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Jupyter for Data Science

You're reading from   Jupyter for Data Science Exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781785880070
Length 242 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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 Toomey Toomey
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Toomey
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Toc

Table of Contents (17) Chapters Close

Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Jupyter and Data Science FREE CHAPTER 2. Working with Analytical Data on Jupyter 3. Data Visualization and Prediction 4. Data Mining and SQL Queries 5. R with Jupyter 6. Data Wrangling 7. Jupyter Dashboards 8. Statistical Modeling 9. Machine Learning Using Jupyter 10. Optimizing Jupyter Notebooks

Creating a human density map


I had originally planned on producing a worldwide human density map, but the graphics available don't allow for setting the color of each country. So, I built a density map for the United States.

The algorithm is:

  1. Obtain graphic shapes for each of the states.
  2. Obtain the density for each state.
  3. Decide on a color range and apply the lowest density to one end of the range and the highest to the other end.
  4. For each state:
    • Determine it's density
    • Lookup that density value in the range and select a color
    • Draw the state

This is coded with the following (comments embedded as the code proceeds):

%matplotlib inline
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from matplotlib.patches import Polygon
import pandas as pd
import numpy as np
import matplotlib
# create the map
map = Basemap(llcrnrlon=-119,llcrnrlat=22,urcrnrlon=-64,urcrnrlat=49,
        projection='lcc',lat_1=33,lat_2=45,lon_0=-95)
# load the shapefile, use the name 'states'
# download from https...
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