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.
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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