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Learning IPython for Interactive Computing and Data Visualization - Second Edition by Cyrille Rossant

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Chapter 2. Interactive Data Analysis with pandas

In this chapter, we will cover the following topics:

  • Exploring a dataset in the Notebook
  • Manipulating data
  • Complex operations

We'll see how to load, explore, and visualize a real-world dataset with pandas, matplotlib, and seaborn, all in the Notebook. We will also perform data manipulations efficiently.

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 ...

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