Skip to main content

Package for calculating and visualising confidence intervals, e.g. for A/B test analysis.

Project description

Spotify Confidence

Status Latest release Python Python

Python library for AB test analysis.

Why use Spotify Confidence?

Spotify Confidence provides convinience wrappers around statsmodel's various functions for computing p-values and confidence intervalls. With Spotify Confidence it's easy to compute several p-values and confidence bounds in one go, e.g. one for each country or for each date. Each function comes in two versions:

  • one that return a pandas dataframe,
  • one that returns a Chartify chart.

Spotify Confidence has support calculating p-values and confidence intervals using Z-statistics, Student's T-statistics (or more exactly Welch's T-test), as well as Chi-squared statistics.

There is also a Bayesian alternative in the BetaBinomial class.

Examples

import spotify_confidence as confidence
import pandas as pd

data = pd.DataFrame(
    {'variation_name': ['treatment1', 'control', 'treatment2', 'treatment3'],
     'success': [50, 40, 10, 20],
     'total': [100, 100, 50, 60]
    }
)

test = confidence.ZTest(
    data,
    numerator_column='success',
    numerator_sum_squares_column=None,
    denominator_column='total',
    categorical_group_columns='variation_name',
    correction_method='bonferroni')
    
test.summary()
test.difference(level_1='control', level_2='treatment1')
test.multiple_difference(level='control', level_as_reference=True)

test.summary_plot().show()
test.difference_plot(level_1='control', level_2='treatment1').show()
test.multiple_difference_plot(level='control', level_as_reference=True).show()

See jupyter notebooks in examples folder for more complete examples.

Installation

Spotify Confidence can be installed via pip:

pip install spotify-confidence

Find the latest release version here

Code of Conduct

This project adheres to the Open Code of Conduct By participating, you are expected to honor this code.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

spotify-confidence-2.3.5.tar.gz (3.6 MB view details)

Uploaded Source

Built Distribution

spotify_confidence-2.3.5-py3-none-any.whl (64.3 kB view details)

Uploaded Python 3

File details

Details for the file spotify-confidence-2.3.5.tar.gz.

File metadata

  • Download URL: spotify-confidence-2.3.5.tar.gz
  • Upload date:
  • Size: 3.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.6.9

File hashes

Hashes for spotify-confidence-2.3.5.tar.gz
Algorithm Hash digest
SHA256 764a25c558fdb2e0bc6ea84c676b359f8f59f8a1d235c6d564e0e5cee2a41908
MD5 17b8304773f5948b2abe512bef40c0d8
BLAKE2b-256 211dc70bd33cbb9c519fcc5d2d75ba02404e064845fff506de5e32b89d8290b8

See more details on using hashes here.

File details

Details for the file spotify_confidence-2.3.5-py3-none-any.whl.

File metadata

  • Download URL: spotify_confidence-2.3.5-py3-none-any.whl
  • Upload date:
  • Size: 64.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.6.9

File hashes

Hashes for spotify_confidence-2.3.5-py3-none-any.whl
Algorithm Hash digest
SHA256 76072f727059de8ddaca0205f3a5edfe3821e2ec0a79a3abd5b592ba9020061f
MD5 4786ba260b9fddc20f9ed3f94b19dcfb
BLAKE2b-256 d6e789c8a1b6b47a23bf84ee00f31e0ea692b25973ddb167d6ad7af1eec89ff3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page