Bar Chart
Compares values across different categories. Excellent for showing magnitude and ranking.
Sales by regionSurvey responses
PlotPerfect
Match your data story to its perfect visual.
Interactive chart selection tool for data analysts, business intelligence developers, and anyone working with data visualization. Choose from over 15 chart types with detailed guidance.
How to Choose the Right Chart
Define Your Purpose
Are you comparing values, showing trends over time, or displaying relationships between variables?
Know Your Audience
Consider who will view your chart and their level of data literacy when choosing complexity.
Match Data Type
Different data types (categorical, numerical, time-series) work better with specific chart types.
Comparison Charts
Compare values across different categories or groups.
Line Chart
Shows trends and changes in data over time. Ideal for continuous data.
Stock prices over timeWebsite traffic trends
Area Chart
Similar to a line chart but emphasizes the volume or magnitude of change over time.
Revenue growth over timePopulation changes
Data Visualization Best Practices
Choose Appropriate Colors
Use colors that are accessible, meaningful, and consistent. Avoid using too many colors that can confuse your audience.
Label Everything Clearly
Include clear titles, axis labels, legends, and units. Your chart should be self-explanatory without additional context.
Keep It Simple
Remove unnecessary elements that don't add value. Focus on the key message you want to communicate.
Start Axes at Zero
For bar charts and most comparisons, start your y-axis at zero to avoid misleading visual proportions.
Consider Your Medium
Design charts differently for print vs digital, presentation vs dashboard, mobile vs desktop viewing.
Test with Users
Get feedback from your target audience to ensure your visualizations are clear and actionable.
Complete Chart Selection Guide
Step 1: Identify Your Data Type
Categorical Data
Data that can be divided into groups or categories (e.g., product types, regions, departments).
Numerical Data
Quantitative data that can be measured and counted (e.g., sales figures, temperatures, ages).
Time-Series Data
Data points collected over time intervals (e.g., monthly sales, daily website visits).
Step 2: Define Your Purpose
Comparison
Show differences between categories or groups. Use bar charts, column charts, or radar charts.
Trends
Display changes over time. Line charts and area charts work best for trend analysis.
Composition
Show parts of a whole. Pie charts, donut charts, and stacked bar charts are ideal.
Industry-Specific Chart Applications
Finance & Banking
- • Candlestick charts for stock analysis
- • Waterfall charts for cash flow
- • Line charts for portfolio performance
- • Pie charts for asset allocation
- • Heat maps for risk assessment
Marketing & Sales
- • Funnel charts for conversion rates
- • Bar charts for campaign performance
- • Scatter plots for customer segmentation
- • Area charts for revenue trends
- • Bubble charts for market positioning
Operations & HR
- • Gantt charts for project timelines
- • Histograms for performance distribution
- • Organizational charts for structure
- • Gauge charts for KPI tracking
- • Box plots for salary analysis
Common Chart Selection Mistakes to Avoid
❌ What NOT to Do
- • Using pie charts with more than 5-6 categories
- • Starting bar chart axes at non-zero values
- • Using 3D effects that distort data perception
- • Choosing colors that aren't colorblind-friendly
- • Overloading charts with too much information
- • Using line charts for categorical data
- • Ignoring your audience's data literacy level
✅ Best Practices
- • Choose chart types that match your data story
- • Use consistent color schemes across charts
- • Include clear titles and axis labels
- • Test charts with your target audience
- • Keep designs simple and focused
- • Ensure accessibility for all users
- • Provide context and explanations when needed
Recommended Data Visualization Tools
Free Tools
- • Google Charts
- • Chart.js
- • D3.js
- • Plotly
- • Apache ECharts
Business Tools
- • Tableau
- • Power BI
- • Looker
- • QlikView
- • Sisense
Online Platforms
- • Canva
- • Infogram
- • Datawrapper
- • Flourish
- • RAWGraphs
Programming
- • Python (Matplotlib)
- • R (ggplot2)
- • JavaScript
- • Jupyter Notebooks
- • Observable