Skip to main content

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


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)

Uploaded Python 3

Supported by

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