Create A New Chart


datapine’s intuitive Drag & Drop interface allows you to visualize your KPIs with just a few clicks. As explained in the visualization & chart preview chapter, you can create and build your charts very easily. The structure is simple and made of four categories: what to measure (corresponding to the Y axis on a chart), the dimensions (corresponding to the X axis), how you would like to decompose it or if you would like to apply any filter. The two first parts are obviously essential to a chart, while the two others we put at your disposal are a great way to customize the charts regarding your individual analysis needs. Decomposing can help you in visualizing categorical data (for instance by gender or marketing channel), while the filters enable you to curb the amount of data shown to only specific conditions.


Please follow the instructions below to learn how to create a new chart in datapine using the Chart Creator.




  1. From the top navigation bar click on Analyze to open the empty Chart Creator.
  2. Choose a chart type from the dropdown menu in the middle of the tool bar.
  3. Select your data source from the drop down menu in the left upper corner of the Chart Editor. This will open the list of tables of your selected data source below. Clicking on one of the tables will display the list of data fields which represent the columns of your data source table.
  4. Drag and drop fields from the left into the Measures and Dimensions on the right to build your chart. To learn more about Measures and Dimensions click here.
  5. Click on the small edit icon next to the chart title and assign a name to your chart.
  6. You may now use the Chart Options or Advanced Options to customize the look of your chart. Then Save your chart to a dashboard tab or project.



While you drag a field into the visualization screen the valid areas to drop off your field will be highlighted in blue. The type of field determines where you may add this field to. Click here to learn more about the different field types in datapine.