Zach Barry
Zach Barry
In notebook 4: Is: ``` # Compare for yourself that those are the only triangles that node 3 is involved in. neighbors3 = G.neighbors(3) neighbors3.append(3) nx.draw(G.subgraph(neighbors3), with_labels=True) ``` Should be:...
It would be nice to be able to add functionality to the Pandas `GroupBy` objects: `GroupBy`, `DataFrameGroupBy`, `SeriesGroupBy`. There's no convenient accessor interface to do this, but maybe there's a...
Right now, we're copying entire dataframes to avoid mutating the original in a pyjanitor function. This of course can come with big computational costs depending on the size of the...
https://pyjanitor.readthedocs.io/reference/index.html `janitor.[biology,chemistry,finance]` are.
See: https://stackoverflow.com/questions/23668427/pandas-three-way-joining-multiple-dataframes-on-columns Most of the methods proposed are something like a `.merge().merge().merge` chaining. This seems like a pretty computationally suboptimal way of doing things (as far as I can tell)....
When you have for example a dataframe of classes of object on the topmost level, and on the second level, (x,y) coordinates of that object. It's helpful to keep this...
Like mypy? @ericmjl, @szuckerman
Currently, dfs have to be passed as in `unionize_dataframe_categories(*dfs)` or `unionize_dataframe_categories(df1, df2, df3)`. If `dfs` happens to be a list / tuple, detect this and use it instead of erroring.
XArray supports the [Sparse](https://github.com/pydata/sparse) package but doesn't expose the functions to convert to/from sparse objects. These functions could be nicely packaged in pyjanitor to do so: ```python import sparse @register_xarray_dataarray_method...
Potential candidates include (but would be in no way limited to): * xarray * vaex * Dask The idea here is that data cleaning and higher-level functions to manipulate data...