Pivot Tables

Pivot tables enable you to reorganize and summarize rows or columns of data so as to have another, chosen report. It will not change your spreadsheet itself but will “turn” (pivot) the data, giving it another perspective. These special tables are useful when you have to deal with an important amount of data to analyze, as they automatically sort, count, average or total the data that is gathered in a data source. They will help you to quickly create a simpler cross tabulation.


For instance, as an online retailer with a thousand of products, you cannot go through the number of items you have sold over the past six months to know which item is a best-seller. In theory you could, but that would take you an indecent amount time and energy. Thanks to a pivot table, you can re-arrange all that data and summarize the details of each of your items to have a clearer picture of your sales in the past half year.


How To Build Pivot Tables in datapine


datapine’s pivot tables are a great way to summarize, aggregate and analyze your data. They are easy to build and will help you to gain valuable insights at a quick glance. Follow the steps below to learn how to create a pivot table in datapine.


Pivot Table Example created with datapine


  1. Start building your pivot table with a click on Analyze in the upper navigation bar to open the Chart Creator.
  2. Below, in the dropdown menu on the Chart Creator’s tool bar click on Chart Type and select Table.
  3. Now, drag and drop the fields you wish to measure into the Y-Axis and the fields you wish to use to group your data by into the X-Axis.
  4. Add a field to the Decompose by area to further break down your data. This will add additional sub-columns which aggregate your measured values by the selected variables and thus create a basic pivot table format of your data.
  5. Optionally, you may add a field to Filter by to further limit your result set.

Tip: Use the conditional formatting options or the cell background gradient to highlight outliers in your data.