luisDVA

# expanding a series, consecutive values
# by Filipe Chichorro, modified for vectors
expandSeries <- function(strStartEnd){
  
  words<-strsplit(strStartEnd, " ")
  
  if (length(words[[1]])== 1) return(strStartEnd)
   
  else
    

luisDVA

## UNTANGLE FUNCTION
#  Luis D. Verde (www.liomys.mx)
#' Pull interspersed header data into own column
#'
#' @param dframe The tibble or data frame with the interspersed headers in the first column
#' @param matchstring the string to match to pull the header rows (quoted character)
#' @param newCol name for the new variable that will be added to the df (quoted char)
#' @return a tbl or df (depending on the input) with the interspersed headers in their own column
#' @export
#' 

luisDVA

# define function
# this code is just for fun and I do not have rights to the images on dogtime.com I just like dogs

ggpupBV <- function(ggplotObject,breedVector){
  
  # required packages 
  require(dplyr)
  require(jpeg)
  require(grid)
  require(gridExtra)

luisDVA

# define function
# this code is just for fun and I do not have rights to the images on dogtime.com I just like dogs

ggpup <- function(ggplotObject){

# required packages 
  require(dplyr)
  require(jpeg)
  require(grid)
  require(gridExtra)

luisDVA

# crear tabla de datos
ventas <- data.frame(vend = LETTERS[sample(15,replace=F)],
                     artsVend = sample(9:70, 15, replace = T),
                     totalv = sample(300:7900, 15, replace=T))

# cargar paquetes adicionales (instalar primero si es necesario)
library(ggplot2)
devtools::install_github("hrbrmstr/ggalt")
devtools::install_github("hrbrmstr/hrbrthemes")
library(ggalt)

luisDVA

library(ggplot2)

dat <- data.frame(x=rnorm(20,4,2),y=rnorm(20,3,2))

theme_Eiffel65 <- function(base_size = 12, base_family = "") { 
  # modification to theme_grey  
  theme_grey(base_size = base_size, base_family = base_family) %+replace% 
    theme( 
      axis.text         = element_text(size = rel(0.8),colour = "blue"), 
      axis.title        = element_text(colour = "blue"),

luisDVA

# point overlap, LDVA
# load 
library(sp)
library(dplyr)
library(ggplot2)
library(ggmap)
library(fields)
library(cowplot)
library(rgbif)
library(gridExtra)

luisDVA

library(ggplot2)
library(dplyr)
library(gridExtra)
library(rphylopic)

MammalDisc <- read.csv(file = "https://raw.githubusercontent.com/luisDVA/codeluis/master/mammalDiscoveries.csv",stringsAsFactors = FALSE)

# plot search results by order for all orders
ggplot(MammalDisc,aes(results,reorder(sp,descYear)))+
  geom_point() + theme_minimal() + theme(axis.text.y = element_blank())+

luisDVA

# mapping conservation research

#load libraries
library(geosphere)
library(dplyr)
library(StandardizeText)
library(ggmap)
library(maps)
library(rvest)
library(rworldmap)

luisDVA

#Package load

library(dplyr)
library(reshape2)
library(ggplot2)
library(devtools)
install_github('timcdlucas/palettetown')
library(palettetown)

# read the data directly from the repo