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Data types and import into R

R functions

  • read.table - reads table in a plain text with cells delimited by some symbol (default setting for delimiter is sep = “”, i.e. one or more white spaces, tabs, newlines or returns).
  • read.delim - reads table delimited by tabulators.
  • read.csv - reads table delimited by commas (,), with decimals being dots (.).
  • read.csv2 - reads table delimited by semicolons (;) and decimals being commas (,).
  • read_excel (library readxl) - reads data frames directly from Excel file (both *.xls and *.xlsx) without need to install any third party software; it stores data in tibble format, with rownames (if any) as the first column of the data - this needs to be treated before further analysis (see Example section to see how).
  • read.cep (library vegan) - reads legacy canoco condensed files (usually with extension *.cep or *.cc!); the function can get quite slow for large datasets - if the speed is an issue, consider using readCEP from cepreader package (also maintained by Jari Oksanen)
  • read.CEP (library rioja) the same as read.cep from vegan and readCEP from cepreader; the package rioja has also function write.CEP producing cep files.

Note that by default, functions like read.table, read.delim, read.csv and read.csv2 import the columns containing characters strings into R as factors. If you don't like this behaviour, change the setting of stringsAsFactors argument into FALSE. If you want to know why this behaviour is set to default, read this blog post.

en/data_import_r.txt · Last modified: 2021/03/03 19:47 by David Zelený