Chart Types

An overview of chart types supported in Cohort Browser

Apollo Cohort Browser provides a variety of chart types that quickly visualize your data.

You can quickly visualize a data field of interest by adding a single data field as a Tile. Data fields can also be combined to create Multi-Variable Charts, which helps identify relation across different data fields.

As you browse and select data fields in a dataset, Cohort Browser would provide suggested chart types basing on the combination of data fields chosen.

Single-Variable Charts

  1. Row Chart

  2. Histogram

  3. Box Plot

  4. List View

Multi-Variable Charts

  1. List View

Interpreting Chart Data

Chart Total and Missing Data

For any chart type, a chart total count is provided under the chart title. The chart total is the total number of non-null/non-empty unique data points the chart is visualizing.

The chart total is not always equal to cohort size. This is due to the fact that some records in your cohort selection may be missing data on this field and thus are not visualized in the chart. You can see number of records with missing data by hovering over the warning icon.

Hover to see missing data count

For multi-variable charts that combine more than one data fields, the chart would include only records with non-null/non-empty data on BOTH data fields. Records with null/empty values on either of the two data fields would be treated as having missing data, and thus not visualized as part of the chart.

Note: All data and counts shown in a chart are specific to the entity which the chart is based on. In the example above, the chart is based on entity "Participants". Thus, all numbers in this chart are thus counting unique number of participants that are currently in your cohort selection.

Note that chart types only support up to 30,000 results. For fields where more than 30,000 results exist, only the top 30,000 are shown. This is most commonly encountered in scatter plots and list view.