For example, if I had a dataframe that looks like
| A | B |
|---|---|
| 1 | 8 |
| 4 | 9 |
| 2 | 5 |
| 6 | 2 |
Is there a easier way to sort the two rows where Col-A is in ascending order and B in descending order and any row that B cannot be ordered in descending be dropped? The second row should be dropped because 9 is greater than 5.
I am expecting a table that looks like
| A | B |
|---|---|
| 1 | 8 |
| 2 | 5 |
| 6 | 2 |
>Solution :
You can sort_values, then compute a cummin, drop the rows that violate the cummin:
tmp = df.sort_values(['A','B'], ascending=[True, False])
m = tmp['B'].le(tmp['B'].cummin())
out = tmp[m]
# or to keep the original DataFrame
out = df.loc[m[m].index]
Output:
A B
0 1 8
2 2 5
3 6 2