juan-stats 2.1

Python module that calculates the probability density or mass function, along with the median and standard deviation for numerical datasets exhibiting Gaussian or Binomial distributions.

Installation

pip install juan-stats
from juan_stats import *

Demo in Google Colab

Look the package in action here

Features Gaussian Distribution

• Read numerical datasets from a CSV file or a Python list

gaussian_one = Gaussian()
gaussian_one.read_data_file("numbers.csv")

#another option is to read the data from a list
gaussian_one.data = [10,10,10,19,15,15,12,12,2,9,8,8,5] 

• Calculate the mean, standard deviation, and relative probability density at a specific point in a Gaussian distribution

print(gaussian_one.calculate_mean())
print(gaussian_one.calculate_stdev())
print(gaussian_one.pdf(49))

• Plot Histogram of the data or the Normalized histogram along with the probability density function

gaussian_one.plot_histogram()
gaussian_one.plot_histogram_pdf()

Features Binomial Distribution

• Calculate the mean, and standard deviation given some probability p and number of trials n

Binomial(0.4, 25)
#or
Binomial(p=0.4, n=25)

• Read numerical datasets from a CSV file or a Python list. The dataset should be composed of 0 and 1.
• Calculate the mean, standard deviation, and probability mass at a specific point in a Binomial distribution

binomial_one.data = [0,1,0,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1] 
print(binomial_one.calculate_mean())
print(binomial_one.calculate_stdev())
print(binomial_one.pdf(5))

• Plot the probability mass function of the binomial distribution

binomial_one.plot_bar_pdf()

Contributing

Submit a pull request to this Github repository and add other distributions you may like!