Skip to main content

A framework for compiling simple, mapreduce style pipelines over MEDS datasets.

Project description

MEDS Visualizations

Visualization tools for MEDS datasets.

[!WARNING] This is a work in progress. The API and functionality are very likely change as we develop the library.

Installation

pip install MEDS_visualizations

Usage

In a Jupyter notebook, you can load whatever combination of data extractor and plotter you want:

from MEDS_visualizations.extractors import CodeFrequency
from MEDS_visualizations.plotters import Bar
from MEDS_visualizations.visualization import Visualization

CF = CodeFrequency(as_proportions=True)
P = Bar(top_k=10, y_cols=["n_occurrences"])

V = Visualization(extractor=CF, plotter=P)
V.render(data_shards)

In the future, we anticipate

  • Registering extractors and plotters via pypi entry points.
  • Adding the capability to chain together arbitrary extractors and plotters to make a report in a visualization.
  • Adding the capability to apply arbitrary filters or transformations to all data shards used to power a visualization.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

meds_visualizations-0.0.1.tar.gz (13.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

meds_visualizations-0.0.1-py3-none-any.whl (12.6 kB view details)

Uploaded Python 3

File details

Details for the file meds_visualizations-0.0.1.tar.gz.

File metadata

  • Download URL: meds_visualizations-0.0.1.tar.gz
  • Upload date:
  • Size: 13.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for meds_visualizations-0.0.1.tar.gz
Algorithm Hash digest
SHA256 fb09c9ba878f5cb07a24a53ab2cb371aa55da6e223944b5a48241a2637e37aff
MD5 2dab0541126575122568d6f6cbf201ff
BLAKE2b-256 2549a34dba3358f2f865513b6e5a37a0267a5fa7eca4401831a3523f71297dda

See more details on using hashes here.

Provenance

The following attestation bundles were made for meds_visualizations-0.0.1.tar.gz:

Publisher: python-build.yaml on mmcdermott/MEDS_visualizations

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file meds_visualizations-0.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for meds_visualizations-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 eba65a6e3f9a5670fc1d2b880f360e280899e1258767d81e5507befef89bd95a
MD5 2072f60c2fa959bc64abe6f2aa6e946d
BLAKE2b-256 3d64bfaea9c2a5f7bc63a7c5c824e2b1081396e3ff19efbec0c51ae0d6d79832

See more details on using hashes here.

Provenance

The following attestation bundles were made for meds_visualizations-0.0.1-py3-none-any.whl:

Publisher: python-build.yaml on mmcdermott/MEDS_visualizations

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page