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Feature request: Allow recycling of col_type #114

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rickdonnelly opened this Issue Jul 7, 2015 · 3 comments

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@rickdonnelly

rickdonnelly commented Jul 7, 2015

I tried to set a single value for col_type to text for an Excel sheet with multiple columns. I got this error message:

Error: Need one name and type for each column

Since there is no way to extract the number of columns before reading the file it would be great if col_type could recycle its arguments when the list is shorter than the number of columns, as read.table, read_table, and fread all do.

@bbritten

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bbritten commented Jul 12, 2015

@rickdonnelly There is actually a way to extract the number of columns in an Excel sheet before reading it in. While I agree that it would be nice to have a recycling feature, this is the workaround I've been using:

library(tools)
format <- file_ext(file) %>% tolower()
sheetNames <- excel_sheets(file)
sheetIndex <- which(sheetNames == sheet)
functionName <- paste("readxl", format, "col_names", sep="_")
n <- .Call(functionName, PACKAGE = 'readxl', file, sheetIndex, skip) %>% length()
colTypes <- rep("text", n)
dat <- read_excel(file, col_types=colTypes, sheet=sheet, skip=skip)

You can obviously replace "text" in the colTypes assignment with one of the other values that is accepted by read_excel.

Hope this helps!

@vergilcw

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vergilcw commented Aug 14, 2015

readxl/R/RcppExports.R contains a number of helper functions that are not exported. Some of these could be useful for reading in excel sheets with unknown characteristics ahead of time (e.g. for linux users with no access to excel):
xls_col_names and xlsx_col_names as @theRanalyst suggests in his workaround
but there are also:
xls_col_types and xlsx_col_types which I assume predict the column types of a worksheet
xlsx_dim for getting the dimesions of the tabular data
countRows
and a few others. @hadley, is there a plan to export any of these helper functions in the future?

@jennybc

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jennybc commented Jan 7, 2017

Covered by #198

@jennybc jennybc closed this Jan 7, 2017

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