Heroku app to explore boardgame data

Related tags

Third-party APIs Wrappers boardgame
Overview

A Dashboard for the Board Game Geeks among us

Link to Application

As many Board Game Geeks like myself track the scores of board game matches I decided to create an application allowing for the exploration of this data. Moreover, it felt like a nice opportunity to see how much information can be extracted from relatively simple data.

As a Data Scientist and self-proclaimed Board Game Nerd I obviously made sure to write down the results of every board game I played. The data in the application is currently my own, but will be extended to include those of others.


API stability API stability API stability

The Application

🎲 The Application

This application is a Streamlit dashboard hosted on Heroku that can be used to explore the results from board game matches that I tracked over the last year.

There are currently four pages available in the application:

  • ♟ General Statistics ♟
    • This gives a general overview of the data including frequency of games over time, most games played in a day, and longest break between games.
  • ♟ Player Statistics ♟
    • As you play with other people it would be interesting to see how they performed. This page allows you to see, per player, an overview of their performance across games.
    • This also includes a one-sample Wilcoxon signed-rank test to test if a player performs significantly better/worse than the average for one board game.
  • ♟ Head to Head ♟
    • I typically play two-player games with my wife and thought it would be nice to include a head to head page. This page describes who is the better of two players between and within games.
  • ♟ Explore Games ♟
    • This page serves to show statistics per game, like its distribution of scores, frequency of matches and best/worst players.
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Comments
  • Bump numpy from 1.16.4 to 1.22.0

    Bump numpy from 1.16.4 to 1.22.0

    Bumps numpy from 1.16.4 to 1.22.0.

    Release notes

    Sourced from numpy's releases.

    v1.22.0

    NumPy 1.22.0 Release Notes

    NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

    • Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
    • A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
    • NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
    • New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
    • A new configurable allocator for use by downstream projects.

    These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

    The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

    Expired deprecations

    Deprecated numeric style dtype strings have been removed

    Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

    (gh-19539)

    Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

    numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

    (gh-19615)

    ... (truncated)

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Owner
Maarten Grootendorst
Data Scientist | Psychologist
Maarten Grootendorst
GitHub https://bgexploration.herokuapp.com/
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