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# Add another dataset's rows to a dataset in Mammoth

> Append or replace a Mammoth dataset's rows from another dataset in the project: pick the source, map columns, keep or delete it, or save as a new dataset.
>
> Applies to: Roles: Edit-level access to the destination dataset. Where: Data Library › dataset panel › Add data › Select existing

You can load the rows of another dataset in the same project into a dataset, adding them or replacing what is there, for example to merge two datasets that share the same columns. Open the destination's panel in the **Data Library**, click **Add data**, and choose **Select existing**. You need Edit-level access to the destination dataset, and the source must be in the same project.

The **Update method** at the top of the dialog applies here too: **Add to existing data** appends the source rows and keeps previous data; **Replace all data** deletes all existing rows and inserts the source rows. See [Choose add or replace](https://mammoth.io/docs/learn/get-data-in/add-or-replace-data/#choose-add-or-replace-the-update-method).

![Animation of the Add or Replace data dialog with Select existing chosen and an empty Select dataset dropdown](https://mammoth.io/docs/images/20260508_050328_map-replace.webp)

## Pick the source dataset

1. Choose **Select existing**.
2. Open the **Dataset** picker and choose the source. It lists the other datasets in the project, plus the project's unprocessed PDF files (marked **Unprocessed PDF**).
3. Check the data preview of the source columns and first rows.

![Select existing source list showing store_transaction and cust1-extra-col.xls_test02, a data preview, and a Review Column Mapping button](https://mammoth.io/docs/images/20260430_065845_select-existing-list-dataset-to-combine1.webp)

Datasets that hold unstructured data are marked with a warning icon and **Needs structuring**. They appear only when the destination dataset has a saved recipe, and they must be structured to match the destination before they can combine.

Two picks behave differently:

- **Unprocessed PDF:** Mammoth replays the destination's saved recipe on the PDF. There is no column mapping, and the button is **Submit**.
- **Needs structuring:** the button is **Apply Recipe**. It previews the destination's recipe applied to the source dataset, and nothing is written until you select **Submit**. Submitting confirms the recipe on the source and deletes the source dataset.

## Keep or delete the source dataset

The **Delete dataset after combining** checkbox is ticked by default. It is hidden when you pick a PDF or a dataset that needs structuring. If left ticked, Mammoth permanently deletes the source dataset after the operation. Untick it to keep the source; leave it ticked only when the source is a temporary staging dataset you no longer need.

![Add or Replace data dialog with Select existing chosen, orders.csv in the source field, and Delete dataset after combining checked](https://mammoth.io/docs/images/20260505_060220_Screenshot2026-04-281612071.webp)

## Check that the columns match

After you pick a source, Mammoth checks whether its columns match the destination's.

| Outcome | What you see | What to do |
| --- | --- | --- |
| Columns match | Green check: "New data matches the settings" | Click **Validate** or **Submit**, or **Review Column Mapping** to adjust |
| Columns differ | Red message: "These columns do not all match the dataset's, by name or by type. Review the column mapping to line them up." | Click **Review Column Mapping** and map the columns |

## Map the columns when they differ

![Column mapping view with Customer id unmapped, Customer name and Item matched, Save results into options, and Previous and Validate buttons](https://mammoth.io/docs/images/20260430_071019_review-column-mapping1.webp)

The sub-header confirms what is happening, for example "Daily Sales is combining data with orders.csv", with the **Delete dataset after combining** checkbox beside it.

The mapping table lists every destination column on the left (with its data type icon: `T` for Text, `#` for Number, `⏱` for Date / Time) and a **Select column** dropdown on the right for the matching source column.

- Use **Filter columns by** to show **All**, **Matched** or **Unmatched** columns.
- A column search appears when the dataset has many columns or when you start typing.
- When a mapped source column has a different type from the destination column, a selector lets you choose which type to keep.
- **Validate** is enabled once at least one column is mapped (and, for a new dataset, once it has a name). Unmapped columns are allowed.
- After a successful validation, the button becomes **Submit**.

## Save the result as a new dataset

By default, the combined result overwrites the destination dataset. Set **Save results into** to **New Dataset** to keep both the source and the destination and write the output to a new dataset. You can name it (up to 300 characters). With **New Dataset**, **Submit** is available without validating.

## Check what the change affects before you submit

When you click **Validate**, Mammoth checks for Views, pipelines or tasks that depend on the destination dataset and would be affected. If it finds any, a **Review** window lists them. Confirm you understand the impact before the final submit becomes available.

After you submit, the operation runs in the background and a message confirms when the source dataset will be deleted. See [What happens after you submit](https://mammoth.io/docs/learn/get-data-in/add-or-replace-data/#what-happens-after-you-submit).

## Related

- [Add rows to a dataset or replace its data](https://mammoth.io/docs/learn/get-data-in/add-or-replace-data/): upload a file, and what happens after you submit.
- [Combine datasets](https://mammoth.io/docs/learn/organise/combine-datasets/): put the rows of several datasets together from the list.
- [Set column mapping and type rules](https://mammoth.io/docs/learn/get-data-in/column-mapping-rules/): aliases and type rules for every load.
- [Activity log](https://mammoth.io/docs/learn/automate/activity-log/): every batch operation with time and user.

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Source: https://mammoth.io/docs/learn/get-data-in/add-from-another-dataset.md · Updated: 2026-11-08