darokun

## -------------------------- ##
## An R Function that Shades  ##
## under a normal density.    ##
##                            ##
## This is a convenience      ##
## function for polygon()     ##
## -------------------------- ##

shadenorm = function(below=NULL, above=NULL, pcts = c(0.025,0.975), mu=0, sig=1, numpts = 500, color = "gray", dens = 400,
                   lines=FALSE,between=NULL,outside=NULL){

darokun

# Finding square numbers that are also triangular numbers

# This snippet of code has been inspired by Matt Parker's book: Things to make and do in the fourth dimension, Chapter 3, pg. 50

# Square numbers
SqNum <- function(to, from = 1) {
  x <- NULL
  for(i in seq(from = from, to = to)) {
    x[i] <- i^2
  } 

darokun

library(RColorBrewer)
qual_col_pals <- brewer.pal.info[brewer.pal.info$category == 'qual',]
col_vector <- unlist(mapply(brewer.pal, qual_col_pals$maxcolors, rownames(qual_col_pals)))

#check
myunif <- runif(40, 1, 1)
barplot(myunif, col = col_vector)

darokun

construction <- as.Date("1961-08-13")
fall <- as.Date("1989-11-09")
now <- as.Date("2018-02-06")

now-fall > fall-construction

fall-construction
now-fall

darokun

# Based on this blog post: https://www.r-bloggers.com/updating-r/

### 1
## Change accordingly
list_dir <- "/Library/Frameworks/R.framework/Resources/library"

## Get the list of installed packages
installed <- dir(.libPaths())

## Save the list for later use

darokun

library(tidyverse)
library(readxl)
library(stringr)



xl_data <- read_excel("Feedback_Job_Interview.xlsx")

col_names <- c("student", "date", "preparation", "fluency", "grammar", "vocabulary", "questions", "grade", "comments")
colnames(xl_data) <- col_names

darokun

install.packages("extrafont")
install.packages("extrafontdb")

library(extrafont)
library(extrafontdb)
library(ggplot2)

# make sure to install the desired font in the computer at this point

# then:

darokun

# from a tweet I found around, by @WeAreRLadies maybe?

x <- 1:4
y <- 3:6

compare <- function(x, y) {
  list(
    "These values are in x but not in y" = setdiff(x, y),
    "These values are in y but not in x" = setdiff(y, x),
    "These values are shared between x and y" = intersect(x, y),

darokun

pacman::p_load(tidyverse, suncalc, ggimage, lubridate)
src_calendR <- "https://raw.githubusercontent.com/R-CoderDotCom/calendR/master/R/calendR.R"
download.file(src_calendR, "calendR.R")
source("calendR.R") # installing package doesn't work in my system (old R version), sourcing instead.
days_until_20201130 <- seq(ymd("20200101"), ymd("20201130"), "days")

### habits to track
# arms
calendR(orientation = "landscape", pdf = TRUE, doc_name = "arms_cal2020", special.days = 1:length(days_until_20201130), special.col = "black", low.col = "white", title = "arms 2020")
calendR(year = 2021, orientation = "landscape", pdf = TRUE, doc_name = "arms_cal2021", title = "arms 2021")

darokun

# data from http://www.edisonresearch.com/wp-content/uploads/2017/04/Podcast-Consumer-2017.pdf
library(tidyverse)

set.seed(20210311)
podcast_women <- tibble(
  gender = rep("female", 2000*.44),
  y2013 = sample(c("yes", "no"), size = 2000*.44, replace = TRUE, prob = c(0.09, 1 - 0.09)),
  y2014 = sample(c("yes", "no"), size = 2000*.44, replace = TRUE, prob = c(0.13, 1 - 0.13)),
  y2015 = sample(c("yes", "no"), size = 2000*.44, replace = TRUE, prob = c(0.16, 1 - 0.16)),
  y2016 = sample(c("yes", "no"), size = 2000*.44, replace = TRUE, prob = c(0.18, 1 - 0.18)),