May 1, 2024
Updated May 8, 2025
24 minute read
Data manipulation is the process of changing, organizing, or restructuring raw data to make it more understandable, usable, and suitable for analysis or other downstream tasks. It's a critical step in the broader fields of data analysis, data mining, and preparing data for machine learning models. Essentially, data manipulation involves taking data in its initial form and transforming it into a more refined state, which can lead to easier insights and better-informed decisions. This process can encompass a wide array of operations, including cleaning, sorting, filtering, aggregating, and joining datasets.
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Find a path to becoming a Data Manipulation. Learn more at:
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Reading list
We've selected nine 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 Manipulation.
Provides a comprehensive overview of data manipulation techniques in R, covering topics such as data cleaning, transformation, and visualization. It valuable resource for beginners who want to learn the basics of data manipulation and for experienced users who want to improve their skills.
Provides a comprehensive overview of data manipulation techniques in Python, covering topics such as data cleaning, transformation, and visualization. It valuable resource for beginners who want to learn the basics of data manipulation and for experienced users who want to improve their skills.
Provides a comprehensive overview of data manipulation techniques in Stata, covering topics such as data cleaning, transformation, and analysis. It valuable resource for researchers and practitioners who need to manipulate data for statistical analysis.
Provides a comprehensive overview of data manipulation techniques in SQL, covering topics such as data cleaning, transformation, and analysis. It valuable resource for researchers and practitioners who need to manipulate data for statistical analysis.
Provides a comprehensive overview of data manipulation techniques in Hadoop, covering topics such as data cleaning, transformation, and analysis. It valuable resource for researchers and practitioners who need to manipulate data for statistical analysis.
Provides a comprehensive overview of data manipulation techniques in Spark, covering topics such as data cleaning, transformation, and analysis. It valuable resource for researchers and practitioners who need to manipulate data for statistical analysis.
Provides a comprehensive overview of data manipulation techniques in Pig, covering topics such as data cleaning, transformation, and analysis. It valuable resource for researchers and practitioners who need to manipulate data for statistical analysis.
Provides a comprehensive overview of data manipulation techniques in SAS, covering topics such as data cleaning, transformation, and analysis. It valuable resource for researchers and practitioners who need to manipulate data for statistical analysis.
Provides a comprehensive overview of data manipulation techniques in Excel, covering topics such as data cleaning, transformation, and analysis. It valuable resource for beginners who want to learn the basics of data manipulation and for experienced users who want to improve their skills.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/43qk18/data
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