plot_model_clusters {evprof}

Plot all bi-variable GMM (clusters) with the colors corresponding to the assigned user profile. This shows which clusters correspond to which user profile, and the proportion of every user profile.

Description

Plot all bi-variable GMM (clusters) with the colors corresponding to the assigned user profile. This shows which clusters correspond to which user profile, and the proportion of every user profile.

Usage

plot_model_clusters(
  subsets_clustering = list(),
  clusters_definition = list(),
  profiles_ratios,
  log = TRUE
)

Arguments

subsets_clustering

list with clustering results of each subset (direct output from function cluser_sessions())

clusters_definition

list of tibbles with clusters definitions (direct output from function define_clusters()) of each sub-set

profiles_ratios

tibble with columns profile and ratio

log

logical, whether to transform ConnectionStartDateTime and ConnectionHours variables to natural logarithmic scale (base = exp(1)).

Value

ggplot2

Examples

library(dplyr)

# Select working day sessions (`Timecycle == 1`) that
# disconnect the same day (`Disconnection == 1`)
sessions_day <- evprof::california_ev_sessions_profiles %>%
  filter(Timecycle == "Workday") %>%
  sample_frac(0.05)
plot_points(sessions_day, start = 3)

# Identify two clusters
sessions_clusters <- cluster_sessions(
  sessions_day, k=2, seed = 1234, log = TRUE
)

# Plot the clusters found
plot_bivarGMM(
  sessions = sessions_clusters$sessions,
  models = sessions_clusters$models,
  log = TRUE, start = 3
)

# Define the clusters with user profile interpretations
clusters_definitions <- define_clusters(
  models = sessions_clusters$models,
  interpretations = c(
    "Connections during all day (high variability)",
    "Connections during working hours"#'
  ),
  profile_names = c("Visitors", "Workers"),
  log = TRUE
)

# Create a table with the connection GMM parameters
connection_models <- get_connection_models(
  subsets_clustering = list(sessions_clusters),
  clusters_definition = list(clusters_definitions)
)

# Plot all bi-variable GMM (clusters) with the colors corresponding
# to their assigned user profile
plot_model_clusters(
  subsets_clustering = list(sessions_clusters),
  clusters_definition = list(clusters_definitions),
  profiles_ratios = connection_models[c("profile", "ratio")]
)