A small package for statistical distributions
Project description
minimal-stats
This is a simple python package for statistical distributions. Currently this package calcuates Binomial and Gaussian distribution.
Installation
pip install minimal-stats
Gaussian Distribution
We can directly provide the mean and standard deviation of data (or read data from a file) and add two gaussain distribution.
>>> from distributions import Gaussian
>>> g1 = Gaussian(180, 34)
>>> g1
g = Gaussian(mean=180, stdev=34)
>> str(g1)
'mean 180, standard deviation 34'
>>> g2 = Gaussian(180, 34)
>>> g1 + g2
g = Gaussian(mean=360, stdev=48.08326112068523)
Here, we read data from a file, calculate mean, standard deviation and probability density function of gaussian distribution and then see graphical output
>>> from distributions import Gaussian
>>> g = Gaussian()
>>> g.read_data_file(r'\tests\input\numbers.txt')
>>> g.calculate_mean()
78.0909090909091
>>> g.calculate_stdev()
92.87459776004906
>>> g.pdf(5)
0.0031515485379333356
>>> g.plot_histogram_pdf()
Binomial Distribution
We can directly provide the n and p of data (or read from file as before) and calculate mean, standard deviation and probability mass function of binomial distribution.
>>> from distributions import Binomial
>>> b = Binomial(0.15, 60)
>>> b
b = Binomial(p=0.15, n=60)
>>> b.calculate_mean()
9.0
>>> b.calculate_stdev()
2.765863337187866
>>> b.pmf(7)
0.11985659270959788
>>> a = Binomial(0.15, 50)
>>> a + b
b = Binomial(p=0.15, n=110)
Here, we read data from a file, `b.replace_stats_with_data()calculate mean, standard deviation, n and p of Binomial distribution and then we plot bar graph of pmf.
>>> from distributions import Binomial
>>> b.read_data_file(r'\tests\input\numbers_binomial.txt')
>>> b.replace_stats_with_data()
>>> str(b)
'mean 8.0, standard deviation 1.7541160386140584, p 0.6153846153846154, n 13'
>>> b.plot_bar_pmf()
Contribution
We appreciate feedback and contribution to this repo! Before you get started, please see the following:
License
This project is licensed under the MIT License - see the LICENSE file for details
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