Flexdashboard Shiny - output not showing the complete output after knitting - r

Question

When I knitting the following code in Flexdashboard in R Markdown file, the entire file is not giving output on the entire page, however when I run the code chunk individually it is showing the correct output.
I have tried adjusting Column {width } as well, but nothing is happening.
title: "By sachin"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: fill
library(flexdashboard)
Page 1
Column {data-width=650}
Chart A
library(dplyr)
library(tidyverse)
library(ggplot2)
df <- read.csv("data.csv")
#view(df)
df1 <- subset(df, select = c("year","dem","all_pass"))
#str(df1)
df1$dem <- as.character(df1$dem)
df1$dem = factor(df1$dem, levels = c(0,1),
labels = c("Democrat","Republic"))
#view(df2)
#colnames(df2)<-c("Year","Party","All Bills Passed")
df2 <-df1 %>% group_by(year,dem) %>% summarise_at(vars(all_pass),funs(sum(. , na.rm = TRUE)))
#df2 <-df1 %>% group_by(year,dem ) %>% summarise_at(vars(all_pass),funs(sum(. , na.rm = TRUE)))
ggplot(df2, aes(x=year, fill = dem )) + geom_area(aes(y = all_pass))+labs(y = "All Bills Passed", x = "Year", title = "Number of bills passed since 1980")
Page 2
Column {data-width=500}
Chart B
library(dplyr)
library(tidyverse)
library(broom)
library(ggplot2)
library(plotly)
#install.packages("jtools")
library(jtools)
df <- read.csv("data.csv")
df <- filter(df, df$congress==110)
#view(df)
df3 <- subset(df, select = c(dem, all_pass,votepct))
#view(df3)
#df3 <- filter(df3, dem ==0 & dem ==1)
#view(df3)
df3$dem <- as.character(df3$dem)
df3$dem = factor(df3$dem, levels = c(0,1),
labels = c("Democrat","Republic"))
#view(df3)
#fit<- lm(formula = votepct~dem,df3)
ggplot(df3, aes(x=votepct,y = all_pass, fill = dem,colour = dem )) + geom_point(aes(y = all_pass),size=3)+labs(y = "All Pass", x = "votepct", title = "Passage and Vote Pct , 110th Congress")+ geom_smooth(method="lm")
#df4 <-df3 %>% group_by(dem) %>% summarise_at(vars(all_pass),funs(sum(. , na.rm = TRUE)))
#view(df4)
#abline(fit)
#effect_plot(fit, pred = "dem",interval = TRUE, plot.points = TRUE)
#(fit, pred = votepct, interval = TRUE, plot.points = TRUE)
Column {data-width=500}
Chart C
library(dplyr)
library(tidyverse)
library(broom)
library(ggplot2)
library(plotly)
#install.packages("jtools")
library(jtools)
df <- read.csv("data.csv")
df <- filter(df, df$congress==110)
#view(df)
df5 <- subset(df, select = c(dem, all_pass,dwnom1))
#view(df5)
#df3 <- filter(df3, dem ==0 & dem ==1)
#view(df3)
df5$dem <- as.character(df5$dem)
df5$dem = factor(df5$dem, levels = c(0,1),
labels = c("Democrat","Republic"))
#view(df5)
fit<- lm(formula = all_pass~dwnom1,df5)
ggplot(df5, aes(x=dwnom1,y = all_pass, fill = dem,colour = dem )) + geom_point(aes(y = all_pass),size=3)+labs(y = "All Pass", x = "DW Nominate", title = "Passage and Ideology , 110th Congress")+geom_smooth(method="lm")
Page 3
Column {data-width=650}
Chart D
library(ggplot2)
library(plotly)
library(dplyr)
library(shiny)
ui <- basicPage(
h1("Total bills passed by state delegation, 110th Congress"),
selectizeInput(inputId = "bins",
label = "Choose State",
choices = state.abb,
multiple = TRUE),
plotOutput("plot")
)
server <- function(input, output) {
df <-
tibble(all_pass = sample(1:500, 350),
st_name = rep(state.abb, 7))
output$plot <- renderPlot({
req(input$bins)
df |>
filter(st_name %in% input$bins) |>
ggplot(aes(y = all_pass,x=st_name )) +
geom_bar(stat = "sum")
})
}
shinyApp(ui = ui, server = server)