Common Chart Types & When to Use Them

Not all charts are created equal. Choosing the right chart type—or understanding why someone chose a particular one—is essential for interpreting data correctly.

The Chart Selection Guide

Chart Type	Best For	Avoid When
Bar Chart	Comparing categories	Too many categories (>10)
Line Chart	Trends over time	Non-sequential data
Pie Chart	Parts of a whole	More than 5-6 segments
Scatter Plot	Relationships between variables	Categorical data
Heatmap	Patterns in large datasets	Simple comparisons

Bar Charts: Comparing Categories

What they show: How different categories compare to each other.

Example uses:

Sales by region
Product performance comparison
Employee count by department

Reading tips:

Longer bars = higher values
Look for the biggest and smallest bars first
Check if the y-axis starts at zero (if not, differences may be exaggerated)

Red flag: A bar chart with 20+ categories is hard to read. Ask for top 10 or grouped data.

Sales by Region (Example)
━━━━━━━━━━━━━━━━━━━━━━━
North    ████████████████████ $200K
South    ████████████████ $160K
East     ██████████████ $140K
West     ████████████ $120K

Line Charts: Trends Over Time

What they show: How a value changes over a continuous period.

Example uses:

Monthly revenue trends
Website traffic over weeks
Customer churn rate by quarter

Reading tips:

Upward slope = increasing
Downward slope = decreasing
Sharp changes may indicate significant events
Multiple lines allow comparison of trends

Red flag: A line chart with non-time data (like comparing products) misrepresents the data. Categories aren't continuous.

Pie Charts: Parts of a Whole

What they show: How something is divided into proportional segments.

Example uses:

Market share distribution
Budget allocation
Traffic sources breakdown

Reading tips:

All slices should add up to 100%
Larger slices = larger proportions
Start reading from the 12 o'clock position

Red flag: Pie charts with more than 5-6 slices become hard to read. Bar charts are often better for many categories.

Do Use Pie Charts	Don't Use Pie Charts
3-5 categories	8+ categories
Showing proportions	Comparing precise values
Single point in time	Trends over time

Scatter Plots: Relationships Between Variables

What they show: Whether two variables are related and how.

Example uses:

Price vs. sales volume
Ad spend vs. conversions
Employee tenure vs. performance

Reading tips:

Points clustering in a line = correlation
Upward slope = positive relationship (as X increases, Y increases)
Downward slope = negative relationship
Random scatter = no clear relationship

Key insight: Correlation doesn't mean causation. Just because two things move together doesn't mean one causes the other.

Heatmaps: Patterns in Large Data

What they show: Intensity or frequency across two dimensions using color.

Example uses:

Website clicks by hour and day
Sales by product and region
Customer activity patterns

Reading tips:

Darker/brighter colors = higher values
Look for clusters of similar colors
Check the color scale legend

Quick Reference: Matching Questions to Charts

Question You're Asking	Best Chart Type
"How does X compare to Y?"	Bar chart
"How has X changed over time?"	Line chart
"What percentage of the total is X?"	Pie chart
"Is there a relationship between X and Y?"	Scatter plot
"Where are the patterns in this data?"	Heatmap

Common Mistakes to Watch For

Truncated Y-axis: Bar charts not starting at zero exaggerate differences
Wrong chart type: Using pie charts for time series data
Too much data: Charts with too many data points become unreadable
Missing labels: Charts without axis labels or legends are hard to interpret
3D effects: 3D charts distort perception; 2D is almost always better

Key Insight: A good chart answers a question at a glance. If you have to study it for minutes to understand it, something is wrong with the visualization—not you.

Next: Learn the anatomy of dashboards and how to navigate them like a pro. :::

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