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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

Install libraries necessary for the project

pip install juan-stats

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 and add other distributions you may like!

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