std-distributions 1.1

Gaussian and Binomial distributions

Description:

It's a statistical tool to analyze your dataset using standard distributions such as binomial and gaussian distributions.

Features:

• Calculate mean, standard deviation, probability density function(pdf) and plot graphs for a dataset. You can also add distribution objects from different datasets to calculate the same for the resultant distribution.
• Binomial distribution allows plotting bar graphs for the instance variable and probability density function(pdf). Gaussian distribution uses histograms for the same

Installation:

pip install std_distributions

Note:

Please install matplotlib to plot graphs,(if not already installed) from here.

Example usage

>>>from std_distributions import Binomial, Gaussian
'''
Creating distribution objects
Sytax:
binomial_obj = Binomial(probability,size)
gaussian_obj = Gaussian(mean, standard_deviation) or Gaussian()
'''
>>>b1 = Binomial(0.5,22)
>>>b1
>>>mean = 11.0, standard deviation = 2.345207879911715, p = 0.5, n = 22b2 = Binomial(0.5,44)
>>>b_resultant = b1+b2
>>>b_resultant
>>>mean = 33.0, standard deviation = 4.06201920231798, p = 0.5, n = 66
>>>g1 = G()
>>>g1.read_data_file("numbers.txt")g1.calculate_mean()
>>>1.8181818181818181g1.calculate_stdev()
>>>1.8340219092574557