Added tables for PM2.5,NO2 and Physical Activity

presentation.R

@@ -6,6 +6,7 @@ library(ggplot2)
 library(esquisse)
 library(dplyr)
 library(stringr)
+library(gt)
 
 ## Data baseline year for reference and scenario
 
@@ -319,6 +320,102 @@ mmet_imd <- ggplot(exposure, aes(x = imd, y = total_mmetHr, fill = scenario)) +
     legend.text = element_text(face = "bold"),
     legend.title = element_text(face = "bold"))
 
+# PM2.5 Table
+pm25_table <- exposure %>%
+  group_by(scenario) %>%
+  summarize(
+    Mean = round(mean(exposure_normalised_pm25), 2),
+    `5th` = round(quantile(exposure_normalised_pm25, 0.05), 2),
+    `25th` = round(quantile(exposure_normalised_pm25, 0.25), 2),
+    `35th` = round(quantile(exposure_normalised_pm25, 0.35), 2),
+    `50th` = round(quantile(exposure_normalised_pm25, 0.5), 2),
+    `95th` = round(quantile(exposure_normalised_pm25, 0.95), 2),
+    Median = round(median(exposure_normalised_pm25), 2),
+    .groups = 'drop'
+  ) %>%
+  mutate(
+    `Change (%)` = round((Median - Median[scenario == "Baseline"]) / Median[scenario == "Baseline"] * 100, 2),
+    Type = "PM2.5"
+  )
+
+# NO2 Table
+no2_table <- exposure %>%
+  group_by(scenario) %>%
+  summarize(
+    Mean = round(mean(exposure_normalised_no2), 2),
+    `5th` = round(quantile(exposure_normalised_no2, 0.05), 2),
+    `25th` = round(quantile(exposure_normalised_no2, 0.25), 2),
+    `35th` = round(quantile(exposure_normalised_no2, 0.35), 2),
+    `50th` = round(quantile(exposure_normalised_no2, 0.5), 2),
+    `95th` = round(quantile(exposure_normalised_no2, 0.95), 2),
+    Median = round(median(exposure_normalised_no2), 2),
+    .groups = 'drop'
+  ) %>%
+  mutate(
+    `Change (%)` = round((Median - Median[scenario == "Baseline"]) / Median[scenario == "Baseline"] * 100, 2),
+    Type = "NO2"
+  )
+
+# Physical Activity (MMET) Table
+mmet_table <- exposure %>%
+  group_by(scenario) %>%
+  summarize(
+    Mean = round(mean(total_mmetHr), 2),
+    `5th` = round(quantile(total_mmetHr, 0.05), 2),
+    `25th` = round(quantile(total_mmetHr, 0.25), 2),
+    `35th` = round(quantile(total_mmetHr, 0.35), 2),
+    `50th` = round(quantile(total_mmetHr, 0.5), 2),
+    `95th` = round(quantile(total_mmetHr, 0.95), 2),
+    Median = round(median(total_mmetHr), 2),
+    .groups = 'drop'
+  ) %>%
+  mutate(
+    `Change (%)` = round((Median - Median[scenario == "Baseline"]) / Median[scenario == "Baseline"] * 100, 2),
+    Type = "Physical Activity"
+  )
+
+combined_table <- bind_rows(pm25_table, no2_table, mmet_table) %>% 
+  arrange(Type, scenario) %>% 
+  gt() %>% 
+  tab_row_group(
+    label = md("**PM2.5**"), 
+    rows = Type == "PM2.5"
+  ) %>% 
+  tab_row_group(
+    label = md("**NO2**"), 
+    rows = Type == "NO2"
+  ) %>% 
+  tab_row_group(
+    label = md("**Physical Activity**"), 
+    rows = Type == "Physical Activity"
+  ) %>% 
+  cols_hide(columns = "Type") %>% 
+  cols_label(
+    scenario = "", 
+    Mean = "Mean", 
+    `5th` = "5th Percentile", 
+    `25th` = "25th Percentile", 
+    `35th` = "35th Percentile", 
+    `50th` = "50th Percentile", 
+    `95th` = "95th Percentile", 
+    Median = "Median", 
+    `Change (%)` = "Change (%)"
+  ) %>% 
+  tab_style(
+    style = cell_text(weight = "bold"),
+    locations = cells_column_labels() 
+  ) %>% 
+  tab_style(
+    style = cell_text(weight = "bold"),
+    locations = cells_row_groups()) %>% 
+  tab_header(
+    title = "Summary Statistics of Individual Exposures",
+    subtitle = "The change is calculated as percentage difference with the baseline scenario") %>% 
+  tab_style(
+    style = cell_text(weight = "bold"),
+    locations = cells_title())
+
+combined_table
 
 ############################ Health ##################################################