DATA MANIPULATION IN R
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Web scraping with rvest
Import and export data
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Pattern matching with grepl() and grep()
String manipulation
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Pattern matching and replacement with gsub() and sub()
String manipulation
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Row and column sums and means
Data transformation
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Row and column names
Data transformation
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Concatenate strings with paste and paste0
String manipulation
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Count the number of characters with nchar
String manipulation
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Read SQL databases
Import and export data
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lapply function
apply family
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Read Excel files
Import and export data
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Merge data frames
Data transformation
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Aggregate
Data transformation
¿What is DATA MANIPULATION?
Data manipulation, also known as data wrangling, refers to the process of transforming and cleaning raw data into a structured format suitable for analysis. This process involves various operations such as filtering, sorting, aggregating, merging, reshaping, and transforming data to make it more organized, understandable, and ready for analysis. R provides several functions to perform these tasks, but dplyr
is one of the most popular and widely used R packages for data manipulation.
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Base R
Data manipulation in base R involves using the core functions and methods provided by R's base package for handling, transforming, and manipulating data structures such as vectors, matrices, arrays, data frames, and lists. -
dplyr
dplyr
is an R package designed for efficient and user-friendly data manipulation. It provides a set of functions that streamline data wrangling tasks by offering a consistent grammar for manipulating data frames and data tables.