Software Open Access
SC4DA: Standard Container For Data Analysis
Maciej Bak
This is a recipe for creating an environment with tools and packages which I use for widely understood data analysis.
In general the smaller the environment is - the better. Little number of packages imply less constraints on software versions and smaller disk space. When it comes to publishing research I highly advise to encapsulate scripts and pipelines into minimal environments necessary to execute the analyses, either with Docker or Conda technologies.
That being said
Having a dedicated environment for software development & data analysis can speed up the research significantly. Often, to avoid wasting precious time, there is a need to perform a quick-and-dirty data inspection or processing. It would be a bad idea to install all the required packages into a main environment. It is much safer, more efficient and cleaner to have a separate work space just like the one I present here.
| Name | Size | |
|---|---|---|
|
SC4DA-master.zip
md5:afc8933206507a18ea4296cbd720561a |
45.9 kB | Download |
| All versions | This version | |
|---|---|---|
| Views | 114 | 114 |
| Downloads | 2 | 2 |
| Data volume | 91.8 kB | 91.8 kB |
| Unique views | 80 | 80 |
| Unique downloads | 1 | 1 |
- Publication date:
- September 18, 2020
- DOI:
-
- Keyword(s):
- Docker container Reproducible Research Data Analysis Conda virtual environment Reproducibility Data Science
- License (for files):
- Apache License 2.0