exportcsv
linktbl_df
or data.frame
. Don't be spooked by the "csv" thing --
the data is NOT actually written to file during this process. Data is read
from the "maximal data rectangle", i.e. the rectangle spanned by the maximal
row and column extent of the data. By default, empty cells within this
rectangle will be assigned NA
. This is the fastest method of data
consumption, so use it as long as you can tolerate the lack of control re:
which cells are being read.gs_read_csv(ss, ws = 1, ..., verbose = TRUE)
googlesheet
objectdata.frame
or, if dplyr
is loaded, a
tbl_df
gs_read_cellfeed
,
gs_read_listfeed
, gs_read
,
gs_reshape_cellfeed
,
gs_simplify_cellfeed
gap_ss <- gs_gap() # register the Gapminder example sheet
oceania_csv <- gs_read_csv(gap_ss, ws = "Oceania")
str(oceania_csv)
oceania_csv
## crazy demo of passing args through to readr::read_csv()
oceania_crazy <- gs_read_csv(gap_ss, ws = "Oceania",
col_names = paste0("Z", 1:6), na = "1962", col_types = "cccccc", skip = 1)
oceania_crazy
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