Introducing “Lux” for faster Data exploration

mediumThis post was originally published by Saurav Anand at Medium [AI]

Image for post
Photo by William Iven on Unsplash

“Exploratory data analysis is an attitude, a state of flexibility, a willingness to look for those things that we believe are not there, as well as those that we believe to be there.” — John Tukey

Background

Introduction

Image for post

Getting Started

import lux
import pandas as pd
df = pd.read_csv("college.csv")
df
Image for post

Recommendations based on user intent

df.intent = ["AverageCost","SATAverage"]
df
Image for post
Image for post
Image for post
Image for post

Programmatic access of exported visualization objects

Image for post

On-demand visualizations with the help of automatic encoding

from lux.vis.Vis import Vis
Vis(["Region=New England","MedianEarnings"],df)
Image for post

Powerful language for working with collections of visualizations

from lux.vis.VisList import VisList
VisList(["Region=?","AverageCost"],df)
Image for post

Installation

pip install lux-api
jupyter nbextension install --py luxwidget
jupyter nbextension enable --py luxwidget

Note

References :

Spread the word

This post was originally published by Saurav Anand at Medium [AI]

Related posts