[PYTHON] Think about the analysis environment (Part 1: Overview) * As of January 2017

Preface

――This article is just an individual opinion ――I think there is a more suitable shape depending on the environment --There may be a smarter way due to lack of study

Flow of analysis environment construction

――We will build a virtual environment according to the following flow

What kind of person is it for?

――When thinking about the analysis environment, I thought about the analysis environment by ** what kind of work I usually do ** ――I think there are various ways of working, but this time I will consider the following analysis environment for people.

The result of thinking

――We considered the following analysis environment

• The more you write, the more complicated and difficult to understand

Thoughts

[1] Why virtualization?

--The analysis execution environment is likely to be SSH to a Linux-based server. --Reduce rework by building a Linux environment locally

• Specifically, because I have experienced the following rework

There is practice ①

--Laptop environment is Windows or Mac --There is a Linux environment if you SSH to the analysis server ――Although there is an analysis server, I want to develop it locally rather than on the server first. --Reason (1): I don't want to bother people who are using the analysis server by sending strange code. --Reason (2): It is troublesome to transfer the result ――Reason ③: It is troublesome to SSH each time you want to analyze quickly --An error occurs when executing locally analyzed code on the analysis server --Cause (1): The package is not installed --Cause (2): Package version is different --Cause ③: Encoding and line feed code are different --Try & error on analysis server

There is practice ②

--Laptop environment is Windows --I want to run it on the terminal, but MS-DOS is difficult to use and I put Cygwin --Stumbling on library installation ――You can do your best and move it for the time being, but the environment will be messed up. --When I try to put Anaconda in Cygwin, it doesn't work. --Give up and analyze in Windows environment and do not run on the terminal --Try & error on analysis server

[2] Analysis client tool

――I personally like the analysis environment like Rstudio ――The reasons I like are as follows

1. The execution result of the script is displayed separately
2. Can be executed line by line
3. You can write markdown
4. You can do a slide show
5. Can work with virtual environment
6. Easy environment construction --Python also searched for a similar environment and summarized below

• There is a possibility of insufficient investigation

[3] Software license

--Use an open source license --The reasons for using it are as follows ――Considering cooperation with academics, I want to avoid paid environments as much as possible --I don't want to be dependent on paid software

[4] Reasons for choosing other software

reference

• http://www.datascientist.or.jp/news/2014/pdf/1210.pdf
• http://qiita.com/chiku_/items/29d8ffd4b2c13989a96b