distimate 0.1

Distributions visualized

Distimate - Distributions visualized

Distimate approximates and plots common statistical functions from histograms.

Distimate can aggregate empirical distributions of random variables. The distributions are represented as histograms with user-defined bucket edges. This is especially useful when working with large datasets that can be aggregated to histograms at database level.

import distimate
import matplotlib.pyplot as plt

edges = [0, 1, 2, 5, 10, 15, 20, 50]
values = [291, 10, 143, 190, 155, 60, 90, 34, 27]
dist = distimate.Distribution.from_histogram(edges, values)

plt.title(f"x̃={dist.quantile(0.5):.2f}")
plt.xlim(0, 50)
plt.ylim(0, 1)
plt.plot(dist.cdf.x, dist.cdf.y, label="CDF")
plt.plot(dist.pdf.x, dist.pdf.y, label="PDF")
plt.legend(loc="lower right")

Features:

• Histogram creation and merging
• Probability density function (PDF)
• Cumulative distribution function (CDF or ECDF)
• Quantile (percentile) function
• Pandas integration.

Distimate is hosted at GitHub and it can be installed from PyPI.

Documentation

Distimate documentation from the docs/ directory can be read online at Read the Docs.

License

Copyright 2020 Akamai Technologies, Inc

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

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