Skip to main content

Welcome to PyCorruptor

A Python Toolbox for Data Corruption

PyPI

In data analysis and modeling, sometimes we may need to corrupt the original data to achieve our goal, for instance, evaluating models' ability to reconstruct corrupted data or assessing the model's performance on only partially-observed data. PyCorruptor is such a tool to help you corrupt your data, which provides several patterns to create missing values in the given data.

Metadata

Release files for pycorruptor 0.0.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for pycorruptor 0.0.4
File Interpreter ABI Platform
pycorruptor-0.0.4-py3-none-any.whl Python 3 none any Details

Release files / pycorruptor-0.0.4-py3-none-any.whl

Download URL pycorruptor-0.0.4-py3-none-any.whl
Size 17.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
eb92edc8f470c6dc90aa78f76d17b1d7ff068b42e0a8b0c84be7dd6cac277f1f
BLAKE2b-256 checksum
How to use checksums
c2c5fa1f299db64bd4fb6d2048c16860a6068c311c2af344ba2b554fad5d6790
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.0 CPython/3.7.4

Release history Release notifications | RSS feed

This release

0.0.4 This release

1 release file

0.0.3

1 release file

0.0.2

1 release file

0.0.1

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page