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Practical Data Analysis Using Jupyter Notebook

You're reading from   Practical Data Analysis Using Jupyter Notebook Learn how to speak the language of data by extracting useful and actionable insights using Python

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781838826031
Length 322 pages
Edition 1st Edition
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Author (1):
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Marc Wintjen Marc Wintjen
Author Profile Icon Marc Wintjen
Marc Wintjen
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Table of Contents (18) Chapters Close

Preface 1. Section 1: Data Analysis Essentials
2. Fundamentals of Data Analysis FREE CHAPTER 3. Overview of Python and Installing Jupyter Notebook 4. Getting Started with NumPy 5. Creating Your First pandas DataFrame 6. Gathering and Loading Data in Python 7. Section 2: Solutions for Data Discovery
8. Visualizing and Working with Time Series Data 9. Exploring, Cleaning, Refining, and Blending Datasets 10. Understanding Joins, Relationships, and Aggregates 11. Plotting, Visualization, and Storytelling 12. Section 3: Working with Unstructured Big Data
13. Exploring Text Data and Unstructured Data 14. Practical Sentiment Analysis 15. Bringing It All Together 16. Works Cited
17. Other Books You May Enjoy

Making your first NumPy array

The easiest example to create a one-dimensional array would be a straightforward command.After renaming your Jupyter notebook from Untitled to array_basics, the first thing to do is to import the numpy library into your active session by typing in import numpy as np in the In [] command and running the cell.

I like to run this line first to ensure the library is installed properly so if you receive an error, double-check and ensure that conda or pip was set up correctly.See Chapter 2,Overview of Python and Installing Jupyter Notebook, for help.

Next, you want to assign the array object a variable name so you can reference it in future commands.It is common to use single character values such as a or x as a shortcut for your array but for just getting started, let's use something more descriptive, such as my_first_array for easier reference.To the right of the equals sign, we reference the numpy method using np.array followed...

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