Python wrapper for Data Explorer
Project description
A Pythonic Data Explorer.
Install
For Python 3.8+:
pip install dx>=1.0.3
Usage
The dx
library currently enables DEX media type visualization of pandas DataFrames
in two ways:
- individual calls to
dx.display()
- updating the current IPython display formatter for a session
Importing
import dx
With dx.display()
dx.display()
will display a single dataset using the DEX media type. It currently supports:
-
pandas
DataFrame
objectsimport pandas as pd import random df = pd.DataFrame({ 'random_ints': [random.randint(0, 100) for _ in range(500)], 'random_floats': [random.random() for _ in range(500)], }) dx.display(df)
-
tabular data as
dict
orlist
typesdx.display([ [1, 5, 10, 20, 500], [1, 2, 3, 4, 5], [0, 0, 0, 0, 1] ])
-
.csv
or.json
filepaths
With dx.register()
and dx.deregister()
dx
will update the current IPython
display formatters to allow DEX media type visualization of pandas DataFrame
objects for an entire notebook / kernel session instead of the default DataFrame
display output.
Note: this only affects pandas DataFrames; it does not affect the display of
.csv
/.json
file data, ordict
/list
outputs
-
dx.register()
import pandas as pd # enable DEX display outputs from now on dx.register() df = pd.read_csv("examples/sample_data.csv") df
df2 = pd.DataFrame( [ [1, 5, 10, 20, 500], [1, 2, 3, np.nan, 5], [0, 0, 0, np.nan, 1] ], columns=['a', 'b', 'c', 'd', 'e'] ) df2
-
dx.deregister()
df2 = pd.DataFrame( [ [1, 5, 10, 20, 500], [1, 2, 3, np.nan, 5], [0, 0, 0, np.nan, 1] ], columns=['a', 'b', 'c', 'd', 'e'] ) df2
dx.deregister() df2
Develop
git clone https://github.com/noteable-io/dx
cd ./dx
pip install -e .
Code of Conduct
We follow the noteable.io code of conduct.
LICENSE
See LICENSE.md.
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