When working with external data, I often see rows with primary key violations. Currently, I could not easily select all the violating rows. For example, if I have a massive file with some inconsistent data
datecol,valuecol
...
2014-01-01,12
2014-01-01,13
2014-01-02,10
...
In this use case, it would be good if we can do df[df.duplicated('datecol', take_all=True)] to directly get the bad rows
2014-01-01,12
2014-01-01,13
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4