From Data to Viz – find the graphic you needFrom Data to Viz leads you to the most appropriate graph for your data. It links to the code to build it and lists common caveats you should avoid.
What kind of data do you have? Pick the main type using the buttons below. Then let the decision tree guide you toward your graphic possibilities. Alternatively, check the complete decision tree.
Swipe sideways to see the whole tree →
Violin
Density
Histogram
Boxplot
Ridgeline
Scatter
Heatmap
Correlogram
Bubble
Connected scatter
Density 2d
Barplot
Spider / Radar
Wordcloud
Parallel
Lollipop
Circular Barplot
Treemap
Venn diagram
Doughnut
Pie chart
Dendrogram
Circular packing
Sunburst
Line plot
Area
Stacked area
Streamchart
Map
Choropleth
Hexbin map
Cartogram
Connection
Bubble map
Chord diagram
Network
Sankey
Arc diagram
Edge bundlingDive deeper into the world of data visualization with Dataviz Universe, my newsletter packed with actionable tips and tricks to enhance your data storytelling skills.
When displaying the value of several entities, ordering it makes it way more insightful.
Cutting the Y axis is one of the most controversial practices in data viz. See why.
A line graph with too many lines becomes unreadable: it is called a spaghetti graph.
The human eye is bad at reading angles. See how to replace the most criticized chart ever.
Always try different bin sizes when you build an histogram, it can lead to different insights.
A boxplot is a great way to summarize a distribution but it hides the sample size and data distribution.
Barplots with error bars must be used with great care. Learn why and how to replace them.
If you need to compare the distribution of many variables, don't clutter your graph.
Too many points on your scatter plot makes it unreadable? Techniques exist to avoid overplotting.
Avoid the rainbow color palette when you map a numeric variable. So many better palettes exist.
Placing individual plots horizontally or vertically is an important choice to make.
Your audience is used to a few dataviz standards. Not respecting it can mislead them.
‘From Data to Viz’ is a classification of chart types based on input data format. It comes in the form of a decision tree leading to a set of potentially appropriate visualizations to represent your dataset. Read more.
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