What's the best chart for your data analysis?

1 Categorical data

Categorical data are data that can be divided into groups or categories, such as gender, color, or product type. Categorical data can be either nominal (no order) or ordinal (has order). For example, hair color is nominal, while education level is ordinal. To visualize categorical data, you can use charts that show the frequency or proportion of each category, such as bar charts, pie charts, or donut charts. Bar charts are good for comparing multiple categories or showing changes over time. Pie charts and donut charts are good for showing the relative size of each category within a whole. However, avoid using too many categories or slices, as they can make your chart hard to read.

2 Numerical data

Numerical data are data that can be measured or counted, such as age, income, or sales. Numerical data can be either discrete (finite) or continuous (infinite). For example, number of customers is discrete, while temperature is continuous. To visualize numerical data, you can use charts that show the distribution, correlation, or aggregation of the data, such as histograms, scatter plots, or line charts. Histograms are good for showing the frequency of different values or ranges in your data. Scatter plots are good for showing the relationship or correlation between two variables. Line charts are good for showing the trend or change of a variable over time or across categories.

3 Temporal data

Temporal data are data that relate to time, such as date, hour, or season. Temporal data can be either absolute (fixed) or relative (variable). For example, birth date is absolute, while age is relative. To visualize temporal data, you can use charts that show the sequence, duration, or cycle of the data, such as timelines, Gantt charts, or calendar charts. Timelines are good for showing the order of events or milestones in your data. Gantt charts are good for showing the duration or progress of tasks or projects in your data. Calendar charts are good for showing the frequency or intensity of events or activities in your data.

4 Spatial data

Spatial data are data that relate to location, such as country, city, or coordinates. Spatial data can be either geometric (shape) or geographic (position). For example, area is geometric, while latitude is geographic. To visualize spatial data, you can use charts that show the shape, position, or distance of the data, such as maps, diagrams, or bubble charts. Maps are good for showing the geographic distribution or variation of your data. Diagrams are good for showing the structure or hierarchy of your data. Bubble charts are good for showing the size or magnitude of your data relative to a location or category.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?