In Part 2 of our Jupyter Notebook Tutorial series, we will learn installing packages in Jupyter, importing data, plotting inline etc works. Our Part 1 of Jupyter Notebook Tutorial was on how to install on localhost or server – on Mac OS X or GNU/Linux. For quick recapitulation to unused with Python, normally on terminal, if you run :
|
1 |
python |
then it will start Python interactive command shell like this :
|
1 2 3 4 |
Python 2.7.13 (default, Jun 24 2017, 02:53:00) [GCC 4.2.1 Compatible Apple LLVM 8.1.0 (clang-802.0.42)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> |
To obtain current directory, we first will run :
---
|
1 |
import os |
then :
|
1 |
os.getcwd() |
To exit that shell, we will type :
|
1 |
exit() |
If you type :
|
1 |
ipython |
you’ll get enhanced interactive Python shell.
Jupyter Notebook Tutorial : Part 2
Now open Jupyter Notebook on browser like we talked in Part 1 of this series. On the right hand side there will be a “New” dropdown menu. If you click it, that first option will be “Python3” (which you’ll normally click to start works), other options includes a terminal. You’ll see the input field :
|
1 |
In [ ] |
Copy paste this :
|
1 |
print("The answer is", 2*2) |
then click the RUN button, which should return “The answer is 4”. If you want a LaTeX output, run this :
|
1 2 |
from IPython.display import display, Math, Latex display(Math(r'sqrt{a^2 + b^2}')) |
For the next steps of guides, you need to install :
- Pandas
- NumPy
- SciPy
- Plotly
- matplotlib
via pi. For Mac OS X appendicectomy sudo -H before the commands and run :
|
1 2 3 4 5 |
pip install pandas pip install numpy pip install scipy pip install plotly pip install matplotlib |
pip install numpy will show that previous command already installed it. Now again freshly launch Jupyter notebook with the command :
|
1 |
jupyter notebook |
In that Jupiter notebook’s input, enter this and run, which is example of using Plotly :
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 |
import plotly.plotly as py from plotly.graph_objs import * import pandas as pd mapbox_access_token = 'pk.eyJ1IjoiY2hlbHNlYXBsb3RseSIsImEiOiJjaXFqeXVzdDkwMHFrZnRtOGtlMGtwcGs4In0.SLidkdBMEap9POJGIe1eGw' json_data = pd.read_json('https://raw.githubusercontent.com/ottlngr/2016-15/ottlngr/ottlngr/sites.json') rating_one_site_lat = [] rating_one_site_lon = [] locations_name = [] for index in range(len(json_data)): if json_data['locations'][index] != []: if json_data['site'][index]['rating'] == 1: rating_one_site_lat.append(json_data['locations'][index][0]['latitude']) rating_one_site_lon.append(json_data['locations'][index][0]['longitude']) locations_name.append(json_data['site'][index]['name']) data = Data([ Scattermapbox( lat=rating_one_site_lat, lon=rating_one_site_lon, mode='markers', marker=Marker( size=18, color='rgb(155, 240, 225)', opacity=0.7 ), text=locations_name, hoverinfo='text' ), Scattermapbox( lat=rating_one_site_lat, lon=rating_one_site_lon, mode='markers', marker=Marker( size=8, color='rgb(205, 245, 100)' ), hoverinfo='skip' )] ) layout = Layout( title='Nuclear Waste Sites on Campus', autosize=True, hovermode='closest', showlegend=False, mapbox=dict( accesstoken=mapbox_access_token, bearing=0, center=dict( lat=38, lon=-94 ), pitch=0, zoom=3, style='dark' ), ) fig = dict(data=data, layout=layout) py.iplot(fig, filename='jupyter/Nuclear Waste Sites on American Campuses') |
