Spider Web Chart

Spider Web Charts are useful to highlight outliers or similarities in your data by displaying multivariate data with three or more quantitative variables. What does that all mean?


Spider charts can help when you basically need to compare more than two “things” with more than three aspects for each of them. One condition however is that you can quantify each “thing” the same way. You can for example compare regions (Australia, Europe, North America). For each of those regions you have a certain quantity of products sold (Computers, Cell Phones, Games, TVs or Cameras). The spider chart enables you to see how each country is performing in terms of sales for each category of product (see image below).


This is a type of chart that you can also use to undertake evaluations. For example, when conducting numerous interviews for your company, you may need to assess a candidate’s suitability to others’. This is where the spider chart is useful, by comparing the candidate’s skills and qualities to the ones of other applicants, displaying it all on one graph.


How to create a Spider Web Chart in datapine


spider web chart created with datapine


  1. Click on Analyze in the upper navigation bar to open the Chart Creator.
  2. Select Chart Type in the tool bar and choose Spider Web from the dropdown menu.
  3. Drag and drop one or several numeric fields into the Y-Axis area and the field for which you wish to split up your data into the X-axis area.
  4. Optional: You might also want to use a field in the Decompose by area to additionally split up your data series into several dimensions.
  5. Optional: You can add a date field to the Filter by field to get the data for a specific time range.

Tip: Changing the series type of a Spider Web from line to column will create a Wind Rose Chart.


Tip 2: Once again, keep in mind that less is more, especially with this kind of very special chart that is rarely used. The strength of spider charts is that when correctly done, they are impressive and tell the story by themselves. If you have more than five values in your dimension (X Axis), the “things” you want to evaluate, it will become hard to read and take away all your point.