Update app.R

app.R

@@ -4,6 +4,16 @@ library(ggplot2)
 library(utils)
 
 data1 <- read.csv("data1.csv", header = TRUE, check.names = FALSE, fileEncoding = "UTF-8")
+data2 <- data2[,2:54]
+
+AAaveragePT <- data1 %>%
+mutate(arm_angle = round(arm_angle, digits = 0)) %>%
+group_by(arm_angle, phand, pitch_name) %>%
+summarise(
+  AvgIVB = mean(IVB, na.rm = TRUE),
+  AvgHB = mean(HB, na.rm = TRUE),
+  .groups = 'drop'
+  )
 
 pitch_type_lookup <- data.frame(
     pitch_name = c("Changeup", "Curveball", "Cutter", "Eephus", "Forkball", 
@@ -307,7 +317,7 @@ ui <- fluidPage(
       width = 3,  
       selectInput("player", "Select Player:", choices = unique(data1$`Pitcher Name`),
                   width = "100%"),  
-      dateRangeInput("date1", "Date Range:", 
+      dateRangeInput("date1", "Dates: (Be wary of multi year plots as arm angles may change)", 
                      start = "2024-02-09", 
                      end = "2024-09-05",
                      width = "100%"),  
@@ -330,16 +340,6 @@ ui <- fluidPage(
 
 # Define server
 server <- function(input, output) {
-
-  AAaveragePT <- data1 %>%
-  mutate(arm_angle = round(arm_angle, digits = 0)) %>%
-  group_by(arm_angle, phand, pitch_name) %>%
-  summarise(
-    AvgIVB = mean(IVB, na.rm = TRUE),
-    AvgHB = mean(HB, na.rm = TRUE),
-    .groups = 'drop'
-  )
-
   
   filtered_data <- eventReactive(input$submit, {
     data1 %>%