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The Data Wrangling Workshop

You're reading from   The Data Wrangling Workshop Create your own actionable insights using data from multiple raw sources

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839215001
Length 576 pages
Edition 2nd Edition
Languages
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Authors (3):
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Dr. Tirthajyoti Sarkar Dr. Tirthajyoti Sarkar
Author Profile Icon Dr. Tirthajyoti Sarkar
Dr. Tirthajyoti Sarkar
Shubhadeep Roychowdhury Shubhadeep Roychowdhury
Author Profile Icon Shubhadeep Roychowdhury
Shubhadeep Roychowdhury
Brian Lipp Brian Lipp
Author Profile Icon Brian Lipp
Brian Lipp
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Toc

Table of Contents (11) Chapters Close

Preface
1. Introduction to Data Wrangling with Python 2. Advanced Operations on Built-In Data Structures FREE CHAPTER 3. Introduction to NumPy, Pandas, and Matplotlib 4. A Deep Dive into Data Wrangling with Python 5. Getting Comfortable with Different Kinds of Data Sources 6. Learning the Hidden Secrets of Data Wrangling 7. Advanced Web Scraping and Data Gathering 8. RDBMS and SQL 9. Applications in Business Use Cases and Conclusion of the Course Appendix

Identifying and Cleaning Outliers

When confronted with real-world data, we often see a specific thing in a set of records: there are some data points that do not fit with the rest of the records. They have some values that are too big, too small, or that are completely missing. These kinds of records are called outliers.

Statistically, there is a proper definition and idea about what an outlier means. And often, you need deep domain expertise to understand when to call a particular record an outlier. However, in this exercise, we will look into some basic techniques that are commonplace for flagging and filtering outliers in real-world data for day-to-day work.

Exercise 6.07: Outliers in Numerical Data

In this exercise, we will construct a notion of an outlier based on numerical data. Imagine a cosine curve. If you remember the math for this from high school, then a cosine curve is a very smooth curve within the limit of [1, -1]. We will plot this cosine curve using the plot...

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