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Probability Density Function calculator for Binmonial and Gaussian distributions

Project description

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Python module that calculates the probability density 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 relative probability density 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 density 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!

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