vorerster commit

content/01_journal/flex_dash.Rmd

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+---
+title: "Sales Dashboard"
+output: 
+  flexdashboard::flex_dashboard:
+    orientation: columns
+    vertical_layout: fill
+    runtime: shiny
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(warning = FALSE, message = FALSE) 
+
+library(flexdashboard)
+
+# Core
+library(tidyverse)
+
+# Interactive Visualizations
+library(plotly)
+
+# Spatial Data
+library(raster)
+library(sf)
+library(dplyr)
+library(lubridate)
+library(shinyWidgets)
+
+```
+
+```{r echo=FALSE}
+format_to_euro <- function(x, suffix = " €") {
+
+  scales::dollar(x,
+                 suffix       = suffix,
+                 prefix       = "",
+                 big.mark     = ".",
+                 decimal.mark = ",")
+}
+
+euro_format <- function(scale        = 1,
+                        prefix       = "",
+                        suffix       = " €",
+                        big.mark     = ".",
+                        decimal.mark = ",") {
+
+  scales::dollar_format(suffix       = suffix,
+                        prefix       = prefix,
+                        big.mark     = big.mark,
+                        decimal.mark = decimal.mark,
+                        scale        = scale)
+
+}
+```
+
+
+```{r}
+# Bike data
+bikes_tbl      <- readRDS("01_data/bikes_tbl.rds")
+bikeshops_tbl  <- readRDS("01_data/bikeshops_tbl.rds")
+orderlines_tbl <- readRDS("01_data/orderlines_tbl.rds")
+
+bike_orderlines_tbl <- orderlines_tbl %>%
+    left_join(bikes_tbl,     by = c("product_id" = "bike_id")) %>%
+    left_join(bikeshops_tbl, by = c("customer_id" = "bikeshop_id")) %>%
+    mutate(total_price = price_euro * quantity)
+
+
+# German spatial data
+# German spatial data
+# germany_sp <- getData('GADM', country='DE', level=1) broken link
+germany_sp <- readRDS("01_data/gadm36_DEU_1_sp.rds")
+germany_sf <- st_as_sf(germany_sp) %>% 
+  
+                  # Add english names
+                  mutate(VARNAME_1 = ifelse(is.na(VARNAME_1), NAME_1, VARNAME_1)) 
+```
+
+
+Column {.sidebar}
+-----------------------------------------------------------------------
+
+```{r}
+DateSeq = seq(as.Date("2015-01-07"), Sys.Date(), "day")
+dateRangeInput("dateRange", "Date Range", format = "yyyy-mm-dd", start=min(DateSeq), end=max(DateSeq))
+
+```
+
+
+```{r}
+checkboxGroupButtons("bike_type", "Bike Type",
+                           choices = c("All", "Road", "Mountain"),
+                           selected = "All",
+                           status = "primary")
+
+
+```
+
+```{r}
+pickerInput("bike_family", "Bike Family",
+            choices = c("All", unique(bike_orderlines_tbl$category_2)),
+            selected = "All",
+            multiple = TRUE)
+```
+
+
+```{r}
+actionButton("apply_filters", "Apply Filters", icon = icon("filter"))
+
+```
+
+
+Column {data-width=1000}
+---------------------------------------------------------------
+
+### By State
+
+```{r}
+# Reactive expression to filter data when the Apply button is clicked
+filtered_data <- eventReactive(input$apply_filters, {
+  req(input$dateRange)  # Ensure dateRange input is available
+  req(input$bike_type)  # Ensure bike_type input is available
+  req(input$bike_family)  # Ensure bike_family input is available
+
+  bike_orderlines_tbl %>%
+  filter(order_date >= input$dateRange[1] & order_date <= input$dateRange[2]) %>%
+  filter(if ("All" %in% input$bike_type || length(input$bike_type) == 0) TRUE else category_1 %in% input$bike_type) %>%
+  filter(if ("All" %in% input$bike_family || length(input$bike_family) == 0) TRUE else category_2 %in% input$bike_family) %>%
+  group_by(state) %>%
+  summarise(total_revenue = sum(total_price)) %>%
+  ungroup() %>%
+  right_join(germany_sf, by = c("state" = "VARNAME_1")) %>%
+  mutate(total_revenue = ifelse(is.na(total_revenue), 0, total_revenue)) %>%
+  mutate(label_text = str_glue("State: {state}
+                               Revenue: {format_to_euro(total_revenue)}")) %>%
+  st_as_sf()
+})
+
+# Render the plot based on filtered data
+output$geo_plot_tbl <- renderPlot({
+  data <- filtered_data()
+ plot_ly(
+      data = data,
+      type = 'choroplethmapbox',
+      geojson = geojsonio::geojson_list(geo_plot_tbl),
+      locations = ~state,
+      featureidkey = "properties.VARNAME_1",
+      color = ~total_revenue,
+      colors = "Blues",
+      hoverinfo = 'text',
+      text = ~label_text,
+      colorbar = list(title = "Total Revenue")
+    ) %>%
+      layout(
+        mapbox = list(
+          center = list(lon = 10, lat = 51),
+          zoom = 4
+        )
+      )
+})
+```
+
+
+```{r}
+
+#geo_plot_tbl <- bike_orderlines_tbl %>% 
+#                  group_by(state) %>%
+#                  summarise(total_revenue = sum(total_price)) %>%
+#                  ungroup() %>%
+#                  right_join(germany_sf, by = c("state" = "VARNAME_1")) %>% 
+#                  mutate(total_revenue = ifelse(is.na(total_revenue), 0, total_revenue)) %>% 
+#                  mutate(label_text = str_glue("State: {state}
+#                                         Revenue: {format_to_euro(total_revenue)}")) %>% 
+#                  st_as_sf()
+```
+
+
+```{r}
+
+```
+
+```{r}
+plotOutput("geo_plot_tbl")
+```
+
+
+Column {data-width=1000}
+---------------------------------------------------------------
+
+### Over Time

content/01_journal/flex_dash_2.rmd

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+---
+title: "Untitled"
+output: 
+  flexdashboard::flex_dashboard:
+    orientation: columns
+    vertical_layout: fill
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(warning = FALSE, message = FALSE) 
+
+library(flexdashboard)
+
+# Core
+library(tidyverse)
+
+# Interactive Visualizations
+library(plotly)
+
+# Spatial Data
+library(raster)
+library(sf)
+library(dplyr)
+library(lubridate)
+library(shinyWidgets)
+library(shiny)
+
+library(dplyr)
+library(ggplot2)
+library(plotly)
+library(sf)
+library(shinythemes)
+
+```
+
+```{r}
+# Bike data
+bikes_tbl      <- readRDS("01_data/bikes_tbl.rds")
+bikeshops_tbl  <- readRDS("01_data/bikeshops_tbl.rds")
+orderlines_tbl <- readRDS("01_data/orderlines_tbl.rds")
+
+bike_orderlines_tbl <- orderlines_tbl %>%
+    left_join(bikes_tbl,     by = c("product_id" = "bike_id")) %>%
+    left_join(bikeshops_tbl, by = c("customer_id" = "bikeshop_id")) %>%
+    mutate(total_price = price_euro * quantity)
+
+
+# German spatial data
+# German spatial data
+# germany_sp <- getData('GADM', country='DE', level=1) broken link
+germany_sp <- readRDS("01_data/gadm36_DEU_1_sp.rds")
+germany_sf <- st_as_sf(germany_sp) %>% 
+  
+                  # Add english names
+                  mutate(VARNAME_1 = ifelse(is.na(VARNAME_1), NAME_1, VARNAME_1)) 
+```
+
+```{r echo=False}
+plot_all_sales <- function(data_tbl) {
+
+  plot_data_for_unit <- function(unit) {
+    data_tbl %>%
+      mutate(rounded_date = floor_date(order_date, unit = unit)) %>%
+      group_by(rounded_date) %>%
+      summarise(total_sales = sum(total_price),  .groups = 'drop') %>%
+      ungroup() %>%
+      mutate(label_text = str_glue("Sales: {format(total_sales, big.mark = ',')} \nDate: {rounded_date %>% format('%B %Y')}"))
+  }
+  
+  p <- plot_ly() %>%
+    add_lines(
+      data = plot_data_for_unit("day"),
+      x = ~rounded_date,
+      y = ~total_sales,
+      text = ~label_text,
+      hoverinfo = 'text',
+      line = list(shape = 'linear'),
+    ) %>%
+    layout(
+      title = "Total Sales",
+      xaxis = list(title = "", type = "date"),
+      yaxis = list(title = "", tickformat = ".0f"),
+      updatemenus = list(
+        list(
+          type = "buttons",
+          x = 0.5,  # Center horizontally
+          y = 1,  # Above the plot (top)
+          buttons = list(
+            list(label = "Quarter", method = "restyle", args = list("x", list(plot_data_for_unit("quarter")$rounded_date),
+                                                                           "y", list(plot_data_for_unit("quarter")$total_sales),
+                                                                           "text", list(plot_data_for_unit("quarter")$label_text),
+                                                                           "name", "Quarter")),
+            list(label = "Month", method = "restyle", args = list("x", list(plot_data_for_unit("month")$rounded_date),
+                                                                      "y", list(plot_data_for_unit("month")$total_sales),
+                                                                      "text", list(plot_data_for_unit("month")$label_text),
+                                                                      "name", "Month")),
+            list(label = "Week", method = "restyle", args = list("x", list(plot_data_for_unit("week")$rounded_date),
+                                                                     "y", list(plot_data_for_unit("week")$total_sales),
+                                                                     "text", list(plot_data_for_unit("week")$label_text),
+                                                                     "name", "Week")),
+            list(label = "Day", method = "restyle", args = list("x", list(plot_data_for_unit("day")$rounded_date),
+                                                                    "y", list(plot_data_for_unit("day")$total_sales),
+                                                                    "text", list(plot_data_for_unit("day")$label_text),
+                                                                    "name", "Day"),  active = TRUE)
+          ),
+          direction = "right",
+          showactive = TRUE
+        )
+      )
+    )
+  
+  # Return the plotly object
+  return(p)
+}
+```
+
+<div style="width:1000px;height:1300px">
+```{r}
+
+# Define UI
+ui <- fluidPage( 
+    theme = shinytheme("cerulean"),
+
+     titlePanel("Sales Visualization"), 
+  sidebarLayout(
+
+    sidebarPanel(
+          dateRangeInput("dateRange", "Date Range", format = "yyyy-mm-dd",
+                   start="2015-01-10", end=max(DateSeq)),
+    pickerInput("bike_type", "Select Bike Type:",
+                choices = c("All", unique(bike_orderlines_tbl$category_1)),
+                selected = "All",
+                multiple = TRUE),
+    pickerInput("bike_family", "Select Bike Family:",
+                choices = c("All", unique(bike_orderlines_tbl$category_2)),
+                selected = "All",
+                multiple = TRUE),
+    width=3
+    )
+    ,
+    mainPanel(
+        column(6, plotlyOutput("geo_plot_tbl", height="800px"), style = "height: 100vh;"),
+        column(6, plotlyOutput("timeseries_plot", height="800px"), style = "height: 100vh;"),
+      
+    width=9)
+  ),
+  style = "height: 100vh;",
+)
+
+# Define server logic
+server <- function(input, output, session) {
+  
+  # Reactive data filtering
+  filtered_data <- reactive({
+    bike_orderlines_tbl %>%
+      filter(order_date >= input$dateRange[1] & order_date <= input$dateRange[2]) %>%
+      filter(if ("All" %in% input$bike_type || length(input$bike_type) == 0) TRUE else category_1 %in% input$bike_type) %>%
+      filter(if ("All" %in% input$bike_family || length(input$bike_family) == 0) TRUE else category_2 %in% input$bike_family)
+  })
+  
+  # Render geoplot
+  output$geo_plot_tbl <- renderPlotly({
+    geo_plot_tbl <- filtered_data() %>%
+      group_by(state) %>%
+      summarise(total_revenue = sum(total_price)) %>%
+      ungroup() %>%
+      right_join(germany_sf, by = c("state" = "VARNAME_1")) %>%
+      mutate(total_revenue = ifelse(is.na(total_revenue), 0, total_revenue)) %>%
+      mutate(label_text = str_glue("State: {state}
+                                   Revenue: {format_to_euro(total_revenue)}")) %>%
+      st_as_sf()
+    
+   plot_ly(geo_plot_tbl, 
+        split      = ~NAME_1, 
+        color      = ~total_revenue,
+        colors     = "Blues",
+        stroke     = I("black"),
+        hoverinfo  = 'text', 
+        text       = ~label_text, 
+      hoveron    = "fills", 
+        showlegend = FALSE) 
+  })
+  
+  output$timeseries_plot <- renderPlotly({plot_all_sales(filtered_data())})
+}
+
+# Run the application 
+shinyApp(ui = ui, server = server, options = list(height = 1300))
+
+```
+</div>
+