Skip to content

Instantly share code, notes, and snippets.

Marcus W Beck fawda123

Block or report user

Report or block fawda123

Hide content and notifications from this user.

Learn more about blocking users

Contact Support about this user’s behavior.

Learn more about reporting abuse

Report abuse
View GitHub Profile
@fawda123
fawda123 / asci_csci_diff.R
Created Mar 22, 2019
plot asci/csci diff by nuts and hab
View asci_csci_diff.R
library(tidyverse)
library(patchwork)
toplo1 <- sqidat %>%
select(MasterID, yr, asci_mean, csci_mean, TN, TP, indexscore_cram) %>%
gather('nuts', 'val', TN, TP) %>%
na.omit %>%
mutate(
inddif = asci_mean - csci_mean,
cramcat = case_when(
@fawda123
fawda123 / evaldat
Last active Jun 23, 2018
limits of imputePSF, compared with na.mean on simulated time series
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')
@fawda123
fawda123 / plotFlowConc.r
Created Aug 29, 2016
plotFlowConc for OWI blog
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
You can’t perform that action at this time.