View evaldat
library(tidyverse)
library(gridExtra)
library(grid)
library(imputeTestbench)
library(PSF)
library(imputePSF)
library(imputeTS)
library(scales)
# total obs in each simulated time series
View tmapex
# load libraries
library(sf)
library(maps)
library(tmap)
# get states as sf
states <- st_as_sf(map('state', plot = F, fill = T))
# calculate area, add to states
area <- st_area(states)
View gist:1870bb6f093b86139addcc515503a39e
# load packages
library(sf)
library(plotly)
library(mapview)
# download data and save in memory
wsa <- read.csv("https://www.epa.gov/sites/production/files/2014-10/wsa_siteinfo_ts_final.csv")
# make an sf object
wsa <- st_as_sf(wsa, coords = c("LON_DD", "LAT_DD"), crs = 4269,agr = "constant")
View chloroex
# load libraries
library(sf)
library(maps)
library(ggplot2)
# get states as sf
states <- st_as_sf(map('state', plot = F, fill = T))
# calculate area, add to states
area <- st_area(states)
View meuse exercise
# load libraries
library(sp) # for meuse
library(sf) # for sf objects
library(ggmap) # for base maps
library(ggplot2) # for mapping
# import dataset, check structure
data(meuse)
str(meuse)
View basic-mappingex1
---
title: "Basic mapping"
author: "Turbo Todd"
output: html_document
---
This lessons covers base graphics, ggplot, and other R packags for mapping spatial data.
```{r}
library(maps)
View gist:5ecb73e1304e7faee83eb05b922937e7
echo sha, contributor, date, message > log.csv
git log --date=local --pretty=format:'%h, %an, %ad, "%s"' >> log.csv
View moth_form.R
#' Format a text file for mothur
#'
#' @param fl chr string for input file
#' @param rev_cmp logical if file needs reverse complemeNT
#' @param savefl logical if output file is saved, otherwise the output is returned in the console
moth_form <- function(fl, rev_cmp = FALSE, savefl = TRUE, flnm = 'myfile.txt'){
# import file
dat <- read.table(fl, sep = '\t')
View plotFlowConc.r
plotFlowConc <- function(eList, month = c(1:12), years = NULL, col_vec = c('red', 'green', 'blue'), ylabel = NULL, xlabel = NULL, alpha = 1, size = 1, allflo = FALSE, ncol = NULL, grids = TRUE, scales = NULL, interp = 4, pretty = TRUE, use_bw = TRUE, fac_nms = NULL, ymin = 0){
localDaily <- getDaily(eList)
localINFO <- getInfo(eList)
localsurfaces <- getSurfaces(eList)
# plot title
toplab <- with(eList$INFO, paste(shortName, paramShortName, sep = ', '))
# flow, date info for interpolation surface
View PPOTM.r
# PPOTM: Practical-Programming Of The Month (2016 January)
# iMAINloop: Continue asking users "what file to load" until they type a zero.
iMAINloop <- 0;
while (iMAINloop < 1 ) {
# Below creates a list of all files (in the current working directory) of pattern *.csv
# Note that you can set path="xxxx" to look in a different folder area
filenames <- list.files(pattern = ".csv")