How to Read Scatter Chart and Bubble Chart
Scatter charts show the relationships among the numeric values in several data series, or between two groups of numbers as one series of XY coordinates.
A scatter chart has two value axes, showing one set of numerical data along the horizontal axis (X-axis) and another one along the vertical axis (Y axis). It combines these values into single data points and displays them in uneven intervals, or clusters. Scatter charts are commonly used for displaying and comparing numeric values, such as scientific, statistical and engineering data.
Scatter plots are best used for data sets in which there is likely to be some form of relationship or association between two different elements included within the data, for example, the relationship between Sales and Quantity per Customer. Financial analysts often use these plots to show correlation between two funds, two stocks or even a stock and the general market.
The following chart presents the relationship between salary and age for 474 employees of a company. This type of data would be expected to show some form of trend since, as the staff gains experience, you would expect their value to the company to increase and therefore their salary to also increase.
As an example, one of the employees as 28.5 years old and had a salary of $16,080. To put this data onto a scatter plot, we insert age into the horizontal axis and salary onto the vertical axis. The different entries onto the plot are the 474 combinations of age and salary resulting from a selection of 474 employees, with each observation being a single point on the chart.
The charts shows that in fact for this company there is no obvious relation between salary and age. We can observe that the age range of employees is from 23 to 65. We can also see that a lone individual earns a considerably higher salary than all the others and that starters and those nearing retirement are actually on similar salaries.
Interpretting a Scatter Plot
Having drawn the plot it is necessary to interpret it. The author should do this before it is passed to any user. The most obvious relationship between the variables X and Y would be a straight line or a linear one. If such a relationship can be clearly demonstrated then it will be of assistance to the reader if this is shown explicitly on the scatter plot. This procedure is known as linear regression and we will discuss it in another course.
A Bubble Chart or Bubble Graph is used to display three dimensions of the data. Each datapoint is plotted as a disk that expresses two of the values through the disk's xy location and the third through its size. Bubble charts can facilitate the understanding of social, economical, medical, and other scientific relationships. A Bubble Chart can be plotted on both Cartesian coordinate grid and Scatter coordinate grid.
The following chart shows the Gross Domestic Product and Gross National Income (per Capita) of various countries. The size of the bubble shows the actual GDP of the place.
- Overview of Data Visualization
- When to Use Bar Chart, Column Chart, and Area Chart
- What is Line Chart and When to Use It
- What are Pie Chart and Donut Chart and When to Use Them
- How to Read Scatter Chart and Bubble Chart
- What is a Box Plot and How to Read It
- Understanding Japanese Candlestick Charts and OHLC Charts
- Understanding Treemap, Heatmap and Other Map Charts
- Visualization in Data Science
- Graphic Systems in R
- Accessing Built-in Datasets in R
- How to Create a Scatter Plot in R
- Create a Scatter Plot in R with Multiple Groups
- Creating a Bar Chart in R
- Creating a Line Chart in R
- Plotting Multiple Datasets on One Chart in R
- Adding Details and Features to R Plots
- Introduction to ggplot2
- Grammar of Graphics in ggplot
- Data Import and Basic Manipulation in R - German Credit Dataset
- Create ggplot Graph with German Credit Data in R
- Splitting Plots with Facets in ggplots
- ggplot2 - Chart Aesthetics and Position Adjustments in R
- Creating a Line Chart in ggplot 2 in R
- Add a Statistical Layer on Line Chart in ggplot2
- stat_summary for Statistical Summary in ggplot2 R
- Facets for ggplot2 Charts in R (Faceting Layer)
- Coordinates in ggplot2 in R
- Changing Themes (Look and Feel) in ggplot2 in R