Using pandas categorical as index leads to max recursion depth error

[twiecki]

Described in #2380

Not sure where the error is from (probably theano somewhere) or if we can catch it. In any case, the work-around is easy: convert the index to ints.

[MarcoGorelli]

@twiecki do you have a reproducible example for this?

[michaelosthege]

Closing because there's no MRE here or in the other thread.

If someone runs into this issue with the latest version, please reopen it and provide a minimum reproducible example that we can make into a test case.

[ivar-rummelhoff]

Please reopen this issue. The problem still exists in PyMC 5.8.1. Here is a small example:

import pymc as pm
import pandas as pd
with pm.Model():
    indices = ['a', 'b', 'c']
    df = pd.DataFrame([1, 2, 3], index=indices, columns=['n'])
    n = pm.ConstantData('n', df.n)
    print(n[indices])

Result: RecursionError: maximum recursion depth exceeded in comparison
Replacing ConstantData with MutableData makes no difference.

[wd60622]

This can also be reproduced with

import pytensor.tensor as pt

x = pt.as_tensor_variable([1.0, 2.0])

# RecursionError
x["a"]
x[["a", "b"]]

So it seems like a pytensor item

[ricardoV94]

Why would strings work as indexes?

[wd60622]

Why would strings work as indexes?

good question. Pandas supports so maybe it could be something someone does by mistake

x = pd.Series([1, 2], index=["a", "b"])
x["a"] # 1

[ivar-rummelhoff]

If PyMC does not support this, then that is what the error message should say. I ran into this issue with data from a relational database with string primary key; but I find Pandas (especially in combination with PyMC) so confusing that I have gone back to using NumPy arrays.

[ricardoV94]

Right yes we can try to have a better message.

PyMC can't really use pandas objects other than converting then to numpy arrays.

[ricardoV94]

Closing as stale, feel free to reopen if still relevant

Btw, the error message if desired, should be implemented in PyTensor