<jupyter_start><jupyter_text>[10 things you really should know about jupyter notebooks - <NAME>](https://www.youtube.com/watch?v=FwUcJFSAfQw&feature=youtu.be&t=211)  Jupyter Themes- [Video - 4:20](https://youtu.be/FwUcJFSAfQw?t=240)- Install with `pip install jupyterthemes`- Note: you may need to clear your browser cache for changes to take place- More info [here](https://github.com/dunovank/jupyter-themes)<jupyter_code>!jt -t monokai -T<jupyter_output><empty_output><jupyter_text>Extensions- [Video - 5:25](https://youtu.be/FwUcJFSAfQw?t=325)- Install with `pip install jupyter_contrib_nbextensions` (juypter notebook server must not be running)- Install individual extensions with `jupyter-contrib nbextension install --sys-prefix`- From the Jupyter Notebook home, you can enable extensions on the **Nbextensions** tab. Refresh open notebooks to enable new extensions.  Some awsome extensions he introduced include:- **Table of Contents**: inserts an automatic table of contents based on your markdown headings- **Snippets Menu**: drops canned code snippets for common operations in popular libraries into a cell.  - You can make your own snippets by checking "Include custom menu content parsed from JSON string below" editing the "JSON string parsed to define custom menus (only used if the option above is checked)"  ```json{    "name" : "MAG Snippets",    "sub-menu" : [        {            "name" : "Data Import ($\\texttt{.xlsx}$)",            "sub-menu" : [                {                    "name" : "Asset Book Master Live",                    "snippet" : ["import pandas as pd",                        "df = pd.read_excel('Asset Book Master Live')"]                }            ]        }    ]}```  Magics- [Video - 13:48](https://youtu.be/FwUcJFSAfQw?t=820)- Documentation [here](http://ipython.readthedocs.io/en/stable/interactive/magics.html)<jupyter_code>%lsmagic
# lets you peek at a file
%pycat about.py
# loads code from a file into the cell
#%load about.py
# run code from a file and outputs displayed in your notebook
%run about.py
# get environmental variables
%env
# toggle pretty printing
%pprint
print('This')
# print cwd
%pwd
# run shell command (but notice how much faster %pwd is!)
!pwd
# install extra packages
!pip install watermark
# print watermark
%reload_ext watermark
%watermark<jupyter_output>2017-12-24T07:11:21-05:00

CPython 3.6.3
IPython 6.1.0

compiler   : GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)
system     : Darwin
release    : 16.3.0
machine    : x86_64
processor  : i386
CPU cores  : 8
interpreter: 64bit<jupyter_text>Interactive Visualization- [Video - 20:05](https://youtu.be/FwUcJFSAfQw?t=1206)<jupyter_code>import pandas as pd
df = pd.read_pickle('/Users/matthewkudija/Documents/GitHub/Aircraft-Data/Data/Ascend-Data/COMPLETE/pickle/FLEET DATABASE.p')
df = df[df.BuildRegion.isin(['Western']) & 
        df.OperatorCategory.isin(['Civil']) & 
        df.AircraftStatus.isin(['In Service','Storage']) & 
        df.AircraftType.isin(['AW139']) & 
        ~df['Mission'].isin(['Military'])
        ]
# install: `conda install -c tim_shawver/label/dev qgrid==1.0.0b10`
import qgrid
df = df[['SerialNumber','BuildRegion','OperatorCategory','AircraftStatus','AircraftType','Operator-Update','Mission-MAG','Age']]
qgrid.show_grid(df)
# embed a webpage (could also be a local PDF file, etc.)
from IPython.display import HTML
HTML('<iframe src="http://www.columbuslibrary.org/" width=800 height=400></iframe>')<jupyter_output><empty_output>
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