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library(shiny)
library(DT)
library(dplyr)

ui <- basicPage(
  tags$style(".glyphicon-ok-sign {color:#2b8ee5}
              .glyphicon-question-sign {color:#f4e107}
              .glyphicon-exclamation-sign {color:#e5413b}
              .glyphicon-flag, .glyphicon-trash {color:#28b728}"),
  DT::dataTableOutput("table")

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library(shiny)
library(shinyjs)
source("module.R")

# UI ==========================================================================
ui <- fluidPage(
  useShinyjs(),
  radioButtons("mode", "Mode",
               choices = c("Entry" = "entry",
                           "Validation" = "validation"),

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df <- replace(df, df == "NA", NA)

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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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# 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(ggplot2)

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