Issue with PP-plot and different distributions
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 28/100
- Issue type
- Bug
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- matplotlib, python
- Domain
- data-visualization
Research direction
Start with the probscale.probplot call shown in the issue and compare the two dist arguments used for the PP-plots. Determine whether identical plots are expected for these distributions; completion would require documenting the behavior or resolving it if it is incorrect.
Written by the indexing model from the issue text.
Description
- Python version: Python 3.6.8
- numpy version: 1.14.3
- matplotlib version: 2.0.2
- mpl-probscale version: 0.2.3
- Operating System: MacOS Mojave 10.14.3
Description
I tried modifying the examples from the documentation and created two PP-plots: one using Standard Normal Distribution as the theoretical distribution, another one using N(100, 5). And both plots look exactly the same (this is not true for QQ-plots). Am I missing something?
What I Did
import warnings
warnings.simplefilter('ignore')
import numpy
from matplotlib import pyplot
import seaborn
from scipy import stats
import probscale
clear_bkgd = {'axes.facecolor':'none', 'figure.facecolor':'none'}
seaborn.set(style='ticks', context='talk', color_codes=True, rc=clear_bkgd)
# load up some example data from the seaborn package
tips = seaborn.load_dataset("tips")
%matplotlib inline
%config InlineBackend.figure_format ='retina'
common_opts = dict(
plottype='pp',
probax='x',
datascale='log',
datalabel='Total Bill (USD)',
scatter_kws=dict(marker='+', linestyle='none', mew=1)
)
norm = stats.norm(100, 5)
fig, (ax1, ax2) = pyplot.subplots(figsize=(10, 6), ncols=2, sharex=True)
fig = probscale.probplot(tips['total_bill'], ax=ax1, dist=norm,
problabel='N(100, 5) Probabilities', **common_opts)
fig = probscale.probplot(tips['total_bill'], ax=ax2, dist=None,
problabel='Standard Normal Probabilities', **common_opts)
seaborn.despine()
- Dominant language
- Python
- Stars
- 40
- Forks
- 11
- PR merge metrics
- No merged PRs in 30d
Contributor guide
First steps
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