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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Hello, I'm IPython-Dashboar, which is inspired by one of the greatest packages, IPython.
I'm a stand alone, light-weight web server for building, sharing graphs created in ipython. Aiming at building for data science, data analysis guys. Building an interactive visualization, collaborated dashboard, and real-time streaming graph.
If you are doing data exploring in IPython notebook, and draw some graph or select some metrics from database, which will be used to present to others, but you don't like to share the code or the complicated logic [ for private or page cleaning ], I think I can help you to do the present part job.
In this tutorial, I'll show you how to do data exploring in ipython notebook and how to share it to others without ipython.
1. Load packages [ One can't make bricks without straw ]
I recommend import package in a readable and reasonable order, which will be useful as the project gets larger.
Step2:  2. Load data
I've prepared a test data on this repo.
Don't forget to take a look at the data before exploring it, that's a good habit.
Step3:  3. Traditionaly way of plotting [ I really like ipython indeed, but ... ]
matplotlib + seaborn + mpld3 
Step4:  4. Not enough even arm matplotlib with seaborn, mpld3
If you just wanna share this graph above to others ?
if you wanna hidden/show a specific field, eg, just show one years' population ?
If you wanna know the exact number of a bar when the hovering on the bar ?
if ...
if ...
5. How IPython-Dashboard make it simple
No need to code complicated graph settings
Flexible to define
Able to share one graph, multi-graph in a dashboard
More ? coming soon ...
5.1 Firstly, send you data to the IPython-Dashboard
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Python Code:
# built-in package
import os
import sys
import json
import time
import datetime as dt
# third-parth package
import dashboard as dash
import pandas as pd
import matplotlib as plt
import seaborn
import mpld3
# package configre
pd.options.display.max_columns = 100
pd.options.display.max_rows = 500
Explanation: Hello, I'm IPython-Dashboar, which is inspired by one of the greatest packages, IPython.
I'm a stand alone, light-weight web server for building, sharing graphs created in ipython. Aiming at building for data science, data analysis guys. Building an interactive visualization, collaborated dashboard, and real-time streaming graph.
If you are doing data exploring in IPython notebook, and draw some graph or select some metrics from database, which will be used to present to others, but you don't like to share the code or the complicated logic [ for private or page cleaning ], I think I can help you to do the present part job.
In this tutorial, I'll show you how to do data exploring in ipython notebook and how to share it to others without ipython.
1. Load packages [ One can't make bricks without straw ]
I recommend import package in a readable and reasonable order, which will be useful as the project gets larger.
End of explanation
url = https://github.com/litaotao/IPython-Dashboard/raw/v-0.1.2-visualiza-table/docs/people_number_by_province_lateset_10_years.csv
data = pd.read_csv(url)
data.head(3)
Explanation: 2. Load data
I've prepared a test data on this repo.
Don't forget to take a look at the data before exploring it, that's a good habit.
End of explanation
data.plot(x="地区", y=["2014年", "2013年"], kind="bar", figsize=(12, 5))
mpld3.display()
Explanation: 3. Traditionaly way of plotting [ I really like ipython indeed, but ... ]
matplotlib + seaborn + mpld3 : I really like it very much, but ...
raw html : ok, it a way indeed, but ...
End of explanation
dash.client.sender(data, key='chinese_population', force=True)
Explanation: 4. Not enough even arm matplotlib with seaborn, mpld3
If you just wanna share this graph above to others ?
if you wanna hidden/show a specific field, eg, just show one years' population ?
If you wanna know the exact number of a bar when the hovering on the bar ?
if ...
if ...
5. How IPython-Dashboard make it simple
No need to code complicated graph settings
Flexible to define
Able to share one graph, multi-graph in a dashboard
More ? coming soon ...
5.1 Firstly, send you data to the IPython-Dashboard
End of explanation
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