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library(dplyr)

iris %>% filter(grepl("se", Species))

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library(tidyr)
library(dplyr)

df <- data.frame(x = c(NA, "a|b", "a|d", "b|c"))
df %>% separate(x, c("word1", "word2"))

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library(broom)

tidy(glimpse(mtcars))

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Rscript -e "shiny::runApp('poldata_app.R')"

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# create a test file
write.table(iris, "iris.csv", sep = ",", quote = FALSE, row.names = FALSE)

# create an empty database.
# can skip this step if database already exists.
sqldf("attach testingdb as new")
# or: cat(file = "testingdb")

# read into table called iris in the testingdb sqlite database
library(sqldf)

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library(shiny)
library(dplyr)
library(ggplot2)

ui = fluidPage(
  tabsetPanel(
    tabPanel("Plot",
             plotOutput("my_plot")
    ),
    tabPanel("Data",

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# hide and show elements using conditional panel

library(shiny)

ui = basicPage(
  checkboxInput("show", "Show datatable",
                value = FALSE),
  conditionalPanel("input.show == true",
                   dataTableOutput("mtcars"))
)

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library(shiny)
library(dplyr)
library(readr)
load(url("http://s3.amazonaws.com/assets.datacamp.com/production/course_4850/datasets/movies.Rdata"))

# UI
ui <- fluidPage(
  sidebarLayout(
    
    # Input(s)

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library(shiny)
library(dplyr)
library(readr)
load(url("http://s3.amazonaws.com/assets.datacamp.com/production/course_4850/datasets/movies.Rdata"))

# UI
ui <- fluidPage(
  sidebarLayout(
    
    # Input(s)

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library(shiny)

ui = basicPage(
  textInput("txt1", "Input the first string"),
  textInput("txt2", "Input the second string"),
  
  uiOutput("cat_str")
)

server = function(input, output) {