(This article was first published on

**Yet Another Blog in Statistical Computing » S+/R**, and kindly contributed to R-bloggers)In R, there are two ways to read a block of the spreadsheet, e.g. xlsx file, as the one shown below.

The xlsx package provides the most intuitive interface with readColumns() function by explicitly defining the starting and the ending columns and rows.

library(xlsx) file <- loadWorkbook("C:\Documents and Settings\Administrator\Desktop\test.xlsx") df1 <- readColumns(getSheets(file)[[1]], startColumn = 3, endColumn = 5, startRow = 5, endRow = 8, header = T) df1 # X Y Z # 1 1 A 2015-01-01 # 2 2 B 2015-02-01 # 3 3 C 2015-03-01

However, if we can define a named range for the block in the excel, the XLConnect package might be more convenient. In the example below, we first defined a range named as “block” within the spreadsheet and then called this named range with readNamedRegionFromFile() function without the necessity of specifying rows and columns.

library(XLConnect) df2 <- readNamedRegionFromFile("C:\Documents and Settings\Administrator\Desktop\test.xlsx", "block") df2 # X Y Z # 1 1 A 2015-01-01 # 2 2 B 2015-02-01 # 3 3 C 2015-03-01

To

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