Probability plot missing data when using 'prob' option
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Assessment
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Newbie friendliness
- 45/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- matplotlib, python
- Domain
- data-visualization
Research direction
Start by running the provided Python example in a Jupyter notebook with mpl-probscale 0.2.5, comparing the prob and qq plots and their default y-limits. Trace the plotting path used by probplot for plottype='prob'; done means all 100 generated points are visible without manually widening the y-axis limits.
Written by the indexing model from the issue text.
Description
- Python version: 3.7.6
- numpy version: 1.19.2
- matplotlib version: 3.3.2
- mpl-probscale version: 0.2.5
- Operating System: Windows 10
Running in jupyter notebook.
Description
I generated 100 data points (norm.rvs) and plotted the results using probscale. I've got two plots -- one uses 'prob' and the other uses 'qq' for the y-axis. The plot that uses qq shows all the data, while the plot that uses prob does not show all the data.
What I Did
fig, (ax1, ax2) = pyplot.subplots(figsize=(12,6), ncols=2, sharex=False)
common_opts = dict(
probax='y',
datascale='linear',
datalabel='',
scatter_kws=dict(marker='o', linestyle='none')
)
df2 = norm.rvs(0,1,size=100)
fig = probscale.probplot(df2, ax=ax1, plottype='prob', bestfit=False, problabel='Probability', color='xkcd:ocean green', **common_opts)
fig = probscale.probplot(df2, ax=ax2, plottype='qq', bestfit=False, problabel='Standard Normal Quantiles', color='xkcd:blue gray', **common_opts)
What else?
If I set the y limits for the 'prob' case to something wider than the defaults, I can see the data points that were being left out.
Thanks,
Joe
- Dominant language
- Python
- Stars
- 40
- Forks
- 11
- PR merge metrics
- No merged PRs in 30d
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