R/snackapp_usage_week_summary.R

In lboro-climb/snackapp.usage: snackapp.usage

#' seven_day_summary
#' 
#' @description A function to generate a summary of SnackApp usage data weekly
#'
#' @param data A dataframe of SnackApp usage data
#'
#' @return A dataframe summarising SnackApp usage data weekly
#' @export
#'
#' @examples
seven_day_summary <- function(data){
  df <- data
  df <- df %>%
    dplyr::group_by(id) %>%
    dplyr::mutate(
      id = as.numeric(id),
      date = as.POSIXct(date),
      date_lag = dplyr::lag(date),
      diff = difftime(date, date_lag, units = "sec"),
      day = as.integer(as.Date(date, format = "%d/%m/%Y") - min(as.Date(date, format = "%d/%m/%Y"))),
      week = dplyr::case_when(
        day <= 6 ~ 1,
        day <= 13 ~ 2,
        day <= 20 ~ 3,
        day <= 27 ~ 4,
        day <= 34 ~ 5,
        day <= 41 ~ 6,
        day <= 48 ~ 7,
        day <= 55 ~ 8,
        day <= 62 ~ 9,
        day <= 69 ~ 10
      ),
      day_of_week = lubridate::wday(date)
    )

  state_change_summary <- df %>%
    dplyr::filter(Event == "app-state-changed") %>%
    dplyr::filter(Metric == "background")

  df$my_stat <- dplyr::lag(dplyr::if_else(stringr::str_detect(df$Metric, "my-stat"), 1, 0))
  df$stat_diff <- dplyr::lead(dplyr::if_else(df$my_stat == 1, as.numeric(difftime(df$date, df$date_lag, units = "sec")), 0), 1)
  
  df$my_goals <- dplyr::lag(dplyr::if_else(stringr::str_detect(df$Metric, "my-goal"), 1, 0))
  df$goal_diff <- dplyr::lead(dplyr::if_else(df$my_goals == 1, as.numeric(difftime(df$date, df$date_lag, units = "sec")), 0), 1)
  
  df$forum <- dplyr::lag(dplyr::if_else(stringr::str_detect(df$Metric, "forum"), 1, 0))
  df$forum_diff <- dplyr::lead(dplyr::if_else(df$forum == 1, as.numeric(difftime(df$date, df$date_lag, units = "sec")), 0), 1)
  
  df$case_studies <- dplyr::lag(dplyr::if_else(stringr::str_detect(df$Metric, "case-studies"), 1, 0))
  df$case_studies_diff <- dplyr::lead(dplyr::if_else(df$case_studies == 1, as.numeric(difftime(df$date, df$date_lag, units = "sec")), 0), 1)
  
  df$planner <- dplyr::lag(dplyr::if_else(stringr::str_detect(df$Metric, "planner"), 1, 0))
  df$planner_diff <- dplyr::lead(dplyr::if_else(df$planner == 1, as.numeric(difftime(df$date, df$date_lag, units = "sec")), 0), 1)
  
  df$case_studies <- dplyr::lag(dplyr::if_else(stringr::str_detect(df$Metric, "case-studies"), 1, 0))
  df$case_studies_diff <- dplyr::lead(dplyr::if_else(df$case_studies == 1, as.numeric(difftime(df$date, df$date_lag, units = "sec")), 0), 1)
  
  df$faq <- dplyr::lag(dplyr::if_else(stringr::str_detect(df$Metric, "faq"), 1, dplyr::if_else(stringr::str_detect(df$Metric, "onboarding"), 0, 0)))
  df$faq_diff <- dplyr::lead(dplyr::if_else(df$faq == 1, as.numeric(difftime(df$date, df$date_lag, units = "sec")), 0), 1)
  
  df$dashboard <- dplyr::lag(dplyr::if_else(stringr::str_detect(df$Metric, "dashboard"), 1, 0))
  df$dashboard_diff <- dplyr::lead(dplyr::if_else(df$dashboard == 1, as.numeric(difftime(df$date, df$date_lag, units = "sec")), 0), 1)
  
  df$profile <- dplyr::lag(dplyr::if_else(stringr::str_detect(df$Metric, "profile"), 1, 0))
  df$profile_diff <- dplyr::lead(dplyr::if_else(df$profile == 1, as.numeric(difftime(df$date, df$date_lag, units = "sec")), 0), 1)
  
  df$onboarding <- dplyr::lag(dplyr::if_else(stringr::str_detect(df$Metric, "onboarding"), 1, 0))
  df$onboarding_diff <- dplyr::lead(dplyr::if_else(df$onboarding == 1, as.numeric(difftime(df$date, df$date_lag, units = "sec")), 0), 1)
  
  df$notifications <- dplyr::if_else(stringr::str_detect(df$Event, "notification"), 1, 0)

  df[, 13:31][df[, 13:31] == 0] <- NA

  state_change_summary_weekly <- state_change_summary %>%
    dplyr::group_by(id, week) %>%
    dplyr::summarise(
      weekly_total_time = as.numeric(sum(diff, na.rm = TRUE)),
      weekly_average_time = as.numeric(mean(diff, na.rm = TRUE))
    )

  state_change_summary_weekday <- state_change_summary %>%
    dplyr::filter(day_of_week <= 5) %>%
    dplyr::group_by(id, week) %>%
    dplyr::summarise(
      weekday_total_time = as.numeric(sum(diff, na.rm = TRUE)),
      weekday_average_time = as.numeric(mean(diff, na.rm = TRUE))
    )

  state_change_summary_weekend <- state_change_summary %>%
    dplyr::filter(day_of_week >= 5) %>%
    dplyr::group_by(id, week) %>%
    dplyr::summarise(
      weekend_total_time = as.numeric(sum(diff, na.rm = TRUE)),
      weekend_average_time = as.numeric(mean(diff, na.rm = TRUE))
    )

  usage_summary <- df %>%
    dplyr::group_by(id, week) %>%
    dplyr::summarise(
      total_stat = sum(stat_diff, na.rm = TRUE),
      total_goal = sum(goal_diff, na.rm = TRUE),
      total_forum = sum(forum_diff, na.rm = TRUE),
      total_case_studies = sum(case_studies_diff, na.rm = TRUE),
      total_planner = sum(planner_diff, na.rm = TRUE),
      total_case_studies = sum(case_studies_diff, na.rm = TRUE),
      total_faq = sum(faq_diff, na.rm = TRUE),
      total_dashboard = sum(dashboard_diff, na.rm = TRUE),
      total_profile = sum(profile_diff, na.rm = TRUE),
      total_onboarding = sum(onboarding_diff, na.rm = TRUE),
      average_stat = sum(stat_diff, na.rm = TRUE) / sum((df[cumsum(rle(df$my_stat)$lengths), ]$my_stat == 1) == TRUE, na.rm = TRUE),
      average_goal = sum(goal_diff, na.rm = TRUE) / sum((df[cumsum(rle(df$my_goals)$lengths), ]$my_goals == 1) == TRUE, na.rm = TRUE),
      average_forum = sum(forum_diff, na.rm = TRUE) / sum((df[cumsum(rle(df$forum)$lengths), ]$forum == 1) == TRUE, na.rm = TRUE),
      average_case_studies = sum(case_studies_diff, na.rm = TRUE) / sum((df[cumsum(rle(df$case_studies)$lengths), ]$case_studies == 1) == TRUE, na.rm = TRUE),
      average_planner = sum(planner_diff, na.rm = TRUE) / sum((df[cumsum(rle(df$planner)$lengths), ]$planner == 1) == TRUE, na.rm = TRUE),
      average_faq = sum(faq_diff, na.rm = TRUE) / sum((df[cumsum(rle(df$faq)$lengths), ]$faq == 1) == TRUE, na.rm = TRUE),
      average_dashboard = sum(dashboard_diff, na.rm = TRUE) / sum((df[cumsum(rle(df$dashboard)$lengths), ]$dashboard == 1) == TRUE, na.rm = TRUE),
      average_profile = sum(profile_diff, na.rm = TRUE) / sum((df[cumsum(rle(df$profile)$lengths), ]$profile == 1) == TRUE, na.rm = TRUE),
      average_onboarding = sum(onboarding_diff, na.rm = TRUE) / sum((df[cumsum(rle(df$onboarding)$lengths), ]$onboarding == 1) == TRUE, na.rm = TRUE),
      stdev_stat = sd(stat_diff, na.rm = TRUE),
      stdev_goal = sd(goal_diff, na.rm = TRUE),
      stdev_forum = sd(forum_diff, na.rm = TRUE),
      stdev_case_studies = sd(case_studies_diff, na.rm = TRUE),
      stdev_planner = sd(planner_diff, na.rm = TRUE),
      stdev_case_studies = sd(case_studies_diff, na.rm = TRUE),
      stdev_faq = sd(faq_diff, na.rm = TRUE),
      stdev_dashboard = sd(dashboard_diff, na.rm = TRUE),
      stdev_profile = sd(profile_diff, na.rm = TRUE),
      stdev_onboarding = sd(onboarding_diff, na.rm = TRUE),
      notificaition_count = sum(notifications)
    )

  usage_summary[usage_summary < 0] <- NA
  usage_summary <- do.call(data.frame, lapply(usage_summary, function(x) replace(x, is.infinite(x), NA)))
  usage_summary[is.na(usage_summary)] <- 0
  usage_summary$id <- as.numeric(usage_summary$id)
  usage_summary <- round(usage_summary, digits = 2)

  bouts <- weekly_snack_count(df)

 results <- dplyr::full_join(state_change_summary_weekly, state_change_summary_weekday, by = c("id" = "id", "week" = "week")) %>%
   dplyr::full_join(state_change_summary_weekend, by = c("id" = "id", "week" = "week")) %>%
   dplyr::full_join(usage_summary, by = c("id" = "id", "week" = "week")) %>%
   dplyr::full_join(bouts, by = c("id" = "id", "week" = "week"))
 return(results)
}