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
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Numerical Computing with Python

You're reading from   Numerical Computing with Python Harness the power of Python to analyze and find hidden patterns in the data

Arrow left icon
Product type Course
Published in Dec 2018
Publisher Packt
ISBN-13 9781789953633
Length 682 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Authors (5):
Arrow left icon
Pratap Dangeti Pratap Dangeti
Author Profile Icon Pratap Dangeti
Pratap Dangeti
Theodore Petrou Theodore Petrou
Author Profile Icon Theodore Petrou
Theodore Petrou
Allen Yu Allen Yu
Author Profile Icon Allen Yu
Allen Yu
Aldrin Yim Aldrin Yim
Author Profile Icon Aldrin Yim
Aldrin Yim
Claire Chung Claire Chung
Author Profile Icon Claire Chung
Claire Chung
+1 more Show less
Arrow right icon
View More author details
Toc

Table of Contents (21) Chapters Close

Title Page
Contributors
About Packt
Preface
1. Journey from Statistics to Machine Learning FREE CHAPTER 2. Tree-Based Machine Learning Models 3. K-Nearest Neighbors and Naive Bayes 4. Unsupervised Learning 5. Reinforcement Learning 6. Hello Plotting World! 7. Visualizing Online Data 8. Visualizing Multivariate Data 9. Adding Interactivity and Animating Plots 10. Selecting Subsets of Data 11. Boolean Indexing 12. Index Alignment 13. Grouping for Aggregation, Filtration, and Transformation 14. Restructuring Data into a Tidy Form 15. Combining Pandas Objects 1. Other Books You May Enjoy Index

Understanding the differences between concat, join, and merge


The merge and join DataFrame (and not Series) methods and the concat function all provide very similar functionality to combine multiple pandas objects together. As they are so similar and they can replicate each other in certain situations, it can get very confusing when and how to use them correctly. To help clarify their differences, take a look at the following outline:

  • concat:
    • Pandas function
    • Combines two or more pandas objects vertically or horizontally
    • Aligns only on the index
    • Errors whenever a duplicate appears in the index
    • Defaults to outer join with option for inner
  • join:
    • DataFrame method
    • Combines two or more pandas objects horizontally
    • Aligns the calling DataFrame's column(s) or index with the other objects' index (and not the columns)
    • Handles duplicate values on the joining columns/index by performing a cartesian product
    • Defaults to left join with options for inner, outer, and right
  • merge:
    • DataFrame method
    • Combines exactly two...
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