The heat table is a graphical representation of data to better visualize the volume of ‘events’ within a dataset and assist in directing viewers towards areas that matter most: values of a matrix are represented as colors.
Magnitudes are shown into a matrix of fixed cell size whose rows and columns are discrete phenomena and categories, with the goal of suggesting clusters or outliers.
The heat table can be found underneath the ‘Special charts’ section. You can add it to the editor by clicking on it or by drag and drop. There are three data slots to add data to - ‘X axis‘, ‘Measure’ and ‘Y axis’.
Columns with data type ‘hierarchy’ are a perfect fit for this slot. You can also use a specific date level, such as year or month, or a numeric. It might be interesting to enable or disable binning in the data slot settings when using a numeric depending on your use case.
The data added to the two slots defines the number of boxes - or combinations of categories - that will appear.
If your X-axis has 4 unique value possibilities, and your Y-Axis has 5 unique value possibilties, then there will be a total of 4 x 5 boxes.
The measures from the particular category combination will be aggregated into the box.
Make sure not to have too many categories on the chart. As it might look messy and difficult to analyze.
Columns with data type ‘numeric’ are a perfect fit for this slot.
The measure slot defines the numeric value of a box - or combination of the X and Y-axis categories. Different aggregations can be set in order to be able to execute different calculations, e.g. the average.
It is not always easy to interpret the exact values, luckily you can toggle on the option ‘show values’ in the general settings of the chart.
Adjust the coloring logic by changing the colors type, method, number of classes and selecting a specific color scheme from the chart settings.