Chart Types

Comparison

Comparison appears to be one of the most common activities in data analysis.
In fact, many situations require us to identify the quantitative difference (or similarity) between values and understand which one is larger or smaller than another.
That's why, basically, there are a lot of chart types designed to facilitate comparison by means of data visualization.

Depending on what kind of data you have, what exactly you need to compare, and whether your visualization should also fulfil any other purpose in addition to comparison, choose from the following types of chart.

Data Over Time

When the purpose of your data visualization is to observe the change in values of something over a specific period of time, you should consider the following chart types.
They facilitate the analysis of continuous data sets and are helpful in bringing trends into focus.

Distribution

Visualizing the distribution of a variable in a given interval, geographic area, etc. is a great solution for quickly spotting outliers, clustering trends, and relationships within a data set.
These are the chart types you are most likely to choose from for your data visualization when you are looking for distribution-based conclusions.

Finance

Data visualization in finance is a specific field of charting where candlestick, OHLC and stock chart types prevail.
The series here represents a financial parameter (e.g. price) that changes over time, so the X-axis is always a date/time scale.
Widely used by traders and investors, financial charts may feature technical indicators for easier market trend analysis and prediction.

Location

Map charts are widely used for visualization of location-related data.
This approach significantly facilitates the spatial analysis by allowing viewers to quickly understand the breakdown of data by regions, countries, provinces, and so on.
In particular, map-based data visualizations are helpful for purposes of comparison and distribution trend identification.

Part Of The Whole

Studying the composition and part-to-whole relationships within data gets much easier with the chart types collected in this section.
The main rule here is that a total, taken as 100%, occupies the whole chart. Each constituent part (segment) of the chart represents data points that contribute to the whole and amount to 100% in total.

Proportion

The present section lists the types of chart that visually bring data proportions into focus.
These are helpful for roughly estimating the difference between values at a glance.

As a result, the following chart types make it easy to identify approximately equal as well as obviously different values.
Learn more about each of them to see which one should work best with your data and current purpose of analysis.

Range

When your data set contains maximums and minimums instead of precise or average values, go for the range charts.
In this way, your visualization will clearly display the largest (highest) and the smallest (lowest) values of points, which greatly facilitates further comparison-based analysis of the resulting ranges.