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:
- A
recipient_id
column indicating who received the donation - An
office
column 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are outdated, and I want to replace/override them.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 overrides_df
What is the proper way to join/merge/update these two to achieve that result?