IPython Dashboard

Abstract

1. Introduction

I'm so glad that this repo still draws you guys' attention until today. but actually I won't spend any time on it and I've got a much better way to draw dynamic plots in ipython notebook, and I've just post a blog about how to make it in notebooks (including source code and demo notebook).

Thank you guys again, and if possible, please don't cancel your stars, ha~ha, any problems and questions when using the new method will get answered as long as you put it under that post.

A stand alone, light-weight web server for building, sharing graphs created in IPython. Build for data science, data analysis guys. Aiming at building an interactive visualization, collaborated dashboard, and real-time streaming graph.

2. Objective

A stand alone, light-weight web server for building, sharing graphs created in ipython. Build for data science, data analysis guys. Aiming at building an interactive visualization, collaborated dashboard, and real-time streaming graph.

This project demonstrates how Python can be applied to a real-world Data Science problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/litaotao/IPython-Dashboard.git
cd IPython-Dashboard

1. Install prerequisite
2. install the latest stable IPython-Dashboard: pip install ipython-dashboard --upgrade
3. install redis 2.6+ : install guide
4. [option, if you need run sql]install mysql : brew install mysql or apt-get install mysql
5. install IPython-Dashboard requirements [unneeded sometimes]:
6. cd ~/your python package path/IPython-Dashboard
7. pip install -r requirements.txt
8. [option, if you need run sql]Config mysql

mysql> SELECT User,Host FROM mysql.user;
        +------+-----------+
        | User | Host      |
        +------+-----------+
        | root | 127.0.0.1 |
        | root | ::1       |
        |      | localhost |
        | root | localhost |
        |      | mac007    |
        | root | mac007    |
        +------+-----------+
        6 rows in set (0.00 sec)

mysql> create user 'ipd'@'localhost' identified by 'thanks';
        Query OK, 0 rows affected (0.00 sec)

        mysql> grant all privileges on *.* to ipd@localhost;
        Query OK, 0 rows affected (0.00 sec)

        mysql> SELECT User,Host FROM mysql.user;
        +------+-----------+
        | User | Host      |
        +------+-----------+
        | root | 127.0.0.1 |
        | root | ::1       |
        |      | localhost |
        | ipd  | localhost |
        | root | localhost |
        |      | mac007    |
        | root | mac007    |
        +------+-----------+
        7 rows in set (0.00 sec)

        mysql> flush privileges;
        Query OK, 0 rows affected (0.00 sec)

nosetests -s dashboard.tests.testCreateData:test_create_mysql_data

chenshan@mac007:/mnt/ipython-dashboard$ls -l
    total 0
    drwxrwxrwx  9 root  wheel  306 Dec 15 22:09 logs

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Turn the analysis into an interactive dashboard
• Automate data refresh with a scheduled job
• Add a predictive model on top of the analysis

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What is the source of the dataset and how was missing data handled?
2. Which exploratory analysis steps revealed the most useful insight?
3. Why were these particular charts chosen to present the data?
4. Which statistical or ML technique supports the conclusions?
5. How could the analysis be automated or refreshed with new data?

9. Source Code & License

This project is developed by litaotao and published on GitHub under the GNU General Public License v2.0. Please follow the license terms and credit the original author when you use or modify this code.