Multi-dimensional analysis with Data Tables

When analyzing a rich dataset, analysts often need to compare multiple metrics at once, and slice and dice that data by different dimensions to generate a custom analysis. Amplitude’s Data Tables enable multi-metric, multi-dimensional analyses in a single view. It is an extremely flexible chart, allowing you to quickly analyze any combination of user behavior, user attributes, and metrics. 

Data Tables are useful for:

• Marketing attribution (total visits, page views, and conversion rate by UTM source)
• Market Segment analysis (comparing several actions broken down by country)
• Experiment analysis (multiple metrics by control vs variant groups)
• Trend investigation (quickly and easily breaking down a number by multiple properties)
• Comparing time periods across multiple metrics (metric A, metric B, and metric C, broken down by category, compared to last quarter)

You can easily sort columns in ascending or descending order (just click the metric header), drag and drop or resize columns, and highlight, copy and paste any number of cells from your Data Table.

To get a quick overview of how Data Tables work, check out our short Loom tutorial.

Don't forget to read the Help Center article on results limits and sorting logic in Data Tables.

Feature availability

This feature is available to users on all Amplitude plans. See our pricing page for more details.

Set up a Data Table

To set up and use a Data Table, follow these steps:

1. Navigate toCreate New > Analysis > Data Table.

2. In the empty Data Table panel, click Add an event or metric and select the event or metric you’re interested in. A new Data Table will open, with your chosen event or metric in the first column. Add more by clicking + Add Event or Metric in the rightmost column in the Data Table.

   You can create a new metric at this point, if you need to.

3. To break out your events and metrics by property v alues—country, for example, or platform, or week—click Select property… in the leftmost column of the table and choose the property you’re interested in.

   

   This will run 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.

   Note

   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).

4. Once you’ve added a group-by property, you can run a secondary group-by on that row of your Data Table. For example, you can break your events and metrics out by the Day of Week property nested within Country.

   

   Click the Bar icon in the rightmost group-by column and select the property you’re interested in.

   

5. Next, add user segments, if desired. Saved segments are accessible. Multiple segments will show up in the table as separate columns within the same metric.

Once setup, there are several options you can use to manage and manipulate your data.

Within any cell, click the Options icon to: 

• Open as chart, which will open a new tab with the chosen metric applied;
• Create cohort, which allows you to save the chart's data points as a cohort;
• Copy the data so you can paste elsewhere as needed or export the data as a CSV file.

Within any column header, click the Options icon to:

• Add Filter, which will apply a filter to the chosen field;
• Duplicate or remove columns;
• Rename a column for clarity or consistency of your data;

• Save as metric, which allows you to use the metric in other analyses;
• Attribution, which allows you to apply an attribution model to the chosen field or all fields;
• Sort values by low to high (ascending) or high to low (descending).

Using metrics in Data Tables

With Data Tables, including a "-" character in any cells included in your formula's calculation will result in an error.

In some cases, using Uniques as a metric type in combination with group-bys can generate results that appear counterintuitive at first. For example, when a group-by is added to the event in the left column, the total sum for the event (as seen on the top row) is not a sum of each of the rows below. Because there is a group-by applied to the event, the same user can exist in multiple rows.

The same logic applies to the Session Totals metric. When a group-by is added in the left column, the total number of sessions in the top row can be fewer than the sum of the rows below. This is because a session containing property values X and Y will be counted under both X and Y groups.

Filter your events and metrics for specific values within a group-by

You can click Filter to select which property values you want to keep or hide in the table.

You can also add an ad hoc filter for in-line events or metrics. To do so, click the three dots from the event or metric header and select “Add Filter.” This will let you apply filters on top of your events or metrics. Once applied, you can see what filters are applied by hovering over the Filter icon.

• Session-based and attribute-based metrics are not supported, and
• display options Relative % for totals nor Data bars in cells are not displayed.

Transpose rows and columns

Columns and rows of a Data Table can be transposed 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 is not possible if:

• nested group-bys exist,
• if the table contains session or attribution-based metrics,
• nor if the user has unchecked the Absolute numbers.

To transpose a Data Table, follow these steps:

1. Add events or metrics to horizontal access.
2. Add top level group-bys to vertical axis.
3. Change the Columns dropdown to rows to flip the axes.