ggplot does not react to selective inputs - r

Question

I am trying to create a NBA shot analysis dashboard and I created 5 variables to sort the data by that update based on their existence in the dataframes from all NBA Teams which I downloaded from NBAsavant.com. so to reproduce this on your machine you should have to just download one teams csv file.
This is done through a selectizeGroupUI and SelectiveGroupServer.
My problem is that when the user selects the restraints to subset the data, I want to pull two columns from that specific subset the user created through the inputs.
That way the final dashboard would show the x and y coordinates in the ggplot based entirely on what the users inputs are, which I am sure of how to code into the ggplot function itself.
Any help would be appreciated!
#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(shinythemes)
library(plotly)
library(tidyverse)
library(rsconnect)
library(readr)
library(ggplot2)
library(plyr)
library(dplyr)
library(jpeg)
library(grid)
library(RCurl)
library(shinyWidgets)
# import all NBA teams csv files into one dataframe
mydir = "NBA Teams 2017-2018"
myfiles = list.files(path = mydir, pattern = "*.csv", full.names = TRUE)
myfiles
data_csv = ldply(myfiles, read_csv)
courtImg <- "http://robslink.com/SAS/democd54/nba_court_dimensions.jpg"
court <- rasterGrob(readJPEG(getURLContent(courtImg)),
width = unit(1, "npc"), height = unit(1, "npc"))
ui = pageWithSidebar(
headerPanel("NBA 2017-2018 Season: Shooting Analysis"),
sidebarPanel(
# uiOutput("team_name"),
# uiOutput("name"),
# uiOutput("shot_type"),
# uiOutput("shot_made_flag"),
# uiOutput("action_type")
selectizeGroupUI(
id = "my-filters",
inline = FALSE,
params = list(
team_name = list(inputId = "team_name", title = "NBA Team", placeholder = 'Select NBA Team'),
name = list(inputId = "name", title = "Player", placeholder = 'Select a Player'),
shot_type = list(inputId = "shot_type", title = "2 PT or 3 PT", placeholder = 'Select Value'),
shot_made_flag = list(inputId = "shot_made_flag", title = "FGA / FG", placeholder = 'Select Between All Shot Attempts or Only Shots Made'),
action_type = list(inputId = "action_type", title = "Shot Type", placeholder = 'Select Shot Type'))
)
),
mainPanel(
#tableOutput("table"),
plotOutput("court_plot")
)
)
server <- function(input, output, session) {
res_mod <- callModule(
module = selectizeGroupServer,
id = "my-filters",
data = data_csv,
vars = c("team_name", "name", "shot_type", "shot_made_flag", "action_type")
)
output$court_plot <- renderPlot({
res_mod()
ggplot(data_csv, aes(x = x, y = colory)) +
annotation_custom(court, -250, 250, -50, 420) +
geom_point(color = data_csv$shot_type) +
xlim(-250, 250) +
ylim(-50, 420)
})
}
shinyApp(ui = ui, server = server)

Answer 1

here is corrected code:
I added data_i = res_mod() to my ggplot and pipelined it through the rest of code in that block.
#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(shinythemes)
library(plotly)
library(tidyverse)
library(rsconnect)
library(readr)
library(ggplot2)
library(plyr)
library(dplyr)
library(jpeg)
library(grid)
library(RCurl)
library(shinyWidgets)
# import all NBA teams csv files into one dataframe
mydir = "NBA Teams 2017-2018"
myfiles = list.files(path = mydir, pattern = "*.csv", full.names = TRUE)
myfiles
# declare csv file
data_csv = ldply(myfiles, read_csv)
# upload image of court for ggplot
courtImg <- "http://robslink.com/SAS/democd54/nba_court_dimensions.jpg"
court <- rasterGrob(readJPEG(getURLContent(courtImg)),
width = unit(1, "npc"), height = unit(1, "npc"))
# ui for shiny dashboard
ui = fluidPage(
# change the theme to be easier on the eyes
theme = shinytheme('darkly'),
# title of shiny app
headerPanel("NBA 2017-2018 Season: Shooting Analysis"),
sidebarPanel(
# create a subset of the data that changes based on user input and narrows down the choices
selectizeGroupUI(
id = "my-filters",
inline = FALSE,
params = list(
team_name = list(inputId = "team_name", title = "NBA Team", placeholder = 'Select NBA Team'),
name = list(inputId = "name", title = "Player", placeholder = 'Select a Player'),
shot_type = list(inputId = "shot_type", title = "2 PT or 3 PT", placeholder = 'Select Value'),
shot_made_flag = list(inputId = "shot_made_flag", title = "Missed(0) or Made(1) Shot", placeholder = 'Select Between All Shot Attempts or Only Shots Made'),
action_type = list(inputId = "action_type", title = "Shot Type", placeholder = 'Select Shot Type'))
),
status = "primary"
),
mainPanel(
# plot the court next to the user input
plotOutput(outputId = "court_plot", width = '800px')
)
)
# server side of the app that allows the user interactions to affect the dataframe
server <- function(input, output, session) {
# allow the custom subset dataframe to be called
res_mod <- callModule(
module = selectizeGroupServer,
id = "my-filters",
data = data_csv,
vars = c("team_name", "name", "shot_type", "shot_made_flag", "action_type")
)
# the code side of the plot that plots the users input by calling the subsetted dataframe
output$court_plot <- renderPlot({
data_i = res_mod()
data_i %>% ggplot(aes(x, y)) +
annotation_custom(court, -250, 250, -50, 420) +
geom_point(color = data_i$shot_type) +
xlim(-250, 250) +
ylim(-50, 420)
})
}
shinyApp(ui = ui, server = server)