kz-jpylb

This repository makes it easy to create an environment fot data-analysis via Docker.

This is a base image

Jupyter Notebook Data Science Stack

Some people reckon that such an environment is satisfied with JupyterNotebook or Colaboratory. Yes. It's exactly as you thought. However, the actual reason why I did such a hassle thing is for my comprehension of Docker. I am just a one of learners. I wanna confirm if I apprehend the usage of Docker. I think this is gonna be a great opportunity. As I said, however, I am still a beginner. It means there might be some mistakes. Thus, If you have some advice or request, please feel free to leave issues.

Actually, these has nothing to do with this repository, I listed up some useful and pragmatic references when creating this repository as follows:

There are bunch of references because of my lack of competences. Anyway, Thank you very much.

Directory Structure

kz-jpylb
    ┣ work
    ┃   ┣ test1.ipynb        # Example Notebook_01
    ┃   ┗ test2.ipynb        # Example Notebook_02
    ┣ juoyter                # Jupyter Stuffs
    ┃   ┗ Dockerfile
    ┣ kzdb                   # Database Stuffs
    ┃   ┣ ...
    ┃   ┗ kzbase             # Example Table
    ┣ README.md              # Instruction Manual
    ┣ LICENSE
    ┣ my.conf
    ┣ .env.example           # You have to modify, look at a detail below
    ┣ .gitignore
    ┗ docker-compose.yml

1. Installing Docker

General installation instructions are on the Docker site, but we give some quick links here:

OSX
Windows

2.1 Modify your own UID

Linux/MacOS:

$ echo $UID
501  (yours might be different from mine)

After executing above command, you should follow the instructions:

Open .env.example
Modify UID=501 (this number was acquired above)
Rename .env.example to .env

That's all.

2.2 run a new Docker container

Windows/Linux/MacOS:

$ docker-compose up -d

This container setup

Package            Version    
------------------ --------
beautifulsoup4     4.7.1   
conda              4.6.8  
matplotlib         3.0.3   
numpy              1.15.4  
pip                19.0.3  
requests           2.21.0 
scikit-image       0.14.2  
scikit-learn       0.20.3  
scipy              1.2.1   
seaborn            0.9.0  
SQLAlchemy         1.3.1 
urllib3            1.24.1  
xgboost            0.82

etc...

3 How to use Jupyter Lab

Copy/paste this URL into your browser when you connect for the first time,

http://localhost:8888/lab/?

if you want to use Jupyter-Notebook

http://localhost:8888/?

4 How to use DataBase