R “如何制定”;tbl变量(y)中的错误:参数;“是”;缺少,没有默认值;在闪亮?
我真的需要一些有用的帮助 我已经写了代码,但不起作用。然而,几乎同一个例子是完美的工作 以下是我得到的:R “如何制定”;tbl变量(y)中的错误:参数;“是”;缺少,没有默认值;在闪亮?,r,database,ggplot2,shiny,R,Database,Ggplot2,Shiny,我真的需要一些有用的帮助 我已经写了代码,但不起作用。然而,几乎同一个例子是完美的工作 以下是我得到的: Warning: Error in tbl_vars: argument "y" is missing, with no default Stack trace (innermost first): 45: tbl_vars 44: as.vector 43: base::intersect 42: in
Warning: Error in tbl_vars: argument "y" is missing, with no default
Stack trace (innermost first):
45: tbl_vars
44: as.vector
43: base::intersect
42: intersect.default
41: intersect
40: common_by
39: inner_join.tbl_sql
38: inner_join
1: shiny::runApp
Error in tbl_vars(y) : argument "y" is missing, with no default
我是新手,特别有光泽。
请帮忙
这是代码和+文件的附件
用户界面
库(闪亮)
图书馆(ggvis)
图书馆(数据集)
actionLink也有同样的问题,这个问题让我找到了解决方案。这里
all_c <- inner_join(corruption)
all\u c只要通读一下代码,我很确定它是这一行:all\u c UPD:启动traceback()
后,我得到:5:Sys.sleep(0.001)4:withCallingHandlers(expr,error=function(e){if(is.null)(attr(e,“stack.trace”,exact=TRUE)){调用
library(shiny)
library(ggvis)
library(dplyr)
if (FALSE) library(RSQLite)
db <- src_sqlite("corruption.db")
corruption <- tbl(db, "corruption")
all_c <- inner_join(corruption)
shinyServer(function(input, output, session) {
corruption <- reactive({
gdp <- input$gdp
gni <- input$gni
finv <- input$finv
c <- all_c %>%
filter(
CPI >= cpi,
IndexOfEconomicFreedom >= icf,
HDI >= hdi,
GINI >= gini
) %>%
arrange(CPI)
})
vis <- reactive({
xvar_name <- names(axis_vars)[axis_vars == input$xvar]
yvar_name <- names(axis_vars)[axis_vars == input$yvar]
xvar <- prop("x", as.symbol(input$xvar))
yvar <- prop("y", as.symbol(input$yvar))
corruption %>%
ggvis(x = xvar, y = yvar) %>%
layer_points(size := 50, size.hover := 200,
fillOpacity := 0.2, fillOpacity.hover := 0.5) %>%
add_axis("x", title = xvar_name) %>%
add_axis("y", title = yvar_name) %>%
set_options(width = 500, height = 500)
})
vis %>% bind_shiny("plot")
})
axis_vars <- c(
"Corruption Perception Index" = "cpi",
"Index Of Economic Freedom" = "icf",
"HDI" = "hdi",
"GINI" = "gini",
"Foreign Investments" = "finv",
"GDP per capita" = "gdp"
)
all_c <- inner_join(corruption)
all_c <- some_other_table %>% inner_join(corruption)