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janpipek / physt

Python histogram library - histograms as updateable, fully semantic objects with visualization tools. [P]ython [HYST]ograms.
MIT License
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2d-histograms heatmap histogram plotting python visualization

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physt Physt logo

P(i/y)thon h(i/y)stograms. Inspired (and based on) numpy.histogram, but designed for humans(TM) on steroids(TM).

Create rich histogram objects from numpy or dask arrays, from pandas and polars series/dataframes, from xarray datasets and a few more types of objects. Manipulate them with ease, plot them with matplotlib, vega or plotly.

In short, whatever you want to do with histograms, physt aims to be on your side.

ReadTheDocs Join the chat at https://gitter.im/physt/Lobby PyPI downloads PyPI version Anaconda-Server Badge Anaconda-Server Badge Code style: black

See it in action

With uv installed, you can run the following command without needing to install anything to see some examples in action:

uv run --with "physt[terminal]>=0.8.3" -m physt.examples

Simple example

from physt import h1

# Create the sample
heights = [160, 155, 156, 198, 177, 168, 191, 183, 184, 179, 178, 172, 173, 175,
           172, 177, 176, 175, 174, 173, 174, 175, 177, 169, 168, 164, 175, 188,
           178, 174, 173, 181, 185, 166, 162, 163, 171, 165, 180, 189, 166, 163,
           172, 173, 174, 183, 184, 161, 162, 168, 169, 174, 176, 170, 169, 165]

hist = h1(heights, 10)           # <--- get the histogram data
hist << 190                      # <--- add a forgotten value
hist.plot()                      # <--- and plot it

Heights plot

2D example

from physt import h2
import seaborn as sns

iris = sns.load_dataset('iris')
iris_hist = h2(iris["sepal_length"], iris["sepal_width"], "pretty", bin_count=[12, 7], name="Iris")
iris_hist.plot(show_zero=False, cmap="gray_r", show_values=True);

Iris 2D plot

3D directional example

import numpy as np
from physt import special_histograms

# Generate some sample data
data = np.empty((1000, 3))
data[:,0] = np.random.normal(0, 1, 1000)
data[:,1] = np.random.normal(0, 1.3, 1000)
data[:,2] = np.random.normal(1, .6, 1000)

# Get histogram data (in spherical coordinates)
h = special_histograms.spherical(data)

# And plot its projection on a globe
h.projection("theta", "phi").plot.globe_map(density=True, figsize=(7, 7), cmap="rainbow")

Directional 3D plot

See more in docstring's and notebooks:

Installation

Using pip:

pip install physt

or conda:

conda install -c janpipek physt

Features

Implemented

Planned

Not planned

Rationale (for both): physt is dumb, but precise.

Dependencies

Publicity

Talk at PyData Berlin 2018:

Contribution

I am looking for anyone interested in using / developing physt. You can contribute by reporting errors, implementing missing features and suggest new one.

Thanks to:

Patches:

Alternatives and inspirations