Data Science Toolkit (DST) is a Python library that helps implement data science related project with ease.
Project description
Data Science Toolkit
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
Release history Release notifications | RSS feed
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
Close
Hashes for data-science-toolkit-0.1.64.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6ba9f561dc451a736821301b2237eff378c2228a4ed206aff684810b689fc33c |
|
MD5 | 4619fd1ce0e32a8c698dab245d570176 |
|
BLAKE2b-256 | 32ec00bbd1579fa027fac53fd6e1cfdd776503dd1ed2237f6e32bff07a43c248 |
Close
Hashes for data_science_toolkit-0.1.64-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 461c9becde5b81cd7741bc462fc9d685b5441a33749d50149032a89c45fd8b2d |
|
MD5 | a5319959d13e16d038ae8588870c0a21 |
|
BLAKE2b-256 | 49c2de6973aec0047c0308b7d584cd44b608bdb909002dd26e675542a716493c |