samplingsimulatorpy 0.1.0

This is a sampling simulator

samplingsimulatorpy

samplingsimulatorpy is a Python package intended to assist those teaching or learning basic statistical inference.

Authors

Name	GitHub
Holly Williams	hwilliams10
Lise Braaten	lisebraaten
Tao Guo	tguo9
Yue (Alex) Jiang	YueJiangMDSV

Overview

This package allows users to generate virtual populations which can be sampled from in order to compare and contrast sample vs sampling distributions for different sample sizes. The package also allows users to sample from the generated virtual population (or any other population), plot the distributions, and view summaries for the parameters of interest.

Installation:

pip install -i https://test.pypi.org/simple/ samplingsimulatorpy

Function Descriptions

• generate_virtual_pop creates a virtual population.
  • Inputs : distribution function (i.e. np.random.lognormal, np.random.binomial, etc), the parameters required by the distribution function, and the size of the population.
  • Outputs: the virtual population as a tibble
• draw_samples generates samples of different sizes
  • Inputs : population to sample from, the sample size, and the number of samples
  • Outputs: returns a tibble with the sample number in one column and value in a second column.
• plot_sample_hist creates sample distributions for different sample sizes.
  • Inputs : population to sample from, the samples to plot, and a vector of the sample sizes
  • Outputs: returns a grid of sample distribution plots
• plot_sampling_dist creates sampling distributions for different sample sizes.
  • Inputs : population to sample from, the samples to plot, and a vector of the sample sizes
  • Outputs: returns a grid of sampling distribution plots
• stat_summary: returns a summary of the statistical parameters of interest
  • Inputs: population, samples, parameter(s) of interest
  • Outputs: summary tibble

How do these fit into the Python ecosystem?

To the best of our knowledge, there is currently no existing Python package with the specific functionality to create virtual populations and make the specific sample and sampling distributions described above. We do make use of many existing Python packages and expand on them to make very specific functions. These include:

• scipy.stats to get distribution functions
• np.random to generate random samples
• Altair to create plots

Python pandas already includes some summary statistics functions such as .describe(), however our package will be more customizable. Our summary will only include the statistical parameters of interest and will provide a comparison between the sample, sampling, and true population parameters.

Dependencies

• python = "^3.7"
• pandas = "^1.0.1"
• numpy = "^1.18.1"
• altair = "^4.0.1"

Usage

generate_virtual_pop

from samplingsimulatorpy import generate_virtual_pop
generate_virtual_pop(size, distribution_func, *para)

Arguments:

• size: The number of samples
• distribution_func: The distribution that we are generating samples from
• *para: The arguments required for the distribution function

Example:

pop = generate_virtual_pop(100, np.random.normal, 0, 1)

draw_samples

from samplingsimulatorpy import draw_samples
draw_samples(pop, reps, n_s)

Arguments:

• pop the virtual population as a data frame
• reps the number of replication for each sample size as an integer value
• n_s the sample size for each one of the samples as a list

Example:

samples = draw_samples(pop, 3, [5, 10, 15, 20])

plot_sample_hist

from samplingsimulatorpy import plot_sample_hist
plot_sample_hist(pop, samples)

Arguments:

• pop the virtual population as a data frame
• samples the samples as a data frame

Example:

plot_sample_hist(samples)

plot_sampling_hist

from samplingsimulatorpy import plot_sampling_hist
plot_sampling_hist(pop, samples)

Arguments:

• samples the samples as a data frame

Example:

plot_sampling_hist(samples)

stat_summary

from samplingsimulatorpy import stat_summary
plot_sampling_hist(pop, samples, parameter)

Arguments

• population The virtual population
• samples The drawed samples
• parameter The parameter(s) of interest

Example

stat_summary(pop, samples, ['np.mean', 'np.std'])

Example Usage Scenario

from samplingsimulatorpy import generate_virtual_pop,
                                draw_samples,
                                plot_sample_dist,
                                plot_sampling_dist,
                                stat_summary
# create virtual population
pop = generate_virtual_pop(100, np.random.normal, 0, 1)
# take samples
samples = draw_samples(pop, 3, [10, 20])
# plot sample histogram
plot_sample_hist(pop, samples)

# plot sampling distribution
plot_sampling_hist(samples)

# compare mean and standard deviation
stat_summary(pop, samples, ['np.mean', 'np.std'])

Documentation

The official documentation is hosted on Read the Docs: https://samplingsimulatorpy.readthedocs.io/en/latest/

Credits

This package was created with Cookiecutter and the UBC-MDS/cookiecutter-ubc-mds project template, modified from the pyOpenSci/cookiecutter-pyopensci project template and the audreyr/cookiecutter-pypackage.