I have a question regarding joining two datasets together. I now have data that looks like this: (example)
| dummy | ID | current year|
| -------- | -------------- |------- |
| 0 | 1 |1621
| 0 | 1 |1622
| 0 | 1 |1623
| 1 | 1 |1624
| 0 | 2 |1623
| 0 | 2 |1624
| 0 | 2 |1625
| 0 | 2 |1626
| 0 | 2 |1627
| 1 | 2 |1628
I have another huge dataset containing all sorts of information about every transaction, for example:
| Gender | ID | Price|
| -------- | -------------- |------- |
| 1 | 1 |16
| 0 | 2 |12
| 0 | 3 |13
| 1 | 4 |22
| 0 | 5 |23
| 0 | 6 |38
| 1 | 7 |10
| 0 | 8 |16
| 0 | 9 |17
| 1 | 10 |8.
I now want to add a column to the first dataframe, which states the gender for every row. I guess this could be done by looking at the ID. Note that the first dataset has multiple rows per ID, and is thus much longer. I have no idea how to do this so any help would be appreciated, let me know if anything is still unclear :) Like this:
| dummy | ID | current year | Gender |
|---|---|---|---|
| 0 | 1 | 1621 | 1 |
| 0 | 1 | 1622 | 1 |
| 0 | 1 | 1623 | 1 |
| 1 | 1 | 1624 | 1 |
| 0 | 2 | 1623 | 0 |
| 0 | 2 | 1624 | 0 |
| 0 | 2 | 1625 | 0 |
| 0 | 2 | 1626 | 0 |
| 0 | 2 | 1627 | 0 |
| 1 | 2 | 1628 | 0 |
