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Data Reshaping

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May 1, 2024 3 minute read

Data reshaping, also known as data transformation, is the process of modifying the structure or format of a dataset to make it more suitable for a specific purpose. This can involve changing the number of rows, columns, or variables in a dataset, as well as the order of the data points.
Reshaping data can be necessary for a variety of reasons. For example, you may need to reshape data to make it compatible with a particular software program or algorithm.

Why Learn Data Reshaping?

Path to Data Reshaping

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We've curated three courses to help you on your path to Data Reshaping. Use these to develop your skills, build background knowledge, and put what you learn to practice.

Sorted from most relevant to least relevant:

Reshaping Data with R

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Tidy Messy Data using tidyr in R

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Managing Data in R Using Data Frames

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Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Reshaping.

The Elements of Statistical Learning

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Provides a comprehensive overview of statistical learning methods, including a chapter on data preprocessing and transformation, which covers data reshaping techniques.

The Elements of Statistical Learning: Data Mining,...

Hardcover

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The Elements of Statistical Learning: Data Mining,...

Hardcover

$$$

The Elements of Statistical Learning: Data Mining,...

Kindle Edition

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