how computers turn votes into pictures! In this lesson, we'll explore how to turn boring lists of information, called data, into exciting charts and graphs....
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Key Concepts & Vocabulary

TermDefinitionExample Data SetA collection of related information or facts, like a list of numbers or words.A list of students' favorite pets: ['Dog', 'Cat', 'Dog', 'Fish', 'Cat', 'Dog'] Bar ChartA chart that uses rectangular bars to show how large each value is. The bars can be vertical or horizontal.A chart with a bar for 'Dogs' at a height of 3, a bar for 'Cats' at a height of 2, and a bar for 'Fish' at a height of 1. Pie ChartA circular chart divided into slices to show a part-to-whole relationship. Each slice represents a percentage of the total.A circle chart showing that 50% of students chose Dogs, 33% chose Cats, and 17% chose Fish. X-AxisThe horizontal line at the bottom of a chart that...
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Core Syntax & Patterns

Bar Chart Creation Pattern create_bar_chart(categories, values, title) This is a common pattern in coding for making a bar chart. You provide a list of category labels (like pet names), a list of their corresponding values (the counts), and a title for the whole chart. Data Counting Loop For each item in a data list, count how many times each unique item appears. Before you can make a chart, you need to analyze your raw data. This pattern involves going through your data set and counting the occurrences of each category to get the numbers you need for the Y-Axis.

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Sample Practice Questions

Challenging
A data set of favorite school subjects is: `['Math', 'Science', 'Math', 'History', 'Science', 'Math']`. Which line of pseudo-code correctly creates a bar chart for this data?
A.create_bar_chart(['Math', 'Science', 'History'], [3, 2, 1])
B.create_bar_chart(categories=['Math', 3], values=['Science', 2], title='Subjects')
C.create_bar_chart(['Math', 'Science', 'History'], [3, 2, 1], 'Favorite School Subjects')
D.create_bar_chart(['Math', 'Science', 'History', 'Art'], [3, 2, 1, 0], 'Favorite Subjects')
Challenging
You are analyzing a pie chart that shows how a student spends their allowance. The slices are labeled: 'Snacks (40%)', 'Savings (35%)', and 'Toys (20%)'. What is the most likely error in this chart's data?
A.The student spent too much on snacks.
B.The percentages do not add up to 100%.
C.pie chart cannot have a 'Savings' category.
D.There are not enough slices in the pie chart.
Challenging
You have a bar chart showing books read by two friends: Friend A (bar height of 4) and Friend B (bar height of 6). If Friend A reads 4 more books, what will happen to their bar on the chart?
A.Friend A's bar will become shorter than Friend B's bar.
B.Friend A's bar will disappear from the chart.
C.Friend A's bar will stay the same height, but its color will change.
D.Friend A's bar will become taller than Friend B's bar.

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