Nothing
# Pivot table summarizes and analyzes large quantities of data
test_that("datPivot Testing", {
skip_on_cran()
# Using datPivot - from vignette
test1 <- datPivot(x = WYtree,
pvar = "HT", ##Height
xvar = "SPGRPCD", ##Species Group Code
yvar = "TREECLCD", ##Tree Class Code
pfun = mean) ##Name of function to use for pivot values
# Using datPivot - from Tracy's Example
test2 <- datPivot(x = WYtree,
pvar = "VOLCFNET",
xvar = "PLT_CN",
yvar = "SPCD",
xfilter = "STATUSCD == 1")
CN <- 40404730010690
test2_subset <- round(test2[test2$PLT_CN == CN, "X113",][[1]], 2)
test2_subset_char <- as.character(test2_subset)
input1 <- WYtree[WYtree$PLT_CN == CN, ]
input2 <- round(sum(input1[input1$SPCD == 113 & input1$STATUSCD == 1, "VOLCFNET"]), 2)
input3_final <- formatC(input2)
expect_equal(test2_subset_char, input3_final)
expect_equal(dim(test1), c(10,4))
expect_snapshot(test1)
})
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