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Geospatial Data Science Quick Start Guide

You're reading from   Geospatial Data Science Quick Start Guide Effective techniques for performing smarter geospatial analysis using location intelligence

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789809411
Length 170 pages
Edition 1st Edition
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Authors (2):
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Abdishakur Hassan Abdishakur Hassan
Author Profile Icon Abdishakur Hassan
Abdishakur Hassan
Jayakrishnan Vijayaraghavan Jayakrishnan Vijayaraghavan
Author Profile Icon Jayakrishnan Vijayaraghavan
Jayakrishnan Vijayaraghavan
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Toc

Exploratory data analysis

For this chapter, we will be using curated data from the New York taxi trip dataset provided by the city of New York. The original source for this data can be found here: https://data.cityofnewyork.us/api/odata/v4/hvrh-b6nb.

Visit the following website for more details about the data that's included in this dataset: https://data.cityofnewyork.us/Transportation/2016-Green-Taxi-Trip-Data/hvrh-b6nb.

For starters, let's have a peek at the data at hand using pandas. The curated data (NYC_sample.csv) that we will be using here can be found at the following download link: https://drive.google.com/file/d/1OkkYZJEcsdCkU0V42eP6pj6YaK2WCGCE/view.

df = pd.read_csv("NYC_sample.csv")
df.head().T

The curated New York taxi trip data that we are using has around 1.14 million records and has columns related to taxi fare, as well as trip duration, as...

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