# Data Visualization Cheat Sheet

In this data visualization cheat sheet, you'll learn about the most common data visualizations to employ, when to use them, and their most common use-cases.

Apr 2022 · 5 min read

Have this cheat sheet at your fingertips

Download PDF## How to Capture a Trend

These data visualizations allow you to display a trend over time. Here's a breakdown of these charts:

**Line chart:**The most straightforward way to capture how a numeric variable is changing over time**Multi-line chart:**Captures multiple numeric variables over time. It can include multiple axes allowing comparison of different units and scale ranges**Area chart:**Shows how a numeric value progresses by shading the area between line and the x-axis**Stacked area chart:**Most commonly used variation of area charts, the best use is to track the breakdown of a numeric value by subgroups**Spline chart:**Smoothened version of a line chart. It differs in that data points are connected with smooth curves to account for missing values, as opposed to straight lines

## How to Visualize Relationships

These data visualizations allow you to display relationships between data points. Here's a breakdown of these charts:

**Bar chart:**One of the easiest charts to read which helps in quick comparison of categorical data. One axis contains categories and the other axis represents values.**Column chart:**Also known as a vertical bar chart, where the categories are placed on the x-axis. These are preferred over bar charts for short labels, date ranges, or negatives in values.**Scatter plot:**Most commonly used chart when observing the relationship between two variables. It is especially useful for quickly surfacing potential correlations between data points.**Connected scatterplot:**A hybrid between a scatter plot and a line plot, the scatter dots are connected with a line**Bubble charts:**Often used to visualize data points with 3 dimensions, namely visualized on the x-axis, y-axis, and with the size of the bubble. It tries to show relations between data points using location and size**World cloud chart:**A convenient visualization for visualizing the most prevalent words that appear in a text. This can be used to visualize the relationship between different words that appear together or capture a trend on the most commonly prevalent words.

## Part-to-whole Charts

These data visualizations allow you to show sub-categories within a large category

**Pie chart:**One of the most common ways to show part to whole data. It is also commonly used with percentages**Donut pie chart:**The donut pie chart is a variant of the pie chart, the difference being it has a hole in the center for readability**Heat maps:**Heatmaps are two-dimensional charts that use color shading to represent data trends**Stacked column chart:**Best to compare subcategories within categorical data. Can also be used to compare percentages**Treemap charts:**2D rectangles whose size is proportional to the value being measured and can be used to display hierarchically structured data

## How to Visualize a Single Value

These data visualizations allow you to visualize a single data point

**Card:**Cards are great for showing and tracking KPIs in dashboards or presentations**Table chart:**Best to be used on small datasets, it displays tabular data in a table**Gauge chart:**This chart is often used in executive dashboard reports to show relevant KPIs

## How to Capture Distributions

These data visualizations allow you to visualize the distribution of a variable

**Histograms:**Shows the distribution of a variable. It converts numerical data into bins as columns. The x-axis shows the range, and the y-axis represents the frequency**Box plot:**Shows the distribution of a variable using 5 key summary statistics—minimum, first quartile, median, third quartile, and maximum**Violin plot:**A variation of the box plot. It also shows the full distribution of the data alongside summary statistics**Density plot:**Visualizes a distribution by using smoothing to allow smoother distributions and better capture the distribution shape of the data

## Visualize a flow

These data visualizations allow you to visualize how data points flow into eachother

**Sankey chart:**Useful for representing flows in systems. This flow can be any measurable quantity**Chord chart:**Useful for presenting weighted relationships or flows between nodes. Especially useful for highlighting the dominant or important flows**Network chart:**Similar to a graph, it consists of nodes and interconnected edges. It illustrates how different items have relationships with each other