Book Image

IPython Interactive Computing and Visualization Cookbook - Second Edition

By : Cyrille Rossant
Book Image

IPython Interactive Computing and Visualization Cookbook - Second Edition

By: Cyrille Rossant

Overview of this book

Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.
Table of Contents (19 chapters)
IPython Interactive Computing and Visualization CookbookSecond Edition
Contributors
Preface
Index

Creating a route planner for a road network


In this recipe, we build upon several techniques described in the previous recipes in order to create a simple GPS-like route planner in Python. We will retrieve California's road network data from the United States Census Bureau in order to find shortest paths in the road network graph. This will allow us to display road itineraries between any two locations in California.

Getting ready

You need Smopy for this recipe. You can install it with pip install git+https://github.com/rossant/smopy. In order for NetworkX to read Shapefile datasets, you also need GDAL/OGR. You can install it with conda install gdal.

Note

At the time of this writing, gdal does not appear to work well with conda and Python 3.6. You may need to downgrade Python to Python 3.5 with conda install python=3.5.

How to do it...

  1. Let's import the packages:

    >>> import io
        import zipfile
        import requests
        import networkx as nx
        import numpy as np
        import pandas as pd...