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Hands-On Data Analysis with Pandas

You're reading from   Hands-On Data Analysis with Pandas Efficiently perform data collection, wrangling, analysis, and visualization using Python

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Product type Paperback
Published in Jul 2019
Publisher
ISBN-13 9781789615326
Length 740 pages
Edition 1st Edition
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Author (1):
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Stefanie Molin Stefanie Molin
Author Profile Icon Stefanie Molin
Stefanie Molin
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Table of Contents (21) Chapters Close

Preface 1. Section 1: Getting Started with Pandas
2. Introduction to Data Analysis FREE CHAPTER 3. Working with Pandas DataFrames 4. Section 2: Using Pandas for Data Analysis
5. Data Wrangling with Pandas 6. Aggregating Pandas DataFrames 7. Visualizing Data with Pandas and Matplotlib 8. Plotting with Seaborn and Customization Techniques 9. Section 3: Applications - Real-World Analyses Using Pandas
10. Financial Analysis - Bitcoin and the Stock Market 11. Rule-Based Anomaly Detection 12. Section 4: Introduction to Machine Learning with Scikit-Learn
13. Getting Started with Machine Learning in Python 14. Making Better Predictions - Optimizing Models 15. Machine Learning Anomaly Detection 16. Section 5: Additional Resources
17. The Road Ahead 18. Solutions
19. Other Books You May Enjoy Appendix

Collecting temperature data

In Chapter 2, Working with Pandas DataFrames, we worked on data collection and how to perform an initial inspection and filtering of the data; this usually gives us ideas of things that need to be addressed before we move further in our analysis. Since this chapter builds on those skills, we will get to practice some of them here as well. To begin, we will start by exploring the weather API that's provided by the NCEI. We will learn about data wrangling with temperature data that's obtained from the API.

To use the API, you will have to request a token by filling out the form with your email address here: https://www.ncdc.noaa.gov/cdo-web/token. If you don't want to do this, you can read through the API code and then read in the CSV file from the GitHub folder and follow along from there.

For this section, we will be working in the...

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