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Home > Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools

Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools


Book Informaton

Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools

Author

David Mertz

Year of Publication

2021

Publisher

Packt Publishing - ebooks Account

Language

en

ISBN

1801071292, 9781801071291

ARI Id

1673353120494


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Showing 1 to 20 of 141 entries
Chapters/HeadingsAuthor(s)PagesInfo
Part I - Data Ingestion
Chapter 1: Tabular Formats
Tidying Up
Sanity Checks
The Good, the Bad, and the Textual Data
The Bad
The Good
Spreadsheets Considered Harmful
SQL RDBMS
Massaging Data Types
Repeating in R
Where SQL Goes Wrong (and How to Notice It)
Other Formats
HDF5 and NetCDF-4
Tools and Libraries
SQLite
Apache Parquet
Data Frames
Spark/Scala
Pandas and Derived Wrappers
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 20 of 141 entries