Cut outliers based on minimum and maximum limits of ConnectionHours and ConnectionStartDateTime variables

Usage

cut_sessions(
  sessions,
  connection_hours_min = NA,
  connection_hours_max = NA,
  connection_start_min = NA,
  connection_start_max = NA,
  log = FALSE,
  start = getOption("evprof.start.hour")
)

Arguments

sessions: tibble, sessions data set in evprof standard format.
connection_hours_min: numeric, minimum of connection hours (duration). If NA the minimum value is considered.
connection_hours_max: numeric, maximum of connection hours (duration). If NA the maximum value is considered.
connection_start_min: numeric, minimum hour of connection start (hour as numeric). If NA the minimum value is considered.
connection_start_max: numeric, maximum hour of connection start (hour as numeric). If NA the maximum value is considered.
log: logical, whether to transform ConnectionStartDateTime and ConnectionHours variables to natural logarithmic scale (base = exp(1)).
start: integer, start hour in the x axis of the plot.

Value

session dataframe

Examples

library(dplyr)
# Localize the outlying sessions above a certain threshold
california_ev_sessions %>%
  sample_frac(0.05) %>%
  plot_points(start = 3)


# For example sessions that start before 5 AM or that are
# longer than 20 hours are considered outliers
sessions_clean <- california_ev_sessions %>%
  sample_frac(0.05) %>%
  cut_sessions(
    start = 3,
    connection_hours_max = 20,
    connection_start_min = 5
  )
plot_points(sessions_clean, start = 3)