Multi-dimensional analysis with Data Tables
Amplitude Academy
Analyze Multiple Metrics at Once with Data Tables
Learn how to do multi-dimensional analysis with Data Tables.
Get startedWhen analyzing a rich dataset, analysts often need to compare multiple metrics at once and slice the data by different dimensions to build a custom analysis. Amplitude's Data Tables enable multi-metric, multi-dimensional analyses in a single view.
Use Data Tables for:
- Marketing attribution (total visits, page views, and conversion rate by UTM source)
- Market segment analysis
- Experiment analysis
- Trend investigation
- Comparing time periods across multiple metrics (metric A, metric B, and metric C, broken down by category, compared to last quarter)
Sort columns in ascending or descending order by clicking the metric header, drag or resize columns, and highlight, copy, and paste any number of cells from your Data Table.
Display limits
When you apply group-bys, Data Tables display the top 100 results for a single group-by, or up to 500 results for multiple top-level group-bys. Metrics with attribution have a 20-row limit. These are display limits—Amplitude processes all your data but shows only the top results. Export limits vary by metric type. For complete details, review Results limits and sorting logic in Data Tables charts.
Create a Data Table
To create and use a Data Table:
Go to Create > Chart > Data Table.
In the empty Data Table panel, click Add an event or metric and select the event or metric you want. A new Data Table opens with your chosen event or metric in the first column. Add more by clicking + Add Event or Metric in the rightmost column.
You can create a new metric at this point if you need to.
To break out your events and metrics by property values—such as country, platform, or week—click Select property… in the leftmost column of the table and choose the property.
This runs a group-by on your events and metrics, grouping by the property you selected. You can include up to five top-level group-bys in a single Data Table.
When you do a top-level group-by in a Data Table and include a Formula Metric, the results are consistent with measuring by a Formula in Event Segmentation and grouping by an Event property (as opposed to grouping by a Segment in Event Segmentation).
After you add a group-by property, run a secondary group-by on that row of your Data Table. For example, break your events and metrics out by the
Day of Weekproperty nested withinCountry.Click the bar icon in the rightmost group-by column and select the property.
When using a time dimension as a group-by property, the time dimension must be the last group-by you add: group by: country, then group by: day of week. Adding these group-bys in the reverse order doesn't generate correct results.
- Add user segments if you want. Saved segments are accessible. Multiple segments appear in the table as separate columns within the same metric.
After you configure the data table, you can manage and manipulate your data in several ways.
In any cell, click the Options icon to:
- Open as chart to open a new tab with the chosen metric applied.
- Create cohort to save the chart's data points as a cohort.
- Copy the data to paste elsewhere, or export the data as a CSV file.
In any column header, click the Options icon to:
- Add Filter to apply a filter to the chosen field.
- Duplicate or remove columns.
- Rename a column for clarity or consistency.
To reset a display name to its original name, choose Reset to Original Name from the column's Options icon.
- Save as metric to use the metric in other analyses.
- Attribution to apply an attribution model to the chosen field or all fields.
- Sort values from low to high (ascending) or high to low (descending).
Use metrics in Data Tables
In Data Tables, including a "-" character in any cell included in your formula's calculation results in an error.
Using Uniques as a metric type in combination with group-bys can produce results that look counterintuitive. When you add a group-by to the event in the left column, the total sum for the event in the top row isn't a sum of the rows below. Because a group-by is applied to the event, the same user can exist in multiple rows.
The same logic applies to the Session Totals metric. When you add a group-by in the left column, the total number of sessions in the top row can be fewer than the sum of the rows below. The chart counts a session containing property values X and Y under both X and Y groups.
When you add conversion metrics to your data table, the conversion rate appears in the cell. When you add a group-by, the breakdown shows the conversion rate for each grouped value.
Transpose rows and columns
You can transpose columns and rows of a Data Table when:
- you've toggled on a period over period comparison,
- segments exist in your chart definition,
- you've added top-level group-bys to your data table, or
- time properties exist.
Transposing isn't possible if:
- nested group-bys exist
- you've unchecked Absolute numbers
Transposed Data Tables don't support the display options Relative % for totals, Data bars in cells, or Color % delta.
To transpose a Data Table:
- Add events or metrics to the horizontal axis.
- Add top-level group-bys to the vertical axis.
- Change the Columns dropdown to rows to flip the axes.
Transposed Data Tables are read-only.
Was this helpful?