Comments (1)
This was the only parameter that was not adjustable. I also changed that now.
The bar_properties can be set based on all known properties
from distfit import distfit
import numpy as np
X = np.random.normal(0, 2, 10000)
dfit = distfit()
dfit.fit_transform(X)
dfit.plot(bar_properties={'width':0.1})
update to the latest version with: pip install -U distfit
from distfit.
Related Issues (20)
- plot_summary throws error HOT 2
- extend __init__.py descriptions HOT 3
- Help needed to interpret loc and scale HOT 2
- Boostrapping bug - The data contains non-finite values HOT 2
- Bug(?): lognorm distribution with negative loc parameter HOT 2
- Feature request: parallel execution when fitting multiple distributions HOT 3
- Quantile Bootstrap to avoid computationally expensive simple Bootstrap HOT 1
- plot freeze HOT 8
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- My code bog down on drawing pdf if best fit distribution is T distribution HOT 6
- More theoretical distributions can be added, such as zero truncated and zero modified theoretical distributions HOT 3
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- Incorporate numba with scipy.special and numba-stats HOT 4
- module 'scipy.stats' has no attribute 'gilbrat' HOT 4
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from distfit.