Visualize data
Visually inspecting a dataset isn't the easiest way to uncover patterns and relationships in your data, and the bigger the dataset, the slower the task. Data can quickly be converted into an easy-to-understand visualization, such as a bar chart or a graph that brings your data to life.
Common visualizations include:
Line chart - A line chart plots values as points on a chart, then joins these values to create a line. This line immediately shows the trend you're measuring. A line chart has an X and a Y axis. The X axis is frequently used to show time, which you read horizontally from left to right across the chart. The Y axis, or the vertical axis, represents the measure, such as revenue. When you have multiple series, or lines, on your chart, it's good practice to include a legend to clarify what each line equates to. You can also include a title on your chart.
Pie chart - The pie chart isn't commonly used by statisticians and data scientists, but it's favored in business reporting, and is portioned by the categories in your dataset. Pie charts don't have an X or Y axis, but you can include a title and a legend.
Bar chart - Bar charts, also known as column charts, compare numeric values across categories. You can have multiple series or conditions and, like a line chart, the bar chart includes an X and Y axis. Again, it's good practice to include a title on your chart, and a legend if you have multiple series.
Scatter chart - You can use scatter charts when you need to compare two numeric values. Rather than using time along the X axis, you've used another field. For example, you could measure the sales of a product depending on an exchange rate, with the rate scaled along the X axis, and the sales value plotted along the Y axis.
Other visualizations, such as a map, help to show data patterns that would otherwise be hidden. The choice of chart that you use affects how the story behind the data is revealed. Dashboards are a useful tool for displaying a dataset using different visualizations to uncover trends.
In this video, you'll see how data can be represented using different types of visualizations, and how easy it makes reading the patterns within a dataset: