Python Software


Less is more. Stay pure. Stay poor.
I have never used Python. I am looking to install it on my home computer and get a little familiar with it then put a request in to install it on my work computer. What generic or crude things do I need to know.

For example, when installing it -is it comparable to R; in that I install the base program, and is there an interface like R studio? Then once I get working I install packages like in R? So that may mean there is a repository I need to access? Also, how often do I need to upgrade programs or packages, in general.

I would appreciate any general advice, comments, recommendations.



Probably A Mammal
If you're on Windows I recommend WinPython. The Linux analog would be Anaconda. They both provide the tools to better manage your Python "packages" (modules) so you can more easily get new libraries added to your installation. It also comes loaded with most of the standard scientific libraries you'll probably want. WinPython also comes with Spyder, a Python-based IDE that is "RStudio" like. I like it. But there are others.

From there, the basic things to know are
1. How to use Python, basic syntax, data types, and you can use R analogs here (compare R list to Python dict, R vectors to Python lists, and understand the difference among other Python vectorized types: lists, tuples, dicts, etc.)

2. How to use Python to do basic workflows: import data, write data

3. How to use the libraries to make it easier: Pandas especially, Numpy might still be relevant to some degree (but not really). Pandas brings "R" to Python in a sense.

4. Learn how to visualize things in Python.
I'm a little late to the party...but if you are still looking for recommendations:

1. I use Rodeo, which is a Python IDE used in Data Science - it's nice because you can see plots -->
2. Jupyter Notebook is also nice and allows you to see plots as well
3. Libraries: Pandas especially, but also scipy (for numerical and scientific calculations), numpy, matplotlib (plotting library), Scikit-Learn (machine learning)
4. DataCamp has some nice introductions to Python for Data Science

Numpy tutorial:

Good luck! Python is fun. :)


Less is more. Stay pure. Stay poor.
Thanks, perhaps I will ask you some questions in the future. I have been too busy forever to really take off or even install the programs.