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library(dplyr)
library(ggplot2)
library(tidytext)
library(tm)
library(wordcloud)


# input: a dataframe called raw, in this case the text col is biggest_concern, and X is the ID col

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base <- knitr::kable(final ,"latex", booktabs = T, longtable = T, align = c("l", "r", "r", "r", "r", "r"))
  
  

  
plott <- base %>%  
  
 kableExtra::kable_styling(
    latex_options = c("scale_down"),

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pandoc -s -o book/final_book.md src/*.md --toc --standalone 

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‎‎​

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select * from dual

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library(RSelenium)
library(tidyverse)

# RSELENIUM INSTALL ISSUES ####

# If you have difficulty installing RSelenium from CRAN, try installing with Devtools:
# install.packages("devtools") 
# devtools::install_github("johndharrison/binman")
# devtools::install_github("johndharrison/wdman")
# devtools::install_github("ropensci/RSelenium")

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using Cascadia, Gumbo, HTTP

r = HTTP.get("http://stackoverflow.com/questions/tagged/julia-lang", require_ssl_verification = false)
h = parsehtml(String(r.body))

qs = eachmatch(Selector(".question-summary"),h.root)

println("StackOverflow Julia Questions (votes  answered?  url)")

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library(sf)
library(tidyverse)
library(tidyUSDA)
library(leaflet)



# Make some random lon lat coord pairs ------------------------------------

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save(branches, file = "data/branches.RData")

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branches <- read.csv("O:\\exchange\\branches.csv", header = T)