nteract/dx

Data Explorer for Python

dx

A Pythonic Data Explorer.

Install

For Python 3.8+:

pip install dx

Usage

The dx library contains a simple helper function also called dx.

from dx import dx

dx() takes one positional argument, a dataframe.

dx(dataframe)

The dx(dataframe) function will display the dataframe in data explorer mode:

Today, a Pandas DataFrame may be passed. In the future, other dataframe types may be supported.

Example

import pandas as pd
from dx import dx


# Get happiness data and create a pandas dataframe
df = pd.read_csv('examples/data/2019.csv')

# Open data explorer with the happiness dataframe
dx(df)

If you only wish to display a certain number of rows from the dataframe, use a context and specify the max rows (if set to None, all rows are used):

# To use the first 13 rows for visualization with dx
with pd.option_context('display.max_rows', 13):
  dx(df)

FAQ

Q: What about Spark?

A: Spark support would be highly welcome!

See improved-spark-viz for the current effort. There's a format that pandas handles for us that we could create in spark land.

Develop

git clone https://github.com/nteract/dx
cd dx
pip install -e .

We currently install jupyter and jupyter_on_nteract packages for ease of running examples.

To run nteract on jupyter:

jupyter nteract

Code of Conduct

We follow the nteract.io code of conduct.

LICENSE

See LICENSE.md.