In the data visualization world, the term “chart” can mean many things. It can be a type of diagram that organizes a set of data. It can be map with technical information included, such as a nautical chart. But the thing that all chart types have in common is that they are a graphical representation of data where the data is represented by some kind of symbol: bars in a bar chart, pie slices in a pie chart, lines in a line chart.
Charts are used to make large quantities of data easier to read and to make the relationships between the data easier to comprehend. Like most data visualizations, charts can be read more quickly than the raw data could, and they make the story behind the data easier for the viewer to grasp.
Some chart types are more useful for certain purposes and certain data than others. Percentages might be displayed in a type of chart called a pie chart, or in a bar chart, while data that changes over time might be displayed as a type of chart called a line chart.
No matter what type of chart we’re discussing, most charts have a few common features. They generally focus more on the graphic than on text. And the chart will probably have a legend containing the variables appearing in the chart (e.g. “yes is blue, no is red, undecided is green”).
But it’s the differences between types of charts that are more interesting, because this in when we can start to decide which type of chart will work best for which type of data.
There are many, many types of charts out there. Some of the most common types of charts we’ve already mentioned: bar charts, pie charts and line charts. A bar chart is a chart with rectangular bars with lengths proportional to the values they represent. A pie chart shows percentages displayed as a slice of pie. A line chart connects data arranged over time in order to show trends over time.
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