SwimmeR (version 0.14.2)

splits_to_lap: Converts splits from cumulative to lap format

Description

Cumulative splits are when each split is the total elapsed time at a given distance. For example, if an athlete swims the first 50 of a 200 yard race in 25.00 seconds (lap and cumulative split), and the second 50 (i.e. the 100 lap split) in 30.00 seconds the cumulative 100 split is 25.00 + 30.00 = 55.00. Some swimming results are reported with lap splits (preferred), but others use cumulative splits. This function converts cumulative splits to lap splits.

Usage

splits_to_lap(df, threshold = -Inf)

Value

a data frame with all splits in lap form

Arguments

df

a data frame containing results with splits in cumulative format. Must be formatted in a "normal" SwimmeR fashion - see vignette

threshold

a numeric value below which a split is taken to be cumulative. Default is -Inf

See Also

splits_to_lap is the reverse of splits_to_cumulative

Examples

if (FALSE) {
df <- data.frame(Place = 1,
                Name = "Sally Swimfast",
                Team = "KVAC",
                Event = "Womens 200 Freestyle",
                Finals_Time = "1:58.00",
                Split_50 = "28.00",
                Split_100 = "59.00",
                Split_150 = "1:31.00",
                Split_200 = "1:58.00")

df %>%
 splits_to_lap

df <- data.frame(Place = rep(1, 2),
                Name = c("Lenore Lap", "Casey Cumulative"),
                Team = rep("KVAC", 2),
                Event = rep("Womens 200 Freestyle", 2),
                Finals_Time = rep("1:58.00", 2),
                Split_50 = rep("28.00", 2),
                Split_100 = c("31.00", "59.00"),
                Split_150 = c("30.00", "1:29.00"),
                Split_200 = c("29.00", "1:58.00")
               )

 # since one entry is in lap time and the other is cumulative, need to
 # set threshold value

 # not setting threshold will produce bad results by attempting to convert
 # Lenore Lap's splits, which are already in lap format, into lap format
 # again

 df %>%
   splits_to_lap()

 df %>%
   splits_to_lap(threshold = 35)

 }