tysonwepprich

# Thanks to @greghirson who totally knocked this out of the park! 
# Based on his work, here's a simple script to pull monthly prices from the USDA NASS website.

library(RCurl)
library(XML)

x <- postForm(uri = "http://quickstats.nass.usda.gov/uuid/encode",
  source_desc = "SURVEY", sector_desc="CROPS", 
  group_desc="FIELD CROPS", commodity_desc="CORN",
  statisticcat_desc="PRICE RECEIVED", 

tysonwepprich

# maps of my Strava data
# code modified from Xavi Gimenez 
# http://www.xavigimenez.net/blog/2015/04/mapping-3-years-of-running-workouts/


library(plotKML)
library(ggplot2)
library(ggmap)
library(stringr)
library(lubridate)

tysonwepprich

# Start with all Lepidoptera museum records from
# Boyle, J., H. Dalgleish, and J. Puzey. 2019a. 
# Data from: Monarch butterfly and milkweed declines substantially predate 
# the use of genetically modified crops. Dryad Digital Repository.
# https://datadryad.org/resource/doi:10.5061/dryad.sk37gd2

# these data were downloaded, cleaned, and saved with code provided in Dryad: 
# PART 1.1 Filtering museum data.R
lep <- readRDS("lep_records.rds")

tysonwepprich

# Install these packages if you don't have them
library(dplyr)
library(tidyr)
library(ggplot2)
library(elo)
library(ggrepel)
'%!in%' <- function(x,y)!('%in%'(x,y))

# babynames <- read.csv("data/national.csv", header = TRUE, stringsAsFactors = FALSE) # From SS admin download
babynames <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-03-22/babynames.csv')