Description Usage Arguments Value Examples
Create an abstract data frame
1 2 3 4 5 |
description |
character string. A description of the connection; the path to a file for file connections. |
conMethod |
string indicating the connection method. |
encoding |
encoding to use in the connections |
expand.path |
logical. Should 'description' be normalized and wildcard expanded. |
colClasses |
an optional character vector of column classes. If named and colNames is missing, the names will be used for colNames. If missing, will be automatically determined. |
colNames |
an optional character vector of column names. If missing and header = TRUE, these will be determined be the first row of data. Otherwise, names will be constructed by pasting the character 'V' with the column number. |
skip |
number of lines to strip off of the file or connection before parsing |
chunkProcessor |
a function to apply post-processing to a formatted dataframe. Usually only used without a chunkFormatter. |
chunkFormatter |
an optional function turning the raw connection into a dataframe. It must accept four parameters: data, colNames, colClasses, levels. If missing this will be constructed automatically. |
sep |
character seperating the data columns. Ignored when chunkFormatter is given. |
strict |
logical. Whether the parser should run in strict mode. Ignored when chunkFormatter is given. |
header |
logical indicating whether the first line of data, after skip if provided, contains variable names. Ignored if chunkFormatter is also provided. |
levels |
a named list, with names corresponding to the colNames of class character (or factor). Each element gives the levels for the corresponding variable. These will be automatically determined when missing. |
nrowsClasses |
number of rows to pull for determining colClasses and factor levels when needed; will only be grabbed from the first file or connection if multiple are passed. |
An abstract data frame object.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | n <- 100
test_df <- data.frame(col1 = sample(state.abb,n,TRUE),
col2 = sample(1:10,n,TRUE),
col3 = runif(n),
col4 = complex(n,runif(n),runif(n)),
stringsAsFactors = FALSE)
write.table(test_df, tf <- tempfile(), sep = "|",
quote = FALSE, row.names = FALSE, col.names = FALSE)
write.table(test_df, tf2 <- tempfile(), sep = "|",
quote = FALSE, row.names = FALSE, col.names = FALSE)
adfObj <- adf(c(tf,tf2))
unlink(tf)
unlink(tf2)
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