Fantasy-Premier-League
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| Fantasy-Premier-League | datapane | |
|---|---|---|
| 53 | 30 | |
| 1,329 | 1,349 | |
| - | 0.4% | |
| 7.8 | 7.3 | |
| 11 days ago | 6 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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Fantasy-Premier-League
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How to get GW-by-GW stats of an older season from the Vaastav repo?
Hello guys, I am using the FPL historic data in this repository to build a points prediction ML model for my personal use, just as a side project : https://github.com/vaastav/Fantasy-Premier-League
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FPL ML project
I recently got interested in machine learning and completed a few courses on it; I now want to do a project and create an Fpl predictor, which predicts the best players to pick for the next game week. I was wondering if there is any advice one could get, especially regarding which features to look at, as I am entirely new to this space. So far, I've been looking through this dataset on GitHub https://github.com/vaastav/Fantasy-Premier-League trying to predict total points for each gw, but if anyone has any other suggestions or advice, I would really appreciate it :)
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Top Player Value scatter plot over the last 10 games.
A scatterplot of the weighted average of points(y-axis) in the last 10 matches over player valuation(x-axis). Source of data https://github.com/vaastav/Fantasy-Premier-League/tree/d6c561b1b1a38b0426ce978346c44d66c54eb4e1
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No Haaland All Season
https://github.com/vaastav/Fantasy-Premier-League cheers!
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I've made a guide to the FPL API
Great GitHub repository of this by vaastav
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FPL API: Is Detailed Historical Player Data Available?
This is what you are looking for: https://github.com/vaastav/Fantasy-Premier-League
- Historic player form data by goalweek
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Machine learning mode
Regarding the data: Actually I’m already after this phase. I got current season data (players summary and players by GW) by using the FPL API and I got the historical data from vaastav repository on github: https://github.com/vaastav/Fantasy-Premier-League
- Excel Data analysis
- 2021 2022 Fantasy Premier League FPL Player Data by Match
datapane
- Datapane: Build and share data reports in 100% Python
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Polars: Company Formation Announcement
If you're looking for an easy way to build an HTML report using Python, you might find Datapane (https://github.com/datapane/datapane) helpful. I'm one of the people building it! We don't support polars (yet, on the roadmap) but we do support pandas so you can convert to a pandas DataFrame and include your data and any plots, etc.
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JupyterLab 4.0
If you're interested in an easier way to create reports using Python and Plotly/Pandas, you should check out our open-source library, Datapane: https://github.com/datapane/datapane - you can create a standalone, redistributable HTML file in a few lines of Python.
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Evidence – Business Intelligence as Code
You might be interested in what we're hacking on at Datapane (I'm one of the founders): https://github.com/datapane/datapane.
You can create standalone HTML data reports from Python/Jupyter in ~3 lines of code: https://docs.datapane.com/reports/overview/
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Ask HN: Fastest way to turn a Jupyter notebook into a website these days?
You can build web apps from Jupyter using Datapane [0]. I'm one of the founders, so let me know if I can help at all.
You can either export a static site [1] (and host on GH pages or S3), or, if you need backend logic, you can add Python functions [2] and serve on your favourite host (we use Fly).
We have specific Jupyter integration to automatically convert your notebook into an app [3].
[0] https://github.com/datapane/datapane
[1] https://docs.datapane.com/reference/reports/#datapane.proces...
[2] https://docs.datapane.com/apps/overview/
[3] https://docs.datapane.com/reports/jupyter-integration/#conve...
- Datapane – Build full-stack data apps in 100% Python
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Datapane - Build full-stack data apps in 100% Python
Our GitHub is https://github.com/datapane/datapane and you can get started here: https://docs.datapane.com/quickstart/
- Datapane: Build internal analytics products in minutes using Python
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Datapane - Build internal data products in 100% Python
Thanks a lot! Yes, absolutely, a few people have brought this up and working working on removing the header right now. If I can help at all, feel free to reach us on GH Discussions: https://github.com/datapane/datapane/discussions
- Datapane/datapane: Build full-stack data analytics apps in Python
What are some alternatives?
fplscrapR - This package enables those interested in Fantasy Premier League to perform detailed data analysis of the game, using the FPL's JSON API. The fplscrapR functions help R users collect and parse data from the Official Fantasy Premier League website.
streamlit - Streamlit — A faster way to build and share data apps.
FPLbot - A bot made for /r/FantasyPL
dash - Data Apps & Dashboards for Python. No JavaScript Required.
system-design-primer - Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
fantasy-again - A web app that allows you to replay the 2020/21 season of Fantasy Premier League (FPL) in single-player mode.
perspective - A data visualization and analytics component, especially well-suited for large and/or streaming datasets.
fpl - An asynchronous Python wrapper for the Fantasy Premier League API.
superset - Apache Superset is a Data Visualization and Data Exploration Platform
open-fpl - Open-source Fantasy Premier League tools
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!