Wide to long

1

gather(data, key, value, ..., na.rm = FALSE, convert = FALSE)
  • data: The dataset to be modified (in our case, seps)
  • key: the name of the new “naming” variable (year)
  • value: the name of the new “result” variable (value)
  • na.rm: whether missing values are removed (this dataset doesn’t have any, so it isn’t a problem)
  • convert: convert anything that seems like it should be in another format to that other format, e.g. numeric to numeric (since we used read_csv we don’t need this one either)

Long to wide

1

spread(data, key, value, fill = NA, convert = FALSE)

The format of this one is similar to gather():

  • data: The data to be reformatted (inprogress)
  • key: The column you want to split apart (Field)
  • value: The column you want to use to populate the new columns (the value column we just created in the spread step)
  • fill: what to substitute if there are combinations that don’t exist (not a problem here)
  • convert: whether to fix incorrect data types as it goes (not a problem here)

参考来源

https://rstudio-pubs-static.s3.amazonaws.com/282405_e280f5f0073544d7be417cde893d78d0.html

http://www.cookbook-r.com/Manipulating_data/Converting_data_between_wide_and_long_format/

https://github.com/rstudio/cheatsheets/blob/master/data-import.pdf

https://uc-r.github.io/tidyr