0th

Percentile

##### Standard-evaluation version of spread.

This is a S3 generic.

Keywords
internal
##### Usage
spread_(data, key_col, value_col, fill = NA, convert = FALSE, drop = TRUE, sep = NULL)
##### Arguments
data
A data frame.
key_col, value_col
Strings giving names of key and value cols.
fill
If set, missing values will be replaced with this value. Note that there are two types of missingness in the input: explicit missing values (i.e. NA), and implicit missings, rows that simply aren't present. Both types of missing value will be replaced by fill.
convert
If TRUE, type.convert with asis = TRUE will be run on each of the new columns. This is useful if the value column was a mix of variables that was coerced to a string. If the class of the value column was factor or date, note that will not be true of the new columns that are produced, which are coerced to character before type conversion.
drop
If FALSE, will keep factor levels that don't appear in the data, filling in missing combinations with fill.
sep
If NULL, the column names will be taken from the values of key variable. If non-NULL, the column names will be given by "".