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SciPy Recipes

You're reading from   SciPy Recipes A cookbook with over 110 proven recipes for performing mathematical and scientific computations

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781788291460
Length 386 pages
Edition 1st Edition
Languages
Tools
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Authors (3):
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 Martins Martins
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Martins
Ruben Oliva Ramos Ruben Oliva Ramos
Author Profile Icon Ruben Oliva Ramos
Ruben Oliva Ramos
V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
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Table of Contents (17) Chapters Close

Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Getting to Know the Tools FREE CHAPTER 2. Getting Started with NumPy 3. Using Matplotlib to Create Graphs 4. Data Wrangling with pandas 5. Matrices and Linear Algebra 6. Solving Equations and Optimization 7. Constants and Special Functions 8. Calculus, Interpolation, and Differential Equations 9. Statistics and Probability 10. Advanced Computations with SciPy

Accessing, selecting, and modifying data


In the following section, we will see some basic and advanced methods for indexing, editing, inserting, and deleting data.

Getting ready

A DataFrame consists of both rows and columns and has constructs to select data from specific rows and columns. These selections use the same operators as a Series, including [].loc[], and .iloc[].

Because of the multiple dimensions, the process by which these are applied differs slightly. We will examine these by first learning to select columns, then rows, a combination of rows and columns in a single statement, and also by using Boolean selections.

Additionally, pandas provides a construct for selecting a single scalar value at a specific row and column that we will investigate. This technique is important and exists because it is a very high-performance means of accessing these values.

How to do it...

Selecting the data in specific columns of a DataFrame is performed by using the [] operator. This differs from a...

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