Skip to main content

PyPi Binder Lite

Profile your Pandas Dataframes! Autoprofiler will automatically visualize your Pandas dataframes after every execution, no extra code necessary.

Autoprofiler allows you to spend less time specifying charts and more time interacting with your data by automatically showing you profiling information like:

  • Distribution of each column
  • Sample values
  • Summary statistics

Updates profiles as your data updates

screenshot of Autoprofiler

Autoprofiler reads your current Jupyter notebook and produces profiles for the Pandas Dataframes in your memory as they change.

https://user-images.githubusercontent.com/13400543/199877605-ba50f9c8-87e5-46c9-8207-1c6496bb3b18.mov

Install

To instally locally use pip and then open jupyter lab and the extension will be running.

pip install -U digautoprofiler

Please note, AutoProfiler only works in JupyterLab with version > 3.

Try it out

To try out Autoprofiler in a hosted notebook, use one of the options below

Jupyter Lite Binder
Lite Binder

Development Install

For development install instructions, see CONTRIBUTING.md.

If you're having install issues, see TROUBLESHOOTING.md.

Acknowledgements

Big thanks to the Rill Data team! Much of our profiler UI code is adapted from Rill Developer.

Let us know what you think! 📢

We would love to hear your feedback on how you are using AutoProfiler! Please fill out this form or email Will at willepp@cmu.edu.

Download files

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

Source Distribution

digautoprofiler-0.2.6.tar.gz (1.8 MB view details)

Uploaded Source

Built Distribution

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

digautoprofiler-0.2.6-py3-none-any.whl (2.8 MB view details)

Uploaded Python 3

File details

Details for the file digautoprofiler-0.2.6.tar.gz.

File metadata

  • Download URL: digautoprofiler-0.2.6.tar.gz
  • Upload date:
  • Size: 1.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.10.4

File hashes

Hashes for digautoprofiler-0.2.6.tar.gz
Algorithm Hash digest
SHA256 13cfc402c232900a85ee3f7ced343b0bbc9601a1bbe21e5a6bdb47c002347a5e
MD5 04b8f9ff9fd0efb40ab83147a51e9d54
BLAKE2b-256 f62899b4bb9536dfc1a51d0d27646166a5f945cf4b8b6230f5ef4c47d04fee1b

See more details on using hashes here.

File details

Details for the file digautoprofiler-0.2.6-py3-none-any.whl.

File metadata

File hashes

Hashes for digautoprofiler-0.2.6-py3-none-any.whl
Algorithm Hash digest
SHA256 a9abc9058df44c208542eb353c0c53a5cba67a70b1f2673aafe0953f3ca58092
MD5 8eef3d43b69fc7b4c7da75bc73801b1d
BLAKE2b-256 1c1bf672759b42296dcd7cd213c2060bd43bc9cd4d6ce6a572fc95b21f696045

See more details on using hashes here.

Release history Release notifications | RSS feed

3.0.1

2 files

1.0.2

2 files

1.0.1

2 files

1.0.0

2 files

0.2.10

2 files

0.2.9

2 files

0.2.8

2 files

0.2.7

2 files

This release

0.2.6 This release

2 files

0.2.5

2 files

0.2.4

2 files

0.2.3

2 files

0.2.2

2 files

0.2.1

2 files

0.2.0

2 files

0.1.9

2 files

0.1.8

2 files

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