Join

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Technical documentation

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You can use this step to join a registered dataset to the current dataset, i.e. to bring columns from the former into the latter, matching rows based on columns correspondance. It is similar to a JOIN clause in SQL, or to a VLOOKUP in Excel.

This step is supported by the following backends:

Mongo 5.0
Mongo 4.2
Mongo 4.0
Mongo 3.6
Pandas (python)

Where to find this step?

Widget Combine
Search bar

Options reference

Select a dataset to join (as right dataset):: the name of the dataset you want to append to join to the current dataset
Select a join type: either left or inner:
- left: will keep every row of the current dataset and fill unmatched rows with null values,
- inner: will only keep rows that match rows of the joined dataset.
Join based on column(s):: specify 1 or more column couple(s) that will be compared to determine rows correspondance between the 2 datasets. The first element of a couple is for the current dataset column, and the second for the corresponding column in the right dataset to be joined. If you specify more than 1 couple, the matching rows will be those that find a correspondance between the 2 datasets for every column couple specified (logical ‘AND’).

Example 1: left join on 1 column

Say your dataset being currently edited looks like this:

And say you have a dataset, stored in your application, that references country labels ased on their country code:

ref_countries:

Then if you you apply the following configuration on the current dataset…

…It will result in:

Example 2: inner join on 1 column

Based on the same datasets as in example1, if you you apply the following configuration on the current dataset…

…It will result in:

Example 3: join on several columns

Based on the same ase dataset as in example 1, now say that you have a dataset, stored in your application, that has information on employees number by country and by date:

nb_employees:

You want both the country AND date to be used for matching rows. So if you apply the following configuration on the current dataset…

…It will result in: