Update app.R

app.R

@@ -115,6 +115,92 @@ heatMap <- function(data, gtitle, concen) {
     )
 }
 
+download_private_parquet <- function(repo_id, filename) {
+  library(httr)
+  library(arrow)
+  
+  # Create the direct download URL based on your example
+  url <- paste0("https://huggingface.co/datasets/", repo_id, "/resolve/main/", filename, "?download=true")
+  
+  # Create a temporary file
+  temp_file <- tempfile(fileext = ".parquet")
+  
+  # Download directly to file
+  response <- GET(
+    url,
+    add_headers(Authorization = paste("Bearer", Sys.getenv("GETCSV"))),
+    write_disk(temp_file, overwrite = TRUE)
+  )
+  
+  # Check if download was successful
+  if (status_code(response) == 200) {
+    tryCatch({
+      # Read the parquet file
+      data <- read_parquet(temp_file)
+      file.remove(temp_file)
+      return(data)
+    }, error = function(e) {
+      file.remove(temp_file)
+      stop(paste("Error reading parquet file:", e$message))
+    })
+  } else {
+    file.remove(temp_file)
+    stop(paste("Failed to download file. Status code:", status_code(response)))
+  }
+}
+
+font_add_google("Roboto Condensed")
+
+is_barrel <- function(df) {
+    df$barrel <- with(df, ifelse(hit_angle <= 50 & hit_speed >= 97 & hit_speed * 1.5 - 
+                                     hit_angle >= 117 & hit_speed + hit_angle >= 123, 1, 0))
+    return(df)
+}
+
+apply_percentile_calcs <- function(data) {
+  # List of columns to apply percent_rank
+  percent_rank_cols <- c("Z-Con%", "Z-Swing%", "O-Con%", "Avg EV", "Max EV", "EV90", "Barrel%", "Swing%", "wOBA",
+                         "wOBACON","xwOBA","xDamage")
+  
+  # List of columns to apply inverse percent_rank
+  inverse_percent_rank_cols <- c("Chase%", "Whiff%", "stdev(LA)", "SwStr%")
+  
+  # Create an empty list to store results
+  percentile_list <- list()
+  
+  # Calculate regular percentiles
+  for(col in percent_rank_cols) {
+    percentile_list[[col]] <- data.frame(
+      `Batter Name` = data[["Batter Name"]],  # Using [[ ]] to preserve exact column name
+      `Batter ID` = data[["Batter ID"]],      # Using [[ ]] to preserve exact column name
+      metric = col,
+      percentile = round(percent_rank(data[[col]]) * 100),
+      value = data[[col]],
+      stringsAsFactors = FALSE
+    )
+  }
+  
+  # Calculate inverse percentiles
+  for(col in inverse_percent_rank_cols) {
+    percentile_list[[col]] <- data.frame(
+      `Batter Name` = data[["Batter Name"]],  # Using [[ ]] to preserve exact column name
+      `Batter ID` = data[["Batter ID"]],      # Using [[ ]] to preserve exact column name
+      metric = col,
+      percentile = round((1 - percent_rank(data[[col]])) * 100),
+      value = data[[col]],
+      stringsAsFactors = FALSE
+    )
+  }
+  
+  # Combine all results into one data frame
+  result <- do.call(rbind, percentile_list)
+  
+  # Reset row names
+  rownames(result) <- NULL
+  
+  return(result)
+}
+
 MLB25 <- download_private_parquet("TimStats/StatcastDataAll", "MLB25.parquet")
 MLB25$level <- "MLB"
 AAA25 <- download_private_parquet("TimStats/StatcastDataAll", "AAA25.parquet")