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Merging Data from Different Sources in Python

Unlock the power of pandas and master data merging in Python! Discover join types, merge key specs, and advanced techniques to solve real-world problems.

Advanced
47m
(6)

Created by Rudi Bruchez

Last Updated Jun 07, 2023

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  • Course

Merging Data from Different Sources in Python

Unlock the power of pandas and master data merging in Python! Discover join types, merge key specs, and advanced techniques to solve real-world problems.

Advanced
47m
(6)

Created by Rudi Bruchez

Last Updated Jun 07, 2023

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What you'll learn

Combining data from various sources is crucial for data professionals to extract valuable insights.

In this course, Merging Data from Different Sources in Python, you'll learn the techniques to merge and concatenate diverse data sets seamlessly using pandas.

First, you'll delve into concatenation with pandas' concat() and append() functions.

Next, you'll explore different types of joins, such as one-to-one, many-to-one, and many-to-many, using the pd.merge() function.

Finally, you'll learn how to handle non-matching column names, merge with indices, and resolve overlapping column names using advanced merging strategies.

When you finish this course, you'll have the skills and knowledge needed to effectively combine data from diverse sources in Python, facilitating more comprehensive data analysis.

Software required: Python 3.x and pandas library.

Merging Data from Different Sources in Python
Advanced
47m
(6)
Table of contents

About the author
Rudi Bruchez - Pluralsight course - Merging Data from Different Sources in Python
Rudi Bruchez
8 courses 4.4 author rating 191 ratings

Rudi Bruchez is a freelance consultant and trainer based in Paris, France. He has more than 15 years of experience with SQL Server and started to venture into NoSQL territories. As SGBD evolve into more complex solutions, he tries to make sure that people understand the fundamentals and implement their databases wisely.

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