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Python 3 and Data Visualization

You're reading from   Python 3 and Data Visualization Mastering Graphics and Data Manipulation with Python

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Product type Paperback
Published in Aug 2024
Publisher Mercury_Learning
ISBN-13 9781836645719
Length 281 pages
Edition 1st Edition
Languages
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Authors (2):
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Mercury Learning and Information Mercury Learning and Information
Author Profile Icon Mercury Learning and Information
Mercury Learning and Information
Oswald Campesato Oswald Campesato
Author Profile Icon Oswald Campesato
Oswald Campesato
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Toc

Table of Contents (9) Chapters Close

Preface
1. Chapter 1: Introduction to Python 3 2. Chapter 2: NumPy and Data Visualization FREE CHAPTER 3. Chapter 3: Pandas and Data Visualization 4. Chapter 4: Pandas and SQL 5. Chapter 5: Matplotlib for Data Visualization 6. Chapter 6: Seaborn for Data Visualization 7. Index
Appendix: SVG and D3

LAMBDA EXPRESSIONS

Listing 1.12 displays the contents of Lambda1.py that illustrates how to create a simple lambda function in Python.

LISTING 1.12: Lambda1.py

add = lambda x, y: x + y 

x1 = add(5,7)
x2 = add('Hello', 'Python')

print(x1)
print(x2)

Listing 1.12 defines the lambda expression add that accepts two input parameters and then returns their sum (for numbers) or their concatenation (for strings).

The output from Listing 1.12 is here:

12
HelloPython

The next portion of this chapter discusses Python collections, such as lists (or arrays), sets, tuples, and dictionaries. You will see many short code blocks that will help you rapidly learn how to work with these data structures in Python. After you have finished reading this chapter, you will be in a better position to create more complex Python modules using one or more of these data structures.

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83
Tech Concepts
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Programming languages
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