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Learning IPython for Interactive Computing and Data Visualization, Second Edition

You're reading from   Learning IPython for Interactive Computing and Data Visualization, Second Edition Get started with Python for data analysis and numerical computing in the Jupyter notebook

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783986989
Length 200 pages
Edition 1st Edition
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Author (1):
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Cyrille Rossant Cyrille Rossant
Author Profile Icon Cyrille Rossant
Cyrille Rossant
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Toc

Exploring a dataset in the Notebook

Here, we will explore a dataset containing the taxi trips made in New York City in 2013. Maintained by the New York City Taxi and Limousine Commission, this 50GB dataset contains the date, time, geographical coordinates of pickup and dropoff locations, fare, and other information for 170 million taxi trips.

To keep the analysis times reasonable, we will analyze a subset of this dataset containing 0.5% of all trips (about 850,000 rides). Compressed, this subset data represents a little less than 100MB. You are free to download and analyze the full dataset (or a larger subset), as explained below.

Provenance of the data

You will find the data subset we will be using in this chapter at https://github.com/ipython-books/minibook-2nd-data.

If you are interested in the original dataset containing all trips, you can refer to https://github.com/ipython-books/minibook-2nd-code/tree/master/chapter2/cleaning. This page contains the code to download the original dataset...

You have been reading a chapter from
Learning IPython for Interactive Computing and Data Visualization, Second Edition
Published in: Oct 2015
Publisher:
ISBN-13: 9781783986989
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