mathdatech/awesome-python
1
0
Fork 0
mirror of https://github.com/vinta/awesome-python.git synced 2024-11-27 22:11:07 +00:00
Code Issues Packages Projects Releases Wiki Activity

add blaze to Science and Data Analysis section

Browse Source
This commit is contained in:
Vinta 2014-09-19 18:17:38 +08:00
parent 91eb2a2a4a
commit c165252193
1 changed files with 3 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
README.md
View File

@ -802,8 +802,8 @@ A curated list of awesome Python frameworks, libraries and software. Inspired by
* [faker](http://www.joke2k.net/faker/) - A Python package that generates fake data.
* [mixer](https://mixer.readthedocs.org) - Generating fake data and creating random fixtures for testing in Django ORM, SQLAlchemy, Peewee, MongoEngine, Pony ORM and etc.
* [model_mommy](https://model-mommy.readthedocs.org/) - Creating random fixtures for testing in Django.
* [ForgeryPy](https://pypi.python.org/pypi/ForgeryPy/0.1) - An easy to use forged data generator for Python. It's a port of [forgery](http://rubygems.org/gems/forgery).
* [radar](https://github.com/barseghyanartur/radar) - Generate random datetime / time.
* [ForgeryPy](https://pypi.python.org/pypi/ForgeryPy) - An easy to use forged data generator for Python. It's a port of [forgery](http://rubygems.org/gems/forgery).
* [radar](https://pypi.python.org/pypi/radar) - Generate random datetime / time.
* Error Handler
* [FuckIt.py](https://github.com/ajalt/fuckitpy) - FuckIt.py uses state-of-the-art technology to make sure your Python code runs whether it has any right to or not.
@ -857,7 +857,7 @@ A curated list of awesome Python frameworks, libraries and software. Inspired by
* [Biopython](http://biopython.org/wiki/Main_Page) - Biopython is a set of freely available tools for biological computation.
* [bccb](https://github.com/chapmanb/bcbb) - Collection of useful code related to biological analysis.
* [bcbio-nextgen](https://github.com/chapmanb/bcbio-nextgen) - A toolkit providing best-practice pipelines for fully automated high throughput sequencing analysis.
* [blaze](http://blaze.pydata.org/docs/latest/index.html) - NumPy and Pandas interface to Big Data.
## Data Visualization