How to merge datasets in Flourish
Merging data is useful when you have two datasets with shared variables — for example, a dataset containing country names and GDP, and another containing country names and life expectancy. Flourish allows you to take both datasets and merge them together based on their shared column. In our example below, the shared column is the country name.
Merging data is possible across all Flourish templates and this help doc will walk you through how. Note that before merging data into a template, you should make sure that you understand the data structure and that it matches that of the template.
To merge datasets in Flourish,
- Start by uploading your first dataset to Flourish via the Upload data button. If you're looking to merge data into one of our Projection map or 3D region map starting points, you can skip this step.
- Now it's time to merge in our second dataset. To do this, click on the arrow next to the Upload data button and select Upload data and merge. Then, select your second dataset.
You will be prompted to select which columns to join on. By default, Flourish detects which columns contain similar values and pre-selects them. The values in these columns you are choosing need to match exactly for rows to merge successfully.
TIP: If your datasets have identifying codes, like ISO codes or area codes, it is recommended to use these to join on, as they are more reliable than names, which might be spelled differently across different datasets.
If you have data in either dataset that does not match, you can choose between keeping these rows or discarding them.
Additionally, you can opt to keep or discard the merging column of the dataset that is already uploaded on Flourish and that the matching column you are merging in with.
That's it! You have successfully merged two datasets. This is especially useful in Projection map template in order to keep the geometry column. Learn more about this template in our overview help doc.