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### Description
If `x` is Categorical and `y` is Utf8/Categorical, support `y.cast(x.dtype)` to explicitly give `y` the same physical encoding as `x`.
(Or a "compatible" encoding if `y` has values…
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Requirement: Convert between iris cubes/coordinates and 'r' data types.
https://github.com/cpelley/iris/tree/rpy2_interface
Background:
http://www.statmethods.net/input/datatypes.html
http://en.wikib…
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Currently demoparser doesn't support querying of the weapon aimpunch angle/velocity properties. I suspect because they are vec3's this makes them quite annoying to deal with? I managed to implement th…
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### What happened?
The first equation should be only a function of X1 and X2.
To reproduce the bug, simply run the `bug()` function. Maybe I am doing something wrong.
```julia
using DataFrames
…
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Dataframes can be easily merged using `pd.merge()`; on the other hand, merge metadata is a pain. It would be great if it would be possible to have a `pyreadstat.merge_sav()` method with the same param…
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When performing join on two large dataframes (each with only a 2 or 3 columns, but 10s to 100s of millions of rows, and `allow_duplication=True`), how do I get Vaex to use less memory? For some joins …
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getting a Julia Tables.jl compatible object from a `pandas` DataFrame is very convenient and I appreciate the functionality. I would love to also see a similar ability for `polars` DataFrames !
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Current behaviour is to run `df.replace({True: 1, False: 0})` on all DataFrames passed, this can have quite a noticeable performance impact on large dataframes.
For example, on a 1.25M row, 8 colum…
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### Checks
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pypi.org/project/polars/) of Polars.
### Re…
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## Polars Python code
```python
import polars as pl
df = pl.DataFrame({
'DateTime': [
'2018-02-01 00:00:00', '2018-02-02 00:00:00',
'2018-02-03 00:00:00', '2018-02-04 00:…