Skip to main content

Data Science Toolkit (DST) is a Python library that helps implement data science related project with ease.

Project description

Data Science Toolkit

readthedocs License Reproducible Capsule

Data Science Toolkit (DST) is a Python library that helps implement data science related project with ease.

Simple Demo

from data_science_toolkit.dataframe import DataFrame
from data_science_toolkit.model import Model

data = DataFrame()
data.load_dataset('iris')
y = data.get_column('target')
data.drop_column('target')

# decision tree model
model = Model(data_x=data.get_dataframe(), data_y=y, model_type='dt', training_percent=0.8)

# train the model
model.train()

# get all classification evaluation metrics
model.report()

#get the cross validation
model.cross_validation(5)

Documentation

More information can be found on the DST documentation site.

Contributing

Contrubution and suggestions are welcome via GitHub Pull Requests.

Maintainership

We're actively enhacing the repo with new algorithms.

How to cite

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

data-science-toolkit-0.0.986.tar.gz (37.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

data_science_toolkit-0.0.986-py3-none-any.whl (40.5 kB view details)

Uploaded Python 3

File details

Details for the file data-science-toolkit-0.0.986.tar.gz.

File metadata

  • Download URL: data-science-toolkit-0.0.986.tar.gz
  • Upload date:
  • Size: 37.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/30.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.9 tqdm/4.64.0 importlib-metadata/4.11.3 keyring/23.4.0 rfc3986/1.5.0 colorama/0.4.4 CPython/3.7.3

File hashes

Hashes for data-science-toolkit-0.0.986.tar.gz
Algorithm Hash digest
SHA256 68ef452a654b4570768e1bfd3ad2136571ddb72bf3069d92fe051efea00f0b31
MD5 1ef52d6c05c0d01b35694f544d654e06
BLAKE2b-256 1cb154f029eca43c5c486be492ec1e1ac311ad5aa18fad4d3405469eeb365e0e

See more details on using hashes here.

File details

Details for the file data_science_toolkit-0.0.986-py3-none-any.whl.

File metadata

  • Download URL: data_science_toolkit-0.0.986-py3-none-any.whl
  • Upload date:
  • Size: 40.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/30.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.9 tqdm/4.64.0 importlib-metadata/4.11.3 keyring/23.4.0 rfc3986/1.5.0 colorama/0.4.4 CPython/3.7.3

File hashes

Hashes for data_science_toolkit-0.0.986-py3-none-any.whl
Algorithm Hash digest
SHA256 89b3d48cd3a9754818b3d867b788fe1f545b7db8eadd57330001a9d0ced8108d
MD5 4ac96e9fc8265b63ab4aee77721d0c73
BLAKE2b-256 7b85c8a9af4c3c8649c14a534780a8586a315e0846fea2b366ba12f9853a6167

See more details on using hashes here.

Supported by

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