A dataprocessing package for data preprocess and feature engineering.
Project description
DataLiner - Data processing package for Python
A dataprocessing package for data preprocess and feature engineering.
Please feel free to send pull requests for bug fix, improvements or new preprocessing methods!
Installation
! pip install dataliner
Documentation
https://shallowdf20.github.io/dataliner/preprocessing.html
Quick Start
Train data from Kaggle Titanic is used in this example. https://www.kaggle.com/c/titanic/data
import pandas as pd
from sklearn.pipeline import make_pipeline
import dataliner as dl
df = pd.read_csv('train.csv')
target_col = 'Survived'
X = df.drop(target_col, axis=1)
y = df[target_col]
process = make_pipeline(
dl.DropNoVariance(),
dl.DropHighCardinality(),
dl.BinarizeNaN(),
dl.ImputeNaN(),
dl.TargetMeanEncoding(),
dl.DropHighCorrelation(),
dl.StandardScaling(),
dl.DropLowAUC(),
)
process.fit_transform(X, y)
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 Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
dataliner-1.3.1-py3-none-any.whl
(46.1 kB
view hashes)
Close
Hashes for dataliner-1.3.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | aee8af341086637c413c90ce1ccabb36a211f602ea1a5dd12e455ac5745a8102 |
|
MD5 | 8f58163c0c17d47f66c0f2a563a09044 |
|
BLAKE2b-256 | 629931c927ef36e1f970fdcb4f1b21a40be531e77c2beb040f11af6ff5a8c127 |