Skip to main content

Python package to create stock related features.

Project description

stockfeat

Python PyPI Version License Coffee Github Forks GitHub Open Issues Project Status Sphinx Downloads Downloads

  • stockfeat is Python package

Installation

  • Install stockfeat from PyPI (recommended). stockfeat is compatible with Python 3.6+ and runs on Linux, MacOS X and Windows.
  • A new environment can be created as following:
conda create -n env_stockfeat python=3.8
conda activate env_stockfeat
pip install stockfeat            # normal install
pip install --upgrade stockfeat # or update if needed
  • Alternatively, you can install from the GitHub source:
# Directly install from github source
pip install -e git://github.com/erdogant/stockfeat.git@0.1.0#egg=master
pip install git+https://github.com/erdogant/stockfeat#egg=master
pip install git+https://github.com/erdogant/stockfeat

# By cloning
git clone https://github.com/erdogant/stockfeat.git
cd stockfeat
pip install -U .

Import stockfeat package

from stockfeat import stockfeat

Example:

sf = stockfeat(col_open='Open', col_close='Close', col_volume='Volume', col_high='High', col_low='Low')
df = sf.download_example()
df = df.resample('D').mean()

# Collect features
X = sf.fit(df)

Citation

Please cite stockfeat in your publications if this is useful for your research. Here is an example BibTeX entry:

@misc{erdogant2020stockfeat,
  title={stockfeat},
  author={Erdogan Taskesen},
  year={2020},
  howpublished={\url{https://github.com/erdogant/stockfeat}},
}

References

Maintainer

  • Erdogan Taskesen, github: erdogant
  • Contributions are welcome.
  • If you wish to buy me a Coffee for this work, it is very appreciated :) Star it if you like it!

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

stockfeat-0.1.0.tar.gz (21.3 kB view details)

Uploaded Source

Built Distribution

stockfeat-0.1.0-py3-none-any.whl (23.7 kB view details)

Uploaded Python 3

File details

Details for the file stockfeat-0.1.0.tar.gz.

File metadata

  • Download URL: stockfeat-0.1.0.tar.gz
  • Upload date:
  • Size: 21.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.24.0 setuptools/50.3.1.post20201107 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.5

File hashes

Hashes for stockfeat-0.1.0.tar.gz
Algorithm Hash digest
SHA256 02908c7f530418b9f7ce7de4f2fe3e4aa6fa63c4cda3eb04f6bfee1851294565
MD5 44bf57f71d33dd2292adf2658de00a08
BLAKE2b-256 33e59680cf5296648f942e184fd21b35760cf7415deb8a56914b8241d3951416

See more details on using hashes here.

File details

Details for the file stockfeat-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: stockfeat-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 23.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.24.0 setuptools/50.3.1.post20201107 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.5

File hashes

Hashes for stockfeat-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 67c2f45dec5543871323346cc39699caad453aaaa37b37614bd532dc56f9e731
MD5 b43b562800d9a1813e78b7aadea66101
BLAKE2b-256 b638dd8a4c0cf4edc15e5ed95c47aa5afb1c11ae00f92abce67431708eae019e

See more details on using hashes here.

Supported by

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