The sort_index method does not seem to work properly if the dataframe was created with concat. See this example:
>>> df = pd.DataFrame(index=['a', 'b']) >>> pd.concat([df, df], keys=[0.8, 0.5]).sort_index() Empty DataFrame Columns: [] Index: [(0.8, a), (0.8, b), (0.5, a), (0.5, b)]
The 0.5 tuples should come before the 0.8 ones. Everything works fine if I create the multi-index from a product:
>>> pd.DataFrame(index=pd.MultiIndex.from_product([[0.8, 0.5], ['a', 'b']])) Empty DataFrame Columns: [] Index: [(0.8, a), (0.8, b), (0.5, a), (0.5, b)] >>> pd.DataFrame(index=pd.MultiIndex.from_product([[0.8, 0.5], ['a', 'b']])).sort_index() Empty DataFrame Columns: [] Index: [(0.5, a), (0.5, b), (0.8, a), (0.8, b)]
I'm on pandas version 0.18.1.
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