diff --git a/NAMESPACE b/NAMESPACE
index 5ae87f8..2be2d25 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,6 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
 export("%>%")
+export(create_app_daily_session_chart)
 export(create_app_daily_usage_chart)
 export(create_app_ranking)
 export(create_app_ranking_table)
@@ -34,6 +35,7 @@ export(sort_users_by_role)
 import(apexcharter)
 import(dplyr)
 import(echarts4r)
+import(lubridate)
 import(purrr)
 import(toastui)
 import(visNetwork)
diff --git a/R/helpers-charts.R b/R/helpers-charts.R
index 94a3d3c..e250ad1 100644
--- a/R/helpers-charts.R
+++ b/R/helpers-charts.R
@@ -16,16 +16,23 @@
 #' @import echarts4r
 #' @importFrom shiny validate need is.reactive
 create_calendar_chart <- function(
-  calendar_data,
-  title,
-  subtitle = NULL,
-  start_date = NULL,
-  end_date = NULL,
-  callback = NULL
+    calendar_data,
+    title,
+    subtitle = NULL,
+    start_date = NULL,
+    end_date = NULL,
+    callback = NULL
 ) {
 
   Date <- Freq <- NULL
 
+  tryCatch({
+    session <- get("session", parent.frame(2))
+    ns <- session$ns
+  }, error = function(e) {
+    ns <- identity
+  })
+
   renderEcharts4r({
     validate(need(nrow(calendar_data()) > 0, "No calendar data found ..."))
     if (is.reactive(calendar_data)) calendar_data <- calendar_data()
@@ -51,7 +58,16 @@ create_calendar_chart <- function(
       ) %>%
       e_title(title, subtitle) %>%
       e_tooltip() %>%
-      e_legend(show = FALSE)
+      e_legend(show = FALSE) %>%
+      e_on(
+        list(),
+        sprintf(
+          "function(e) {
+            Shiny.setInputValue('%s', e.data.value[0], {priority: 'event'});
+          }",
+          ns("selected_date")
+        )
+      )
 
     if (!is.null(callback)) {
       calendar_chart %>% htmlwidgets::onRender(callback)
@@ -70,13 +86,64 @@ create_calendar_chart <- function(
 #' See \url{https://echarts4r.john-coene.com/articles/chart_types.html#calendar-1}.
 #'.
 #' @param app_usage Returned by \link{get_app_daily_usage}.
+#' @param ... Pass down any param to \link{create_calendar_chart}.
 #' @return A calendar chart displaying daily app usage.
 #' @export
-create_app_daily_usage_chart <- function(app_usage) {
-  create_calendar_chart(app_usage, "Overall app usage")
+create_app_daily_usage_chart <- function(app_usage, ...) {
+  create_calendar_chart(app_usage, "Overall app usage", "units: user sessions/day", ...)
 }
 
 
+#' Generic calendar chart generator
+#'
+#' @param calendar_data Calendar chart data.
+#' @param title Chart title.
+#' @param subtitle Chart subtitle.
+#' @param start_date Default to minimum calendar_data date. Could also be
+#' an input value with Shiny.
+#' @param end_date Default to maximum calendar_data date. Could also be
+#' an input value with Shiny.
+#' @param callback JS function to pass to \link[htmlwidgets]{onRender}. This is
+#' useful to access the widget API on the R side at render time
+#' and add events on the fly.
+#'
+#' @return An echarts4r line chart
+#' @export
+create_app_daily_session_chart <- function(
+  calendar_data,
+  title = "Cumulated daily usage",
+  subtitle = "time units: minutes",
+  start_date = NULL,
+  end_date = NULL,
+  callback = NULL
+) {
+
+  cum_dur <- NULL
+
+  renderEcharts4r({
+    validate(need(nrow(calendar_data()) > 0, "No calendar data found ..."))
+    if (is.reactive(calendar_data)) calendar_data <- calendar_data()
+    if (is.null(start_date)) start_date <- min(calendar_data$Date)
+    if (is.null(end_date)) end_date <- max(calendar_data$Date)
+    if (is.reactive(start_date)) start_date <- start_date()
+    if (is.reactive(end_date)) end_date <- end_date()
+    if (is.reactive(title)) title <- title()
+
+    usage_chart <- calendar_data %>%
+      filter(.data$Date >= start_date & .data$Date <= end_date) %>%
+      e_charts(Date) %>%
+      e_line(cum_dur) %>%
+      e_title(title, subtitle) %>%
+      e_tooltip() %>%
+      e_legend()
+
+    if (!is.null(callback)) {
+      usage_chart %>% htmlwidgets::onRender(callback)
+    } else {
+      usage_chart
+    }
+  })
+}
 
 
 #' Daily app consumption for selected user
@@ -111,10 +178,10 @@ create_user_daily_consumption_chart <- function(usage) {
 #' @importFrom rlang .data
 #' @importFrom shiny req is.reactive
 create_cumulated_duration_per_user <- function(
-  apps_usage,
-  start_date = NULL,
-  end_date = NULL,
-  selected_app) {
+    apps_usage,
+    start_date = NULL,
+    end_date = NULL,
+    selected_app) {
 
   username <- cum_duration <- NULL
 
@@ -128,8 +195,8 @@ create_cumulated_duration_per_user <- function(
     apps_usage %>%
       filter(
         .data$started >= start_date &
-        .data$started <= end_date &
-        .data$app_name == !!selected_app()
+          .data$started <= end_date &
+          .data$app_name == !!selected_app()
       ) %>%
       group_by(.data$username) %>%
       summarise(cum_duration = as.numeric(round(sum(.data$duration) / 3600, 1))) %>%
@@ -165,10 +232,10 @@ create_cumulated_duration_per_user <- function(
 #' @importFrom rlang .data
 #' @importFrom shiny req is.reactive
 create_cumulated_hits_per_user <- function(
-  apps_usage,
-  start_date = NULL,
-  end_date = NULL,
-  selected_app
+    apps_usage,
+    start_date = NULL,
+    end_date = NULL,
+    selected_app
 ) {
 
   username <- NULL
@@ -183,8 +250,8 @@ create_cumulated_hits_per_user <- function(
     apps_usage %>%
       filter(
         .data$started >= start_date &
-        .data$started <= end_date &
-        .data$app_name == !!selected_app()
+          .data$started <= end_date &
+          .data$app_name == !!selected_app()
       ) %>%
       group_by(.data$username) %>%
       summarise(n = n()) %>% # prefer summarize over sort to remove grouping
diff --git a/R/helpers-data.R b/R/helpers-data.R
index 808b84b..c35c88f 100644
--- a/R/helpers-data.R
+++ b/R/helpers-data.R
@@ -3,15 +3,15 @@
 #' @param app app_name to filter.
 #' @param logs Given by RSC database.
 #'
-#' @return A vector containing dates of usage for
-#' the given app.
+#' @return A tibble containing dates of usage for
+#' the given app as well as the correponding session duration.
 #' @import dplyr
 #' @export
 #' @importFrom rlang .data
 get_rsc_app_dates <- function(app, logs) {
   logs %>%
     filter(.data$app_name == !!app) %>%
-    pull(.data$started)
+    select(.data$started, .data$duration)
 }
 
 
@@ -22,7 +22,7 @@ get_rsc_app_dates <- function(app, logs) {
 #' @param logs Given by RSC database.
 #'
 #' @return A 3 columns tibble with app name, usage and date of usage (nested tibble).
-#' @import dplyr purrr
+#' @import dplyr purrr lubridate
 #' @export
 #' @importFrom rlang .data
 get_rsc_apps_usage <- function(logs) {
@@ -31,7 +31,6 @@ get_rsc_apps_usage <- function(logs) {
   tmp_apps_usage <- logs %>%
     group_by(.data$app_name) %>%
     count(sort = TRUE)
-
   # handle dates. It's quite heavy but we need for
   # each app the dates of usage and a count for each date.
   # Reason why we use table(). We also need to nest them
@@ -44,19 +43,29 @@ get_rsc_apps_usage <- function(logs) {
     get_rsc_app_dates,
     logs
   ) %>%
-    map(tibble::as_tibble) %>%
     map(
       ~ {
-        tbl <- ..1 %>%
+        dat_in <- ..1 %>%
           # Be careful, RSC provides datetime format but
           # this is too specific to count at the scale of a day.
           # We must floor to the corresponding day.
-          mutate(value = lubridate::floor_date(value, "day")) %>%
+          mutate(started = floor_date(.data$started, "day"))
+
+        tbl <- dat_in %>%
+          select(-.data$duration) %>%
           table() %>%
           tibble::as_tibble()
 
         names(tbl) <- c("Date", "Freq")
-        tbl
+
+        # Create duration table
+        cumulated_durations <- do.call(rbind.data.frame, map(tbl$Date, ~ {
+          dat_in %>%
+            filter(started == as_datetime(..1)) %>%
+            summarise(cum_dur = minute(seconds_to_period(sum(.data$duration, na.rm = TRUE))))
+        }))
+
+        cbind(tbl, cumulated_durations)
       }
     ) %>%
     map(nest_by, .key = "calendar_data") %>%
@@ -270,7 +279,7 @@ get_user_daily_consumption <- function(content, users, apps, selected_user) {
   grouped_by_date <- reactive({
     req(nrow(events()) > 0)
     events() %>%
-      mutate(floored_started = lubridate::floor_date(.data$started, "day")) %>%
+      mutate(floored_started = floor_date(.data$started, "day")) %>%
       group_by(.data$floored_started) %>%
       count(sort = TRUE) %>%
       select(Date = .data$floored_started, Freq = .data$n)
@@ -284,6 +293,10 @@ get_user_daily_consumption <- function(content, users, apps, selected_user) {
 #' See \link{create_app_ranking_table}.
 #'
 #' @inheritParams merge_rsc_data
+#' @param start_date Default to minimum calendar_data date. Could also be
+#' an input value with Shiny.
+#' @param end_date Default to maximum calendar_data date. Could also be
+#' an input value with Shiny.
 #'
 #' @return A list containing: `[[1]]` merged data between app usage and users data.
 #' `[[2]]`: data to be digested by \link{create_app_ranking_table}.
@@ -291,9 +304,21 @@ get_user_daily_consumption <- function(content, users, apps, selected_user) {
 #' @import dplyr
 #' @importFrom rlang .data quo eval_tidy
 #' @importFrom shiny reactive is.reactive
-create_app_ranking <- function(content, users, apps) {
+create_app_ranking <- function(content, users, apps, start_date = NULL, end_date = NULL) {
   tmp <- quo({
     rsc_data_merged <- merge_rsc_data(content, users, apps)
+    if (is.null(start_date)) start_date <- min(rsc_data_merged$apps_usage_merged$started)
+    # Note: this might be surprising but some end date are not available in ended so
+    # we have to take the max of the start date.
+    if (is.null(end_date)) end_date <- max(rsc_data_merged$apps_usage_merged$started)
+    if (is.reactive(start_date)) start_date <- start_date()
+    if (is.reactive(end_date)) end_date <- end_date()
+
+    rsc_data_merged[[3]] <- rsc_data_merged[[3]] %>%
+      filter(
+        .data$started >= start_date &
+          .data$started <= end_date
+      )
 
     processed_rsc_apps_usage <- rsc_data_merged[[3]] %>%
       get_rsc_apps_usage() %>%
@@ -308,7 +333,8 @@ create_app_ranking <- function(content, users, apps) {
     list(rsc_data_merged[[3]], processed_rsc_apps_usage)
   })
 
-  if (is.reactive(users) || is.reactive(content) || is.reactive(apps)) {
+  if (is.reactive(users) || is.reactive(content) || is.reactive(apps) ||
+      is.reactive(start_date) || is.reactive(end_date)) {
     if (is.reactive(users)) user <- users()
     if (is.reactive(content)) content <- content()
     if (is.reactive(apps)) apps <- apps()
@@ -396,15 +422,22 @@ create_dev_ranking <- function(users, content) {
 #' Sort RStudio Connect users by role
 #'
 #' Users are grouped by user_role to check the
-#' server role repartition.
+#' server role repartition. Using start_date and end_date allows
+#' to filter data given a specific time range.
 #'
 #' @param users Get from \link[connectapi]{get_users}.
+#' @param start_date Date filter.
+#' @param end_date Date filter.
 #'
 #' @return A tibble with user grouped by role.
 #' @export
 #' @importFrom rlang .data
-sort_users_by_role <- function(users) {
+sort_users_by_role <- function(users, start_date = NULL, end_date = NULL) {
+  if (is.null(start_date)) start_date <- min(users$created_time)
+  if (is.null(end_date)) end_date <- max(users$created_time)
+
   users %>%
+    filter(.data$created_time >= start_date & .data$created_time <= end_date) %>%
     group_by(.data$user_role) %>%
     summarize(n = n()) %>%
     mutate(Percentage = round(n / sum(n) * 100))
@@ -415,12 +448,17 @@ sort_users_by_role <- function(users) {
 #'
 #'
 #' @param content Get from \link[connectapi]{get_content}.
+#' @inheritParams sort_users_by_role
 #'
 #' @return A tibble with content grouped by access type.
 #' @export
 #' @importFrom rlang .data
-sort_content_by_access <- function(content) {
+sort_content_by_access <- function(content, start_date = NULL, end_date = NULL) {
+  if (is.null(start_date)) start_date <- min(content$created_time)
+  if (is.null(end_date)) end_date <- max(content$created_time)
+
   content %>%
+    filter(.data$created_time >= start_date & .data$created_time <= end_date) %>%
     group_by(.data$access_type) %>%
     summarize(n = n()) %>%
     mutate(Percentage = round(n / sum(n) * 100))
@@ -432,13 +470,21 @@ sort_content_by_access <- function(content) {
 #'
 #'
 #' @param content Get from \link[connectapi]{get_content}.
+#' @inheritParams sort_users_by_role
 #'
 #' @return A tibble with content grouped by R version.
 #' @export
 #' @importFrom rlang .data
-sort_content_by_rversion <- function(content) {
+sort_content_by_rversion <- function(content, start_date = NULL, end_date = NULL) {
+  if (is.null(start_date)) start_date <- min(content$created_time)
+  if (is.null(end_date)) end_date <- max(content$created_time)
+
   content %>%
-    filter(!is.na(.data$r_version)) %>%
+    filter(
+      !is.na(.data$r_version) &
+      .data$created_time >= start_date &
+      .data$created_time <= end_date
+    ) %>%
     group_by(.data$r_version) %>%
     summarize(n = n()) %>%
     mutate(Percentage = round(n / sum(n) * 100, 1))
@@ -464,12 +510,17 @@ sort_content_by_pyversion <- function(content) {
 #'
 #'
 #' @param content Get from \link[connectapi]{get_content}.
+#' @inheritParams sort_users_by_role
 #'
 #' @return A tibble with content grouped by app mode.
 #' @export
 #' @importFrom rlang .data
-sort_content_by_appmode <- function(content) {
+sort_content_by_appmode <- function(content, start_date = NULL, end_date = NULL) {
+  if (is.null(start_date)) start_date <- min(content$created_time)
+  if (is.null(end_date)) end_date <- max(content$created_time)
+
   content %>%
+    filter(.data$created_time >= start_date & .data$created_time <= end_date) %>%
     group_by(.data$app_mode) %>%
     summarize(n = n()) %>%
     mutate(Percentage = round(n / sum(n) * 100, 1))
diff --git a/R/helpers-tables.R b/R/helpers-tables.R
index f70654d..c6660be 100644
--- a/R/helpers-tables.R
+++ b/R/helpers-tables.R
@@ -74,13 +74,13 @@ create_table_sparkline <- function(table) {
       column = "calendar_data",
       renderer = function(data) {
         data$Month <- data$Date %>% purrr::map(~ {
-          lubridate::month(..1, label = TRUE)
+          month(..1, label = TRUE)
         }) %>%
           unlist() %>%
           as.character()
 
         data$Month_code <- data$Date %>% purrr::map_dbl(~ {
-          lubridate::month(..1)
+          month(..1)
         })
 
         # gather by month since it is too laggy
@@ -116,5 +116,6 @@ create_table_sparkline <- function(table) {
 #' usage.
 #' @export
 create_app_ranking_table <- function(ranking, pagination = 10, height = NULL) {
+  if (is.reactive(ranking)) ranking <- ranking()
   ranking[[2]] %>% generate_table(sparkline = TRUE, pagination, height)
 }
diff --git a/inst/examples/shiny/app.R b/inst/examples/shiny/app.R
new file mode 100644
index 0000000..4404840
--- /dev/null
+++ b/inst/examples/shiny/app.R
@@ -0,0 +1,313 @@
+library(shiny)
+library(connectapi) # Tested with 0.1.0.9031
+library(connectViz)
+library(dplyr)
+library(bslib)
+library(echarts4r)
+library(toastui)
+library(visNetwork)
+
+rsc_client <- create_rsc_client()
+
+# TO DO: refresh this in the background
+apps_usage <- rsc_client %>% get_usage_shiny(limit = Inf)
+rsc_content <- rsc_client %>% get_content()
+# Remove locked users?
+rsc_users <- rsc_client %>% get_users(limit = Inf) %>%
+  filter(locked == FALSE)
+publishers <- rsc_users %>% filter(user_role == "publisher")
+shiny_apps <- rsc_content %>% filter(app_mode == "shiny")
+
+general_metrics <- list(
+  "Onboarded Users" = nrow(rsc_users),
+  "Publishers" = nrow(publishers),
+  "Deployments" = nrow(rsc_content),
+  "Shiny Apps" = nrow(shiny_apps)
+)
+
+general_metrics_cards <- purrr::map(
+  seq_along(general_metrics),
+  function(i) {
+    value_box(
+      theme_color = "secondary",
+      value = general_metrics[[i]],
+      title = names(general_metrics)[[i]]
+    )
+  }
+)
+
+developers_apps_ranking <- create_dev_ranking(rsc_users, rsc_content)
+max_app <- developers_apps_ranking %>% pull(n_apps) %>% max()
+
+ui <- page_navbar(
+  title = "Shiny apps usage",
+  sidebar = tagList(
+    dateRangeInput(
+      "date_range",
+      "Select the app usage range:",
+      start = min(rsc_content[["created_time"]]),
+      end = Sys.Date()
+    ),
+    span(
+      "About usage data",
+      tooltip(
+        icon("info-circle"),
+        "Important: with a standard Posit Connect API key, you can ONLY see the content
+        YOU OWN. Admin API key has access to ALL data."
+      )
+    )
+  ),
+  nav_panel(
+    "General metrics",
+    layout_columns(
+      fill = FALSE,
+      !!!general_metrics_cards
+    ),
+    layout_columns(
+      col_widths = rep(6, 4),
+      card(
+        card_header("User roles"),
+        full_screen = TRUE,
+        min_height = "400px",
+        echarts4rOutput("roles_chart"),
+      ),
+      card(
+        card_header("Content access type"),
+        full_screen = TRUE,
+        min_height = "400px",
+        echarts4rOutput("content_access"),
+      ),
+      card(
+        card_header("R versions"),
+        full_screen = TRUE,
+        min_height = "400px",
+        echarts4rOutput("r_versions"),
+      ),
+      card(
+        card_header("Content type"),
+        full_screen = TRUE,
+        min_height = "400px",
+        echarts4rOutput("content_type"),
+      )
+    )
+  ),
+  nav_panel(
+    "App data",
+    h3("Apps ranking"),
+    card(
+      full_screen = TRUE,
+      min_height = "400px",
+      datagridOutput("apps_ranking_chart")
+    ),
+    h3("Single app usage"),
+    card(
+      full_screen = TRUE,
+      min_height = "1200px",
+      layout_sidebar(
+        sidebar = sidebar(
+          width = 150,
+          selectInput(
+            "selected_app",
+            "Select an application",
+            choices = NULL
+          )
+        ),
+        echarts4rOutput("daily_usage_chart"),
+        dataTableOutput("daily_usage_table"),
+        echarts4rOutput("daily_sessions_chart"),
+        p("User consumption"),
+        echarts4rOutput("cumulated_duration_per_user_chart"),
+        echarts4rOutput("cumulated_hits_per_user_chart"),
+
+      )
+    )
+  ),
+  nav_panel(
+    "Consumer data",
+    card(
+      full_screen = TRUE,
+      min_height = "400px",
+      card_header("Consumer ranking"),
+      layout_sidebar(
+        sidebar = sidebar(
+          width = 150,
+          numericInput(
+            "views_threshold",
+            "N view threshold",
+            1,
+            min = 0
+          )
+        ),
+        echarts4rOutput("consumer_ranking_chart")
+      )
+    ),
+    card(
+      full_screen = TRUE,
+      min_height = "400px",
+      card_header("Daily app consumption"),
+      layout_sidebar(
+        sidebar = sidebar(
+          width = 150,
+          selectInput("selected_user", "Select a user", rsc_users$username)
+        ),
+        echarts4rOutput("daily_consumption_chart")
+      )
+    )
+  ),
+  nav_panel(
+    "Developer data",
+    card(
+      full_screen = TRUE,
+      min_height = "400px",
+      card_header("Developers ranking n deployments (static, shiny, rmd, ...)"),
+      layout_sidebar(
+        sidebar = sidebar(
+          width = 150,
+          numericInput(
+            "apps_threshold",
+            "N app threshold",
+            round(max_app / 2),
+            min = 1,
+            max = max_app
+          )
+        ),
+        echarts4rOutput("dev_ranking_chart")
+      )
+    ),
+    card(
+      full_screen = TRUE,
+      min_height = "400px",
+      card_header("Dev projects overview (Shiny apps only)"),
+      layout_sidebar(
+        sidebar = sidebar(
+          width = 150,
+          selectInput(
+            "app_developer",
+            "Select a developer",
+            developers_apps_ranking$username
+          )
+        ),
+        visNetworkOutput("dev_projects_network")
+      )
+    )
+  )
+)
+
+server <- function(input, output, session) {
+
+# Apps ranking ------------------------------------------------------------
+
+  apps_ranking <- create_app_ranking(
+    rsc_content,
+    rsc_users,
+    apps_usage,
+    start_date = reactive(input$date_range[1]),
+    end_date = reactive(input$date_range[2])
+  )
+
+  range_text <- reactive({
+    sprintf("between %s and %s", input$date_range[1], input$date_range[2])
+  })
+
+  output$app_usage_title <- renderText({
+    sprintf("Shiny Apps usage %s", range_text())
+  })
+
+  output$apps_ranking_chart <- renderDatagrid({
+    create_app_ranking_table(apps_ranking)
+  })
+
+# App usage ---------------------------------------------------------------
+
+  daily_app_usage <- get_app_daily_usage(reactive(apps_ranking()[[2]]), reactive(input$selected_app))
+
+  observeEvent(apps_ranking(), {
+    updateSelectInput(
+      session,
+      "selected_app",
+      choices = apps_ranking()[[2]]$app_name
+    )
+  })
+
+  output$daily_usage_chart <- create_app_daily_usage_chart(daily_app_usage)
+  output$daily_usage_table <- renderDataTable({
+    req(input$selected_date)
+    apps_ranking()[[1]] %>%
+      mutate(
+        started = lubridate::as_date(started),
+        duration = lubridate::minute(lubridate::seconds_to_period(duration))
+      ) %>%
+      filter(
+      .data$app_name == input$selected_app &
+      .data$started == input$selected_date
+    ) %>%
+      select(username, duration)
+  }, options = list(colnames = c("duration (in minutes)" = 2), pageLength = 5))
+  output$daily_sessions_chart <-create_app_daily_session_chart(daily_app_usage)
+
+  output$cumulated_duration_per_user_chart <- create_cumulated_duration_per_user(
+    reactive(apps_ranking()[[1]]),
+    selected_app = reactive(input$selected_app)
+  )
+  output$cumulated_hits_per_user_chart <- create_cumulated_hits_per_user(
+   reactive(apps_ranking()[[1]]),
+    selected_app = reactive(input$selected_app)
+  )
+
+# User consumption --------------------------------------------------------
+
+  consumer_ranking <- create_apps_consumer_ranking(apps_usage, rsc_users)
+  output$consumer_ranking_chart <- create_apps_consumer_ranking_chart(
+    consumer_ranking, reactive(input$views_threshold)
+  )
+
+  daily_consumption <- get_user_daily_consumption(
+    rsc_content,
+    rsc_users,
+    apps_usage,
+    reactive(input$selected_user)
+  )
+
+  output$daily_consumption_chart <- create_user_daily_consumption_chart(daily_consumption[[2]])
+
+
+# Developers data ---------------------------------------------------------
+
+  output$dev_ranking_chart <- create_dev_ranking_chart(
+    developers_apps_ranking,
+    reactive(input$apps_threshold)
+  )
+
+  output$dev_projects_network <- create_dev_project_overview(
+    rsc_client, reactive(apps_ranking()[[1]]),
+    reactive(input$app_developer)
+  )
+
+
+# General data ------------------------------------------------------------
+  output$roles_chart <- renderEcharts4r({
+    tmp <- sort_users_by_role(rsc_users, input$date_range[1], input$date_range[2])
+    validate(need(nrow(tmp) > 0, "No data found"))
+    tmp %>% create_pie_chart("user_role")
+  })
+
+  output$content_access <- renderEcharts4r({
+    tmp <- sort_content_by_access(rsc_content, input$date_range[1], input$date_range[2])
+    validate(need(nrow(tmp) > 0, "No data found"))
+    tmp %>% create_pie_chart("access_type")
+  })
+
+  output$r_versions <- renderEcharts4r({
+    tmp <- sort_content_by_rversion(rsc_content, input$date_range[1], input$date_range[2])
+    validate(need(nrow(tmp) > 0, "No data found"))
+    tmp %>% create_pie_chart("r_version")
+  })
+
+  output$content_type <- renderEcharts4r({
+    tmp <- sort_content_by_appmode(rsc_content, input$date_range[1], input$date_range[2])
+    validate(need(nrow(tmp) > 0, "No data found"))
+    tmp %>% create_pie_chart("app_mode")
+  })
+}
+
+shinyApp(ui, server)
diff --git a/inst/examples/simple-rmd/analysis.Rmd b/inst/examples/simple-rmd/analysis.Rmd
index 61e379f..399434d 100644
--- a/inst/examples/simple-rmd/analysis.Rmd
+++ b/inst/examples/simple-rmd/analysis.Rmd
@@ -68,45 +68,62 @@ Important note: with a basic __publisher__ API key, we can only recover the data
 #### Most used apps
 
 ```{r}
-apps_ranking <- create_app_ranking(rsc_content, rsc_users, apps_usage)
-card(
-  full_screen = TRUE,
-  create_app_ranking_table(apps_ranking),
+dateRangeInput(
+  "date_range",
+  "Select the app usage range:",
+  start = Sys.Date() - 10,
+  end = Sys.Date()
+)
+apps_ranking <- create_app_ranking(
+  rsc_content, 
+  rsc_users, 
+  apps_usage,
+  start_date = reactive(input$date_range[1]),
+  end_date = reactive(input$date_range[2])
 )
+
+renderUI({
+  card(
+    full_screen = TRUE,
+    title = sprintf("Ranking between %s and %s", input$date_range[1], input$date_range[2]),
+    create_app_ranking_table(apps_ranking),
+  )
+})
 ```
 
 #### Daily app usage
 
 ```{r}
-
-daily_app_usage <- get_app_daily_usage(apps_ranking[[2]], reactive(input$selected_app))
+daily_app_usage <- get_app_daily_usage(apps_ranking()[[2]], reactive(input$selected_app))
 ```
 
 ```{r}
-card(
-  full_screen = TRUE,
-  card_header("App usage"),
-  layout_sidebar(
-    sidebar = sidebar(
-      width = 150,
-      selectInput(
-        "selected_app", 
-        "Select an application", 
-        apps_ranking[[2]]$app_name
+renderUI({
+  card(
+    full_screen = TRUE,
+    card_header("App usage"),
+    layout_sidebar(
+      sidebar = sidebar(
+        width = 150,
+        selectInput(
+          "selected_app", 
+          "Select an application", 
+          apps_ranking()[[2]]$app_name
+        )
+      ),
+      p("Daily app usage"),
+      create_app_daily_usage_chart(daily_app_usage),
+      create_cumulated_duration_per_user(
+        apps_ranking()[[1]],
+        selected_app = reactive(input$selected_app)
+      ),
+      create_cumulated_hits_per_user(
+        apps_ranking()[[1]], 
+        selected_app = reactive(input$selected_app)
       )
-    ),
-    p("Daily app usage"),
-    create_app_daily_usage_chart(daily_app_usage),
-    create_cumulated_duration_per_user(
-      apps_ranking[[1]],
-      selected_app = reactive(input$selected_app)
-    ),
-    create_cumulated_hits_per_user(
-      apps_ranking[[1]], 
-      selected_app = reactive(input$selected_app)
     )
   )
-)
+})
 ```
 
 ### Consumer data
@@ -197,7 +214,7 @@ dev_projects_card <- card(
       )
     ),
     create_dev_project_overview(
-      rsc_client, apps_ranking[[1]], 
+      rsc_client, apps_ranking()[[1]], 
       reactive(input$app_developer)
     )
   )
diff --git a/man/create_app_daily_session_chart.Rd b/man/create_app_daily_session_chart.Rd
new file mode 100644
index 0000000..0524866
--- /dev/null
+++ b/man/create_app_daily_session_chart.Rd
@@ -0,0 +1,38 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/helpers-charts.R
+\name{create_app_daily_session_chart}
+\alias{create_app_daily_session_chart}
+\title{Generic calendar chart generator}
+\usage{
+create_app_daily_session_chart(
+  calendar_data,
+  title = "Cumulated daily usage",
+  subtitle = "time units: minutes",
+  start_date = NULL,
+  end_date = NULL,
+  callback = NULL
+)
+}
+\arguments{
+\item{calendar_data}{Calendar chart data.}
+
+\item{title}{Chart title.}
+
+\item{subtitle}{Chart subtitle.}
+
+\item{start_date}{Default to minimum calendar_data date. Could also be
+an input value with Shiny.}
+
+\item{end_date}{Default to maximum calendar_data date. Could also be
+an input value with Shiny.}
+
+\item{callback}{JS function to pass to \link[htmlwidgets]{onRender}. This is
+useful to access the widget API on the R side at render time
+and add events on the fly.}
+}
+\value{
+An echarts4r line chart
+}
+\description{
+Generic calendar chart generator
+}
diff --git a/man/create_app_daily_usage_chart.Rd b/man/create_app_daily_usage_chart.Rd
index 91184f3..0c589f3 100644
--- a/man/create_app_daily_usage_chart.Rd
+++ b/man/create_app_daily_usage_chart.Rd
@@ -4,10 +4,12 @@
 \alias{create_app_daily_usage_chart}
 \title{Daily app usage chart}
 \usage{
-create_app_daily_usage_chart(app_usage)
+create_app_daily_usage_chart(app_usage, ...)
 }
 \arguments{
 \item{app_usage}{Returned by \link{get_app_daily_usage}.}
+
+\item{...}{Pass down any param to \link{create_calendar_chart}.}
 }
 \value{
 A calendar chart displaying daily app usage.
diff --git a/man/create_app_ranking.Rd b/man/create_app_ranking.Rd
index f430276..f313947 100644
--- a/man/create_app_ranking.Rd
+++ b/man/create_app_ranking.Rd
@@ -4,7 +4,7 @@
 \alias{create_app_ranking}
 \title{Process app data for ranking table}
 \usage{
-create_app_ranking(content, users, apps)
+create_app_ranking(content, users, apps, start_date = NULL, end_date = NULL)
 }
 \arguments{
 \item{content}{Get from \link[connectapi]{get_content}. Can be reactive.}
@@ -12,6 +12,12 @@ create_app_ranking(content, users, apps)
 \item{users}{Get from \link[connectapi]{get_users}. Can be reactive.}
 
 \item{apps}{Get from \link[connectapi]{get_usage_shiny}. Can be reactive.}
+
+\item{start_date}{Default to minimum calendar_data date. Could also be
+an input value with Shiny.}
+
+\item{end_date}{Default to maximum calendar_data date. Could also be
+an input value with Shiny.}
 }
 \value{
 A list containing: \verb{[[1]]} merged data between app usage and users data.
diff --git a/man/get_rsc_app_dates.Rd b/man/get_rsc_app_dates.Rd
index b2196b7..7a2ae8e 100644
--- a/man/get_rsc_app_dates.Rd
+++ b/man/get_rsc_app_dates.Rd
@@ -12,8 +12,8 @@ get_rsc_app_dates(app, logs)
 \item{logs}{Given by RSC database.}
 }
 \value{
-A vector containing dates of usage for
-the given app.
+A tibble containing dates of usage for
+the given app as well as the correponding session duration.
 }
 \description{
 Extract app usage dates
diff --git a/man/sort_content_by_access.Rd b/man/sort_content_by_access.Rd
index 563718b..4b843ee 100644
--- a/man/sort_content_by_access.Rd
+++ b/man/sort_content_by_access.Rd
@@ -4,10 +4,14 @@
 \alias{sort_content_by_access}
 \title{Sort RStudio Connect content by access type}
 \usage{
-sort_content_by_access(content)
+sort_content_by_access(content, start_date = NULL, end_date = NULL)
 }
 \arguments{
 \item{content}{Get from \link[connectapi]{get_content}.}
+
+\item{start_date}{Date filter.}
+
+\item{end_date}{Date filter.}
 }
 \value{
 A tibble with content grouped by access type.
diff --git a/man/sort_content_by_appmode.Rd b/man/sort_content_by_appmode.Rd
index 3e1a650..b4352ce 100644
--- a/man/sort_content_by_appmode.Rd
+++ b/man/sort_content_by_appmode.Rd
@@ -4,10 +4,14 @@
 \alias{sort_content_by_appmode}
 \title{Sort RStudio Connect content by app mode}
 \usage{
-sort_content_by_appmode(content)
+sort_content_by_appmode(content, start_date = NULL, end_date = NULL)
 }
 \arguments{
 \item{content}{Get from \link[connectapi]{get_content}.}
+
+\item{start_date}{Date filter.}
+
+\item{end_date}{Date filter.}
 }
 \value{
 A tibble with content grouped by app mode.
diff --git a/man/sort_content_by_rversion.Rd b/man/sort_content_by_rversion.Rd
index beafb10..77b517c 100644
--- a/man/sort_content_by_rversion.Rd
+++ b/man/sort_content_by_rversion.Rd
@@ -4,10 +4,14 @@
 \alias{sort_content_by_rversion}
 \title{Sort RStudio Connect content by R version}
 \usage{
-sort_content_by_rversion(content)
+sort_content_by_rversion(content, start_date = NULL, end_date = NULL)
 }
 \arguments{
 \item{content}{Get from \link[connectapi]{get_content}.}
+
+\item{start_date}{Date filter.}
+
+\item{end_date}{Date filter.}
 }
 \value{
 A tibble with content grouped by R version.
diff --git a/man/sort_users_by_role.Rd b/man/sort_users_by_role.Rd
index 48b5b92..bcce3cd 100644
--- a/man/sort_users_by_role.Rd
+++ b/man/sort_users_by_role.Rd
@@ -4,15 +4,20 @@
 \alias{sort_users_by_role}
 \title{Sort RStudio Connect users by role}
 \usage{
-sort_users_by_role(users)
+sort_users_by_role(users, start_date = NULL, end_date = NULL)
 }
 \arguments{
 \item{users}{Get from \link[connectapi]{get_users}.}
+
+\item{start_date}{Date filter.}
+
+\item{end_date}{Date filter.}
 }
 \value{
 A tibble with user grouped by role.
 }
 \description{
 Users are grouped by user_role to check the
-server role repartition.
+server role repartition. Using start_date and end_date allows
+to filter data given a specific time range.
 }