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Cumulative minimum of specified columns by group

uby_cum_min.Rd

Creates a cumulative minimum UpdateByOp that computes the cumulative minimum of each column in cols for each aggregation group.

Arguments

cols

String or list of strings denoting the column(s) to operate on. Can be renaming expressions, i.e. “new_col = col”. Default is to compute the cumulative minimum for all non-grouping columns.

Value

UpdateByOp to be used in a call to update_by().

Details

This function acts on aggregation groups specified with the by parameter of the update_by() caller function. The aggregation groups are defined by the unique combinations of values in the by columns. For example, if by = c("A", "B"), then the aggregation groups are defined by the unique combinations of values in the A and B columns.

This function, like other Deephaven uby functions, is a generator function. That is, its output is another function called an UpdateByOp intended to be used in a call to update_by(). This detail is typically hidden from the user. However, it is important to understand this detail for debugging purposes, as the output of a uby function can otherwise seem unexpected.

For more information, see the vignette on uby functions by running vignette("update_by").

Examples

if (FALSE) { # \dontrun{
library(rdeephaven)

# connecting to Deephaven server
client <- Client$new("localhost:10000", auth_type = "psk", auth_token = "my_secret_token")

# create data frame, push to server, retrieve TableHandle
df <- data.frame(
  timeCol = seq.POSIXt(as.POSIXct(Sys.Date()), as.POSIXct(Sys.Date() + 0.01), by = "1 sec")[1:500],
  boolCol = sample(c(TRUE, FALSE), 500, TRUE),
  col1 = sample(10000, size = 500, replace = TRUE),
  col2 = sample(10000, size = 500, replace = TRUE),
  col3 = 1:500
)
th <- client$import_table(df)

# compute cumulative minimum of col1 and col2
th1 <- th$
  update_by(uby_cum_min(c("col1CumMin = col1", "col2CumMin = col2")))

# compute cumulative minimum of col1 and col2, grouped by boolCol
th2 <- th$
  update_by(uby_cum_min(c("col1CumMin = col1", "col2CumMin = col2")), by = "boolCol")

# compute cumulative minimum of col1 and col2, grouped by boolCol and parity of col3
th3 <- th$
  update("col3Parity = col3 % 2")$
  update_by(uby_cum_min(c("col1CumMin = col1", "col2CumMin = col2")), by = c("boolCol", "col3Parity"))

client$close()
} # }