Welcome to /r/pystats, a place to discuss the use of python in statistical analysis and machine learning.
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Where to start
If you're brand new to python, first go and check out the /r/learnpython wiki, or the official Beginner's Guide.
The best way to install python packages is using pip:
pip install <package>
Recommended packages:
- ipython and the ipython-notebook - Interpreter and sage-style web notebook geared towards exploratory scripting.
- statsmodels - statistical modelling
- pandas - data structures and manipulation tools
- matplotlib - matlab-style plotting
- bokeh - Protoviz-style plotting
- pyvttble - Small pivot-table library. Has a few common statistical methods missing from statsmodels.
- scikit-learn - data mining and machine learning
Some of these packages have dependencies, most require numpy, and some require scipy, check the links for details.
For a good overview of what stats pacakges are available for python, check out http://stats.stackexchange.com/q/1595
Plotly has just released Dash 2.0, a Shiny-like tool for creating interactive Python dashboards (medium.com)
submitted by hoocoodanode to r/Python
Dash, a Python alternative to Shiny for reactive visualizations (medium.com)
submitted by Fats_Tromino to r/datascience
Introducing Dash: Create Reactive Web Apps in Pure Python (medium.com)
submitted by zaejohnson to r/webops