I have a Pandas dataframe (
donations_df) that contains thousands of donations. Each donation row has many columns, but the two key ones for my question are:
recipient_idcolumn indicating who received the donation
officecolumn indicating what legislative office the recipient holds.
Some of the values of the
office column in
donations_df are outdated, and I want to replace/override them.
So I have a second, much smaller dataframe (
overrides_df). It contains the preferred office names I want to use. It has only a few rows (one for each recipient). For example:
| recipient_id | office | | ------------ | ------------------ | | 3839314 | Governor | | 24811446 | Secretary of State | | 12733609 | Auditor | | 6676482 | Attorney General |
What is the proper way to join/merge/update this?
What I want to happen is that for each donation in
donations_df, if that donation's
recipient_id exists in
overrides_df, then then the donation would pick up the new
office value from
What is the proper way to join/merge/update these two to achieve that result?