andrewmoles2

# import plotnine for demo and testing
from plotnine import *
from plotnine.data import mtcars

def coolors(URL):
    # function takes coolors url, extracts hex codes and adds #
    if URL.find("palette") != -1:
    # extract just the hex
        cstr = URL.replace("coolors.co", "")
        cstr = cstr.replace("https:///", "")

andrewmoles2

# Function for generating coolors hex codes

coolors <- function(URL) {
#' Coolors hex generator
#' 
#' Function for taking coolors URL that contains hex codes, and extracting that information so we can use the hex codes
#' Currently works for palettes in: palette generator, explore palettes, and gradients
#' @param URL a URL from https://coolors.co/ that contains hex codes, e.g. https://coolors.co/ddfcad-c8e087
  
  # detect if from default or explored palettes

andrewmoles2

# function to check install and load packages
load_library <- function(pkg) {
  # check if package is installed
  new_package <- pkg[!(pkg %in% installed.packages()[, "Package"])]
  
  # install any new packages
  if (length(new_package)) 
    install.packages(new_package, dependencies = TRUE, Ncpus = 6)
  
  # sapply to loop through and load packages

andrewmoles2

# script to upgrade R and re-install all (or at least most) packages

# Pre-upgrade: save your packages as an rds file
my_pkg <- pak::pkg_list()

# if loaded from RStudio 
#here::here("R", "update_packages", "my_packages.rds") 
# if loaded from finder
saveRDS(object = my_pkg, file = "my_packages.rds") 

andrewmoles2

# code from http://r.iresmi.net/2023/04/05/cherry-blossom/ written into function for future use

get_blossom <- function(url = "http://atmenv.envi.osakafu-u.ac.jp/aono/kyophenotemp4/") {
  GET(url) |> 
    content() |> 
    html_element("pre") |>
    html_text2() |>  
    str_replace_all("\xc2\xa0", " ") |> # bad encoding needs correction
    read_fwf(fwf_cols("ad"   = c(7, 10), 
                      "fifd" = c(17, 20), 

andrewmoles2

# function to make table of descriptive statistics
# rows are column names, columns are the descriptives (mean, min etc.)

descriptive_tab <- function(df, cols, round_digits = 2) {
  
  # cols needs to be a vector
  # cols <- c('col1', 'col2', 'col3')
  
  tab <- data.frame(
    t(

andrewmoles2

def clean_names(cols):
    current_cols = cols
    new_cols = []
    for c in range(0, len(current_cols)):
        new_cols.append(
            current_cols[c].lower().replace(' ', '_').replace('(', '').replace(')', '')
        )
    return(new_cols)
    
# we use the .columns method to access the column names