The probplotlib from kunal-bhar

Probability Distributions for Python

The Statistical Void

Stats can get tricky in the transition from plotting fun graphs to advanced algebraic equations. A classic example is the given sum:

1.0e14 + 1.0 - 1.0e14

The actual result is 1.0 but in double precision, this will result in 0.0. While in this example the failure is quite obvious, it can get a lot trickier than that. Instances like these hinder the community from exploring the inferential potential of complex entities.

p=Gaussian(a,b)
q=Gaussian(x,y)
p+q

This snippet would be close to useless as python addition doesn't isn't attributed for higher-level declarables such as Gaussian variables. probplotlib provides simple solutions for probability distributions; posing a highly-optimized alternative to numpy and math, in a niche that is scarce in options.

Usage

probplotlib has the following operative methods:

+: uses Dunder Methods for facilitating dist-additions.
calculate_mean(): returns the mean of a distribution.

gaussianex = Gaussian()
calculate_mean(gaussianx)

calculate_stdev(): returns the standard deviation of a distribution.

binomialex = Binomial()
calculate_stdev(binomialex)

read_dataset(): reads an external .txt dataset directly as a distribution.

gaussianex.read_dataset('values.txt')
binomialex.read_dataset('values.txt')

params(): retrieves the identity parameters of an imported dataset.

gaussianex.params()
binomialex.params()

pdf(): returns the probability density function at a given point.

pdf(gaussianex, 2)

functions unique to Gaussian Distributions:

plot_histogram(): uses matplotlib to display a histogram of the Gaussian Distribution.

gaussianex.plot_histogram()

plot_histogram_pdf(): uses matplotlib to display a co-relative plot along with the Gaussian probability density function.

gaussianex.plot_histogram_pdf()

functions unique to Binomial Distributions:

plot_bar(): uses matplotlib to display a bar graph of the Binomial Distribution.

binomialex.plot_bar()

plot_bar_pdf(): uses matplotlib to display a co-relative plot along with the Binomial probability density function.

binomialex.plot_bar_pdf()

Data Visualization

probplotlib therefore allows you to analyze raw numerical data graphically in minimial lines of code. The example below makes for better understanding.