Я пытаюсь сделать блестящее приложение для моей диссертации. В моей диссертации у меня есть ряд переменных (16), которые я анализирую по 5 условиям.
В моем приложении я хочу иметь боковую панель со списком переменных и условий в виде радиокнопок.
На главной панели я хочу следующий вывод:
- График Plotmeans со средним по условию (у меня есть эта часть)
- Сводка для выбранной переменной и выбранного условия
- График плотности для выбранной переменной и выбранного условия
- Вывод из shapiro.test для выбранной переменной и выбранного условия
- Интерпретация shapiro.test (т. Е. Нормально / не нормально)
Я могу легко получить график с помощью средств по условию, однако у меня возникают проблемы с отображением оставшейся части вывода. Должно быть что-то не так с тем, как я ссылаюсь на свои радиокнопки для условия, потому что после того, как я нажимаю «Анализ», я получаю сообщение об ошибке, сообщающее, что выбранная переменная не найдена.
Пожалуйста, посмотрите на мой код, я буду признателен за любую помощь:
#Shiny app to display means, summary, and normality interpretation for each
variable and condition in study 3
library(shiny)
#############################################################################
# Define UI
ui <- fluidPage(
# Application title
titlePanel(
h1("Variable Means by Condition (Study 3)", align = "center", style =
"color:black")),
# Sidebar with a slider input for number of bins
sidebarLayout(
sidebarPanel(
radioButtons(inputId = "var", label = "Select a Variable:",
c("Time from Catch to Lowest COM" = "T0_1",
"Time from Lowest COM to Release" = "T1_2",
"Release Time" = "T0_2",
"Knee Extension at Catch" = "T0_Knee_Ext",
"Hip Extension at Catch" = "T0_Hip_Ext",
"Minimum Ball Height" = "Min_Ball_Ht",
"Ball Height at Lowest COM" = "T1_Ball_Ht",
"Knee Extension at Lowest COM" = "T1_Knee_Ext",
"Hip Extension at Lowest COM" = "T1_Hip_Ext",
"Shoulder Flexion at Release" = "T2_Sh_Flex",
"Elbow Extension at Release" = "T2_Elb_Ext",
"Release Height" = "T2_Rel_Ht",
"Jump Height" = "T2_Jump_Ht",
"Wrist Extension at Follow-Through" = "T2_Wr_Ext",
"Accuracy" = "ACCURACY",
"Overall Performance" = "Acc.Spd")),
#Add radio buttons to choose a condition
radioButtons(inputId = "cond", label = "Select a Condition:",
c("Condition 1" = 1,
"Condition 2" = 2,
"Condition 3" = 3,
"Condition 4" = 4,
"Condition 5" = 5)),
#Add action button
actionButton("goButton","Analyze")),
# Show a plot of the mean of the selected variable
mainPanel(
#create a plot for selected variable
plotOutput("mean_plot"),
#Get summary for selected variable and selected condition
verbatimTextOutput("summ"),
#Get density plot for selected variable and selected condition
plotOutput("dens_plot"),
#Calculate shapiro wilk test for selected variable and selected
condition
verbatimTextOutput("shap"),
#Return if the selected variable and selected condition is normal or
not
verbatimTextOutput("norm"))
)
)
####################################################################
# Define server logic required to draw plotmeans
server <- function(input, output) {
#import data
library(readr)
dt <- read_csv("dt.csv")
dt$CONDITIONf <- factor(dt$CONDITION, levels = c(1,2,3,4,5), labels =
c("Normal","None","Wrist","Elb. Ht.","Rim"))
#subset data on various inputs from ui
subsetData <- reactive({
new_data <- dt[,CONDITION == input$cond]
return(new_data)
})
#After clicking goButton....
observeEvent(input$goButton, {
#Create plot
output$mean_plot <- renderPlot({
#using gplots plotmeans
library(gplots)
p <- plotmeans(get(input$var) ~ CONDITIONf, data = dt, connect = FALSE,
n.label = FALSE,
mean.labels = TRUE, digits = 2, xlab = "Condition", ylab =
"Mean", main =
"Variable Means by Condition", pch = " ")})
#Get summary for selected variable and condition
#Create density plot
output$dens_plot <- renderPlot({
hist(subsetData[,get(input$var)])
})
#Run shapiro wilk test
output$shap <- renderPrint({
shapiro.test(subsetData[,get(input$var)])
})
#Print interpretation of shapiro.test (ifelse(p-value from shapiro.test <
0.05, "Not Normal", "Normal")
output$norm <- renderPrint({
ifelse(output$shap < 0.05, return("Not Normal", return("Normal")))
})
})
}
#############################################################################
# Run the application
shinyApp(ui = ui, server = server)
Если вам нужен набор данных, пожалуйста, свяжитесь со мной, и я отправлю его вам. Заранее спасибо!
После запуска:
dplot(head(dt, 20))
В моем выводе я получил:
structure(list(X1 = 1:20, PRIM_KEY = 1:20, NAME = c("Andrew Grajeda",
"Andrew Grajeda", "Andrew Grajeda", "Andrew Grajeda", "Andrew Grajeda",
"Andrew Grajeda", "Andrew Grajeda", "Andrew Grajeda", "Andrew Grajeda",
"Andrew Grajeda", "Andrew Grajeda", "Andrew Grajeda", "Andrew Grajeda",
"Andrew Grajeda", "Andrew Grajeda", "Andrew Grajeda", "Andrew Grajeda",
"Andrew Grajeda", "Andrew Grajeda", "Andrew Grajeda"), SUBJECT = c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), BIRTHDAY = structure(c(11860, 11860, 11860, 11860,
11860, 11860, 11860, 11860, 11860, 11860, 11860, 11860, 11860,
11860, 11860, 11860, 11860, 11860, 11860, 11860), class = "Date"),
TODAY_DATE = structure(c(17616, 17616, 17616, 17616, 17616,
17616, 17616, 17616, 17616, 17616, 17616, 17616, 17616, 17616,
17616, 17616, 17616, 17616, 17616, 17616), class = "Date"),
AGE = c(15.7698630136986, 15.7698630136986, 15.7698630136986,
15.7698630136986, 15.7698630136986, 15.7698630136986,
15.7698630136986,
15.7698630136986, 15.7698630136986, 15.7698630136986,
15.7698630136986,
15.7698630136986, 15.7698630136986, 15.7698630136986,
15.7698630136986,
15.7698630136986, 15.7698630136986, 15.7698630136986,
15.7698630136986,
15.7698630136986), YOE = c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), DAILY_SHOTS = c(50L,
50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L,
50L, 50L, 50L, 50L, 50L, 50L, 50L), CLIP = c("00_1", "00_1",
"00_1", "00_1", "00_1", "00_1", "00_1", "00_1", "00_1", "00_1",
"00_1", "00_1", "00_1", "00_1", "00_1", "00_1", "00_1", "00_1",
"00_1", "00_1"), HEIGHT = c(1.73, 1.73, 1.73, 1.73, 1.73,
1.73, 1.73, 1.73, 1.73, 1.73, 1.73, 1.73, 1.73, 1.73, 1.73,
1.73, 1.73, 1.73, 1.73, 1.73), Group = c(1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L), CONDITION = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), SHOT = c(1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L, 5L, 6L,
7L, 8L, 9L, 10L), ACCURACY = c(4.5, 4.5, 4, 4.5, 4, 4.5,
4.5, 4, 3.5, 4.5, 3, 2, 2, 2, 3, 4.5, 4.5, 2, 3, 3), Make = c(1L,
1L, 0L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L,
1L, 0L, 0L, 0L), T0 = structure(c(-2209075175, -2209075170,
-2209075164, -2209075158, -2209075153, -2209075149, -2209075143,
-2209075136, -2209075130, -2209075126, -2209075040, -2209075035,
-2209075030, -2209075025, -2209075020, -2209075015, -2209075010,
-2209075006, -2209075001, -2209074998), class = c("POSIXct",
"POSIXt"), tzone = "UTC"), T0_Knee_Ext = c(169.7, 165.7,
169.3, 173, 171.3, 168.7, 164.1, 165.7, 166.8, 165.7, 164,
157.4, 157.4, 157.4, 147.2, 147.2, 150, 149.9, 152, 149),
T0_Hip_Ext = c(172.6, 172.6, 172.6, 176.7, 171.7, 171.7,
161.1, 161.1, 168.9, 171.7, 163.7, 160.9, 160.9, 160.9, 154.5,
156.2, 156.2, 156.2, 156.5, 156.2), Min_Ball_Ht = c(0.93,
0.94, 0.96, 0.92, 0.95, 0.94, 0.94, 0.93, 0.94, 0.93, 0.8,
0.81, 0.8, 0.8, 0.81, 0.81, 0.8, 0.8, 0.81, 0.8), T1 =
structure(c(-2209075175,
-2209075169, -2209075163, -2209075157, -2209075152, -2209075148,
-2209075143, -2209075135, -2209075129, -2209075125, -2209075039,
-2209075034, -2209075029, -2209075025, -2209075020, -2209075015,
-2209075010, -2209075005, -2209075001, -2209074997), class =
c("POSIXct",
"POSIXt"), tzone = "UTC"), T0_1 = c(0.601, 0.534, 0.601,
0.567, 0.601, 0.601, 0.584, 0.6, 0.567, 0.6, 0.422, 0.372,
0.339, 0.355, 0.288, 0.272, 0.339, 0.289, 0.222, 0.289),
T1_Ball_Ht = c(1.04, 1.03, 1.02, 1.03, 1.04, 1.05, 1.04,
1.03, 1.03, 1.04, 0.97, 0.94, 0.95, 0.96, 0.97, 0.96, 0.95,
0.94, 0.95, 0.96), T1_Knee_Ext = c(116.3, 119.6, 122.9, 119.2,
127.4, 126.9, 134.4, 129, 134.5, 134.4, 112.3, 116.4, 122.3,
119.7, 121.6, 121.6, 117.7, 117.7, 117.7, 117.7), T1_Hip_Ext = c(142,
138.4, 138.4, 138.4, 142.9, 147.9, 147.9, 147.9, 147.9, 147.9,
133.5, 133.5, 141.5, 148.2, 145.4, 145.4, 145.4, 145.4, 145.4,
145.4), T2 = structure(c(-2209075174, -2209075169, -2209075163,
-2209075157, -2209075152, -2209075148, -2209075142, -2209075135,
-2209075129, -2209075125, -2209075039, -2209075034, -2209075029,
-2209075025, -2209075020, -2209075014, -2209075010, -2209075005,
-2209075001, -2209074997), class = c("POSIXct", "POSIXt"), tzone =
"UTC"),
T1_2 = c(0.267, 0.3, 0.3, 0.267, 0.266, 0.283, 0.267, 0.267,
0.3, 0.3, 0.267, 0.267, 0.283, 0.217, 0.267, 0.333, 0.284,
0.267, 0.334, 0.267), T0_2 = c(0.868, 0.834, 0.901, 0.834,
0.867, 0.884, 0.851, 0.867, 0.867, 0.9, 0.689, 0.639, 0.622,
0.572, 0.555, 0.605, 0.623, 0.556, 0.556, 0.556), T2_Sh_Flex =
c(137.3,
140.8, 134.2, 138.6, 138, 138.6, 138.6, 134.2, 134.2, 140.8,
138, 138, 136, 136, 136, 137, 137, 136, 136, 136), T2_Elb_Ext =
c(179.8,
179.8, 179, 179, 178.5, 179.4, 179.2, 179, 178.9, 179.8,
174.9, 174.9, 174.9, 174.9, 174.9, 175, 174.8, 174.9, 175,
174.8), T2_Rel_Ht = c(2.17, 2.18, 2.17, 2.18, 2.17, 2.17,
2.18, 2.17, 2.18, 2.17, 2.17, 2.17, 2.18, 2.17, 2.17, 2.18,
2.17, 2.18, 2.18, 2.17), T2_Jump_Ht = c(0.05, 0.06, 0.05,
0.06, 0.05, 0.05, 0.06, 0.05, 0.06, 0.05, 0.05, 0.05, 0.06,
0.05, 0.05, 0.06, 0.05, 0.06, 0.06, 0.05), T2_Wr_Ext = c(109.3,
106.8, 106.8, 106.8, 107.9, 109.1, 106.8, 107.8, 107, 107.5,
120, 113.5, 107.9, 100.5, 100.5, 100.5, 100.5, 100.5, 100.5,
100.5), CONDITIONf = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label =
c("Normal",
"None", "Wrist", "Elb. Ht.", "Rim"), class = "factor"), Makef =
c("Make",
"Make", "Miss", "Make", "Miss", "Make", "Make", "Miss", "Make",
"Make", "Miss", "Miss", "Miss", "Miss", "Miss", "Make", "Make",
"Miss", "Miss", "Miss"), ACCURACYf = c("Inside Rim - Make",
"Inside Rim - Make", "Inside Rim - Miss", "Inside Rim - Make",
"Inside Rim - Miss", "Inside Rim - Make", "Inside Rim - Make",
"Inside Rim - Miss", "Top Rim - Make", "Inside Rim - Make",
"Top Rim - Miss", "Outside Rim", "Outside Rim", "Outside Rim",
"Top Rim - Miss", "Inside Rim - Make", "Inside Rim - Make",
"Outside Rim", "Top Rim - Miss", "Top Rim - Miss"), ACCURACYnorm =
c(0.875,
0.875, 0.75, 0.875, 0.75, 0.875, 0.875, 0.75, 0.625, 0.875,
0.5, 0.25, 0.25, 0.25, 0.5, 0.875, 0.875, 0.25, 0.5, 0.5),
T0_2norm = c(0.317038102084831, 0.292595255212078, 0.340762041696621,
0.292595255212078, 0.316319194823868, 0.328540618260244,
0.304816678648454, 0.316319194823868, 0.316319194823868,
0.340043134435658, 0.188353702372394, 0.152408339324227,
0.14018691588785, 0.104241552839684, 0.092020129403307,
0.127965492451474,
0.140905823148814, 0.0927390366642703, 0.0927390366642703,
0.0927390366642703), T0_2norm.inv = c(0.682961897915169,
0.707404744787922, 0.659237958303379, 0.707404744787922,
0.683680805176132, 0.671459381739756, 0.695183321351546,
0.683680805176132, 0.683680805176132, 0.659956865564342,
0.811646297627606, 0.847591660675773, 0.85981308411215,
0.895758447160316,
0.907979870596693, 0.872034507548526, 0.859094176851186,
0.90726096333573, 0.90726096333573, 0.90726096333573), Acc.Spd =
c(1.55796189791517,
1.58240474478792, 1.40923795830338, 1.58240474478792,
1.43368080517613,
1.54645938173976, 1.57018332135155, 1.43368080517613,
1.30868080517613,
1.53495686556434, 1.31164629762761, 1.09759166067577,
1.10981308411215,
1.14575844716032, 1.40797987059669, 1.74703450754853,
1.73409417685119,
1.15726096333573, 1.40726096333573, 1.40726096333573)), .Names =
c("X1",
"PRIM_KEY", "NAME", "SUBJECT", "BIRTHDAY", "TODAY_DATE", "AGE",
"YOE", "DAILY_SHOTS", "CLIP", "HEIGHT", "Group", "CONDITION",
"SHOT", "ACCURACY", "Make", "T0", "T0_Knee_Ext", "T0_Hip_Ext",
"Min_Ball_Ht", "T1", "T0_1", "T1_Ball_Ht", "T1_Knee_Ext", "T1_Hip_Ext",
"T2", "T1_2", "T0_2", "T2_Sh_Flex", "T2_Elb_Ext", "T2_Rel_Ht",
"T2_Jump_Ht", "T2_Wr_Ext", "CONDITIONf", "Makef", "ACCURACYf",
"ACCURACYnorm", "T0_2norm", "T0_2norm.inv", "Acc.Spd"), row.names = c(NA,
-20L), class = c("tbl_df", "tbl", "data.frame"))