Tutorials, guides, and examples for all of the major ones and some others.
The flow chart type is useful for showing changes over time across categories. The geometry is similar to a stacked area chart but with spacing and order changes.
The space between the data and the baseline is filled with a color or a pattern, usually emphasizing counts or percentages for a single variable.
The old standby. The classic. The bar height or length represents data. The baseline starts at zero.
A compact way to show a distribution, line segments represent individual points along a single axis.
It's like a line chart, but it specifically uses a reference point, which becomes the baseline, to compare all the other categories to.
It emphasizes individual points in a distribution instead of binning them like a histogram.
Points are placed like in a scatter plot, but they are sized based on the square root of data values.
It looks like a line chart. However, the focus is specifically on ranks, usually over time.
A familiar, everyday layout to show data over time. It is especially useful to show recurring weekly patterns.
Regions are colored by a variable. Be careful with your color choices, as they can quickly change what the map shows.
Connected Scatter Plot
A cross between a scatterplot and a time series. Show two variables over time.
Fill the space between lines to highlight the greater-than and less-than differences over time.
It is like a pie chart. But with a hole. It looks like a donut. That's why it's called a donut chart.
Dot Density Map
Dots are placed randomly within regions to show the density of populations. The dots and spacing allow for multiple groups to be shown at once.
A generalized form of the scatter plot, the dots can be placed in various coordinate systems.
Area or line chart value axes overlap to fit more in a space and add another visual aspect to the magnitude of peaks. Also known as: ridgeline chart, joyplot.
It's a type of bar chart that shows the end and start times. The bars are offset by the former.
Instead of using geographic boundaries, same-size cells are used to represent areas to provide equal visual attention to all.
Cells or bins are colored based on data. As with all visualization types that use color as the main visual encoding, choose shades carefully.
It looks like a bar chart, but it reads differently. The baseline is continuous instead of discrete categories, which allows one to see distributions.
Typically used to show trends over time, the slope of the line between two points shows patterns of change.
Also known as a Marimekko diagram, this chart uses the width and height of rectangles to represent separate variables. It can be useful to represent multidimensional data.
Nodes and edges show connections, typically positioned to show strength of relationships.
It's also known as an org chart, but I'm going with this from now on because it sounds more sophisticated.
Packed Bubble Chart
Circle size represents data like with a bubble chart, but there is typically no x-y axis. Instead position often represents grouping or is used to maximize space.
Explore counts across multiple categories at the same time. The geometry is similar to a Sankey Diagram but without the hierarchical flow.
It's everyone's very favorite chart type. It's okay, you can admit it. The slices represent parts of a whole.
Dots are placed in an x-y coordinate system, based on two variables. The plot is often used when it is thought that the variables are correlated.
Spikes of (usually) equal width but varying height are centered on geographic areas. They are often used to show abnormally high counts in concentered regions.
Stacked Area Chart
Place multiple categories on top of each other for a sense of distribution and overall change. Watch out for large counts eclipsing the small ones.
Stacked Bar Chart
With the stacked version of the bar, compare subcategories across groups. Try not to show too many subcategories though, or it'll clutter quick.
It works like a line chart, but the values change immediately at the x-coordinate instead of with a slope.
Dots are placed along a single continuous scale to show distribution along the corresponding variable.
It shows the individual values as they compare to the whole. Rectangles are arranged to maintain hierarchy.
Each polygon, or Voronoi cell, contains an original point and all areas that are closer to that point than any other.