Duplicated keys column after join

[juba]

Hi,

First of all, many thanks for this awesome library that makes working with tabular data much more natural. As an Observable newbie coming from R and dplyr, I really appreciate it.

A small question : when joining two tables, the key column(s) are duplicated in the resulting joined table. For example, if both tables are merged on the same key column, the resulting table will have both a key_1 and a key_2 columns. In other languages or libraries I'm accustomed to the fact that the result only has a key column, as the original one.

Please excuse me if it is the intended behavior or if I am misunderstanding something.

Thanks.

[jheer]

Thanks! This is the intended behavior. The join verb also supports arbitrary predicate functions for testing if two rows match, and so it is not always apparent if two columns are equivalent. To drop unwanted duplicate columns you can do something like this:

dt.join(table, ['key', 'key'], [aq.all(), aq.not('key')])

This will join on two columns both named 'key', with a result that drops the 'key' column drawn from the second table. As a result no suffix will be added to the column drawn from the first table.

[juba]

Thanks for the detailed explanation !