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Toptal’s GitHub Organization Hijacked: 10 Malicious Packages Published
Threat actors hijacked Toptal’s GitHub org, publishing npm packages with malicious payloads that steal tokens and attempt to wipe victim systems.
Data Profile Viewer tool. Enables the exploration of data profile in Jupyter Notebooks
Data profile viewer is compatible with Jupyter Notebooks. Supports the metadata format generated by datamart-profiler library.
pip install data-profile-viewer
pip install datamart-profiler
In Jupyter Notebook:
import DataProfileViewer
data = DataProfileViewer.get_lifeexpectancy_data()
DataProfileViewer.plot_data_summary(data)
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)
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)
FAQs
Data Profile Viewer tool. Enables the exploration of data profile in Jupyter Notebooks
We found that data-profile-viewer demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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