Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
The Data Wrangling Workshop

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

Arrow left icon
Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839215001
Length 576 pages
Edition 2nd Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
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
Arrow right icon
View More author details
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

Data Formatting

In this section, we will format a given dataset. The main motivations behind formatting data properly are as follows:

  • It helps all the downstream systems have a single and pre-agreed form of data for each data point, thus avoiding surprises and, in effect, there is no risk which might break the system.
  • To produce a human-readable report from lower-level data that is, most of the time, created for machine consumption.
  • To find errors in data.

There are a few ways to perform data formatting in Python. We will begin with the modulus % operator.

The % operator

Python gives us the modulus % operator to apply basic formatting on data. To demonstrate this, we will load the data by reading the combined_data.csv file, and then we will apply some basic formatting to it.

Note

The combined_data.csv file contains some sample medical data for four individuals. The file can be found here: https://packt.live/310179U.

We can load the data from the...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image