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Data Profile Viewer tool. Enables the exploration of data profile in Jupyter Notebooks

Project description

DataProfileViewer

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

Data summary viewer

Refine data profiler results viewer

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)

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