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A high-performance implementation of Wilkinson formulas for Python.

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Current it is difficult to get parts of the formula and what are the data.frame variables (i.e. the column names). It would be useful to add some facilities to enable...

The *dataframe* output of a model matrix has column names [Intercept, b[T.a],...] when one specifies `output = sparse`, the column identifiers are not available... ( the output is a regular...

documentation

Another thing I was considering is wheater we are able to use formulaic for incremental training of some models. Let's imagine we have a dataset that has the categorical variable...

documentation

I think there is a discrepancy in the output of rhs: 1. formula "y~x" -> `rhs = "x+1"` 2. formula "y~x-1" -> `rhs = "x"` 3. formula "y~x+0" -> `rhs...

enhancement

Hi Matthew. This looks like a very promising package. I'm hoping to use this instead of `patsy` as soon as the API has matured. I'm therefore doing some experimentation with...

documentation

Preamble: I have a hard time understanding some of the core code parts. #### 1. What is the reason to add metadata to the data container? ```python import pandas as...

documentation
enhancement

A model spec does not keep the column type. Example: ``` import pandas as pd from formulaic import model_matrix df1 = pd.DataFrame({ 'a': ['A', 'B', 'C'], }) df2 = pd.DataFrame({...

question

What about a possible migration of formulaic under some community space like pydata (like patsy) or statsmodels (like statsmodels)? This is just a suggestion with the purpose of a broader...

The current documentation is incomplete and full of typos. Finish it!

In some cases, particularly in production code, it is nice to have a safe mode that avoids using `eval`, at the expense of some functionality. This issue is here so...

enhancement
question