Numerai Reports
Collection of reports about the numer.ai machine learning competition.
This library was created to provide some reports and statistics about the competition, like round summaries and payout summaries, but also tools to analyze one's model performance. For now, all reports are pure numeric reports.
All information is retrieved via numerai's API and converted to pandas
DataFrames, to make it easy to work with. This allows to create your own
reports on top. numerai_reports also caches API results to disk to limit the
amount of request and to speed-up report generation.
If you encounter a problem or have suggestions, feel free to open an issue.
Installation
pip install --upgrade numerai_reports
Usage Example
from numerai_reports import reports
print(reports.medals_leaderboard())
print(reports.medals_leaderboard(orderby="gold"))
print(reports.payouts(["uuazed", "uuazed2"]))
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file numerai_reports-0.5.4.tar.gz.
File metadata
- Download URL: numerai_reports-0.5.4.tar.gz
- Upload date:
- Size: 7.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
36f0ad4ef6c9f8dbcd4aa85307238f85ddfd963454ffcd42bd33910c4d7528a0
|
|
| MD5 |
fcc6da064fadd7244b613ee3253b67fb
|
|
| BLAKE2b-256 |
cd2ded713778bea2211729515e0cec31c37832d28c8ebb91ffc42fd906a3554b
|
File details
Details for the file numerai_reports-0.5.4-py3-none-any.whl.
File metadata
- Download URL: numerai_reports-0.5.4-py3-none-any.whl
- Upload date:
- Size: 9.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5b502b9aa12e0b6563e4bde0a80e8bcd29866aa09eae4fd3b69e3b8b56ae6f3c
|
|
| MD5 |
e496e99ed40b058c17960b617ecf3a2b
|
|
| BLAKE2b-256 |
381368a6db6791b64d371a3d2131df2f535340f02fe33f8a17d1bc7c60800131
|
