Data Visualization Guide
Master data storytelling. Learn which chart tells your story best, accessibility principles, and when to use Excel vs Tableau vs Python.
Private by design
For file-based tools, processing is designed to happen in your browser. Avoid uploading confidential files to any website unless you are comfortable with the workflow and have permission to use the data.
Use responsibly
Use the result as a practical first pass, then verify any important decision with the appropriate source or professional.
Free access
ToolDox tools are free to use, require no signup, and are supported by clear navigation, guides, templates, and related tools.
Related Tools
How to choose the right chart type
The best chart type depends on three things: what kind of data you have, how many variables you are comparing, and what story you want to tell.
Common chart types and when to use them
Bar chart: Comparing categories. Use when you have discrete groups and want to show magnitude differences.
Line chart: Showing trends over time. Best when time is on the x-axis and you want to show change.
Scatter plot: Showing the relationship between two numeric variables. Great for correlation analysis.
Pie / Donut chart: Showing part-to-whole relationships. Only use with fewer than 6 categories.
Histogram: Showing the distribution of a single numeric variable.
Heatmap: Showing patterns in a matrix of two categorical variables.
Box plot: Comparing distributions across groups, including median, quartiles and outliers.
Frequently asked questions
Can I use a pie chart for more than 5 categories? Technically yes, but it becomes very hard to read. Use a bar chart instead.
When should I use a log scale? When your data spans multiple orders of magnitude — for example revenue data that ranges from $100 to $10,000,000.