May 1, 2024
Updated May 10, 2025
20 minute read
At a high level, a DataFrame is a two-dimensional, size-mutable, and potentially heterogeneous tabular data structure with labeled axes (rows and columns). Think of it like a spreadsheet or a SQL table, where data is organized in a way that's intuitive and easy to understand. It's a fundamental tool in the world of data analysis and manipulation, allowing users to efficiently work with structured data.
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Find a path to becoming a DataFrames. Learn more at:
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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
DataFrames.
Comprehensive guide to using Pandas, a popular Python library for data analysis and manipulation. It covers everything from the basics of dataframes to advanced topics like data cleaning, transformation, and visualization. The author, Wes McKinney, is the creator of Pandas, so you can be sure that you're getting the most up-to-date information.
Comprehensive guide to using Python for data analysis. It covers everything from the basics of Python to advanced topics like data cleaning, transformation, and visualization. The author, Kirk Borne, data scientist and educator with over 15 years of experience using Python.
Comprehensive guide to using R and ggplot2 for data analysis. It covers everything from the basics of R and ggplot2 to advanced topics like data cleaning, transformation, and visualization. The author, Hadley Wickham, leading expert in data science and the creator of the popular tidyverse packages for R.
Comprehensive guide to using SPSS for data analysis. It covers everything from the basics of SPSS to advanced topics like data cleaning, transformation, and visualization. The author, George A. Marcoulides, data analyst and educator with over 20 years of experience using SPSS.
Comprehensive guide to using Go for data analysis. It covers everything from the basics of Go to advanced topics like data cleaning, transformation, and visualization. The author, William Kennedy, data scientist and educator with over 10 years of experience using Go.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/0w1axa/dataframe
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