I'm looking for help for this problem.
Given this a dataframe like this:
| A | B |
| 0 | Blue apple |
| 1 | White banana |
| 2 | Red banana |
| 3 | Red apple |
I have to find the row indexes of rows where I have 'Red' in column 1.
In SQL I would do something like
SELECT A
FROM df
WHERE B LIKE 'Red%'
For Pandas, I googled a bit but only found partial solutions with == operator, I couldn't find anything for a "like". Then I have to collect the row indexes in a list, the result would be like [2, 3].
Can someone help me? Thanks!
