Attaching multiple variables to the 2D graphs as attributes
In the previous section, we saw how to create scatter plots for showing the correlation of CO2 and Methane emissions across different power plants. One useful option is to change the color of data points based on different industry groups to see how different plants CO2 and Methane emission are correlated across different industries. As a result, we drag and drop Industry groups into the Marks and change the visualization mode to Color:
The color coded industry groups into the scatter plot is shown here:
if we choose Power Plants from the right panel that shows different industry groups, we clearly see that there is a linear relationship between CO2 and Methane emissions of power plants:
Scatter plot matrix:
In the previous section we color coded the various industry groups into the scatter plot of CO2 and Methane emissions. We could create multiple scatter plots (i.e. scatter plot matrix) that shows correlation of one variable versus several parameters. As a result, we put reported CO2e emissions in the Rows and Methane (CH4) emissions, Biogenic CO2 emissions, Nitrous Oxide (N2O) emissions, and CO2 emissions (non-biogenic) into the Columns and Industry groups as color to create this scatter plot and filter Natural Gas and Power Plants industries (make sure you change the scale of x and y axes to logarithmic by clicking on them):
Attributing size and marker shape into scatter plot:
Before creating this scatter plot, please enable back the Aggregate Measures. Now put Methane (CH4) emissions into the columns and reported CO2e emissions into the Rows. Put Industry groups and State into the Filter as Marks and put Industry groups on Color and State on Color, Shape, and Size:
Now, filter the Industry groups to show Power Plants and State to show SC and NY:
In the next section, we'll learn how to work with calculated fields, merge two datasets together in Tableau, and finally use built-in statistical tools to show trends in scatter plots.