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.

The standard bar chart is animated to show rankings and change over time. The alternative is a multi-line chart.

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.

The classic chart of quartiles, median, minimum, and maximum shows a basic view of distributions.

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.

Regions scale based on data instead of preserving geographic area.

Show connections between nodes.

Regions are colored by a variable. Be careful with your color choices, as they can quickly change what the map shows.

A cross between a scatterplot and a time series. Show two variables over time.

Look at distributions under the curve.

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.

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.

Each dot represents a data point. Collectively, geographic patterns emerge.

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.

Symbols are used and various dimensions represent different variables in a dataset.

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.

Compact the area chart by slicing it horizontally, and then then shifting the slices to baseline zero. It's like a combo area chart and heatmap.

Typically used to show trends over time, the slope of the line between two points shows patterns of change.

Connect the lines in geographic space and see where they go.

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.

Making use of a force-directed graph, bubbles move between different clusters to show grouping over time.

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.

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.

Differing scales run alongside each other, sometimes showing relationships between multiple variables through connections. Can be tricky though.

Explore counts across multiple categories at the same time. The geometry is similar to a Sankey Diagram but without the hierarchical flow.

Use symbols or icons to bring in context.

It's everyone's very favorite chart type. It's okay, you can admit it. The slices represent parts of a whole.

Typically used to show the age distributions for population of male and females. Often animated.

Looks like a radar. That's why it's called a radar chart.

Show flows from one state to the next.

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.

A specialized line chart, this chart type highlights the change in rank or metric over two time periods.

Use smaller versions of the same chart type to compare across categories.

Round and round and round and round and round.

Instead of using angle to represent parts of a whole, the square version uses, well, squares.

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.

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.

It's like a stacked area chart but with a zero-offset to optimize centrality.

Dots are placed along a single continuous scale to show distribution along the corresponding variable.

In 3-D space, closer to a real-world representation.

Visually plain and boring. Sometimes exactly what you want.

Show three metrics that sum to a whole. It's good for showing the ratio between the metrics.

Place a focus on events over time.

It shows the individual values as they compare to the whole. Rectangles are arranged to maintain hierarchy.

A symbol is used for each unit to place emphasis on individuals or objects.

The vertical height is the same as a regular bar chart. The widths of bars show another dimension for each category. The two dimensions multiplied, area, should mean something.

An abstract visualization method to show the intersection between categories.

Each polygon, or Voronoi cell, contains an original point and all areas that are closer to that point than any other.