dynobo/lmdiag

Python Library providing Diagnostic Plots for Linear Regression

lmdiag's Issues

Markers not visible, when style used...

If a matplotlib style is used, it's possible, that the markers are not shown, e.g. with
plt.style.use('seaborn')

Python 2 compatibility

@dynobo I want to start off by saying that I love this package. Inferential statistics is super easy in R thanks to things like plot.lm, so lmdiag really helps bridge the gap between Python and R! I was hunting down an easy way to do something similar to plot.lm in Python without having to manually build a bunch of the plots, so I was very happy to find this package.

So I found one case in info.py where you used some Python 3-specific string formatting that causes this package to not work for Python 2. If you're only planning on having this be a Python 3 package, I completely respect that, though it would be nice if that were the case to add a note of that in the README. If you are interested in making this package work for Python 2, here is a super quick fix I made in a fork of this package that fixes the issue for Python 2 (note: I haven't done extensive testing based on this fix, I just know it lets the package be imported without raising an error).

Slow for large datasets

Thank you for creating a nice package. It is very handy to install such a functionality with pip.

However, I find this package to be rather slow for large datasets in comparison with the LinearRegDiagnostic class described in the Linear regression diagnostics example of statsmodels. This may indicate some inefficiency of the package.

Example:

df = sm.datasets.get_rdataset("ames", "openintro").data
res = smf.ols("np.log10(price) ~ Q('Overall.Qual') + np.log(area)", df).fit()

lmdiag

%%time
lmdiag.plot(res)

CPU times: user 15.1 s, sys: 215 ms, total: 15.3 s
Wall time: 16.1 s

LinearRegDiagnostic

%%time
LinearRegDiagnostic(res)()

CPU times: user 2.17 s, sys: 125 ms, total: 2.29 s
Wall time: 2.17 s

Estimation results of linearmodels

Thanks for a very useful package. It would be great if lmdiag is extended so that the estimation results of linearmodels can be used as an input, e.g. IV-2SLS and Panel Data.