DataProfileViewer

Data profile viewer is compatible with Jupyter Notebooks. Supports the metadata format generated by datamart-profiler library.

Install via pip

pip install data-profile-viewer
pip install datamart-profiler

Demo

In Jupyter Notebook:

import DataProfileViewer
data = DataProfileViewer.get_lifeexpectancy_data()
DataProfileViewer.plot_data_summary(data)

Data Profile Exploration

import DataProfileViewer
import datamart_profiler

In a jupyter notebook, load the data

data_path = 'lifeexpectancydata.csv'
metadata = datamart_profiler.process_dataset(data_path, include_sample=True, plots=True)

and then plot it using:

DataProfileViewer.plot_data_summary(metadata)

Refine Data Profiler Results

You might want to correct/refine the type information, or provide additional annotations for the columns. To do so, use the code:

DataProfileViewer.plot_edit_profiler(metadata)

To retrieve the updated metadata, use the code:

updatedMetadata = DataProfileViewer.get_exported_metadata(data_path)