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library(tidyverse) | |
library(here) | |
papers_filenames <- list.files(path = here::here("Library"), | |
pattern = "(201[8-9]|2020)", | |
full.names = TRUE) | |
file.copy(from = papers_filenames, to = here::here("Library", "subset")) |
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# PLASMID - abbreviations script | |
# install.packages("tidyverse") # run only if not previously installed | |
# install.packages("googlesheets4") # run only if not previously installed | |
library(tidyverse) | |
library(googlesheets4) | |
gs4_deauth() # deactivate authorization mode so it doesn't ask for google sign-in. Useful when only reading data | |
# read data | |
abb <- read_sheet("https://docs.google.com/spreadsheets/d/1ePlZC0FmFuqiq0B59wtNu4RCDEgypn_ucyBzFb8oK0g/edit#gid=0") |
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# install.packages("ggchicklet", repos = "https://cinc.rud.is") | |
library(ggchicklet) | |
library(tidyverse) | |
x <- rep(letters[1:7], seq.int(0, 30, 5)) | |
hb <- tibble(x) | |
hex_codes1 <- scales::hue_pal()(length(unique(hb$x))) | |
p1 <- ggplot(count(hb, x), aes(x = x, y = n)) + | |
geom_chicklet(radius = grid::unit(2, 'mm'), fill = hex_codes1, colour = "black") + |
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# log_scale_exercises.R | |
format(1*10^-4, scientific = FALSE) # starting point: 1*10^-4 = 1e-04 = 0.0001 | |
format(1*10^-3, scientific = FALSE) # ending point: 1*10^-3 = 1e-03 = 0.001 | |
x <- seq(0.0001:0.001, by = 0.0001, length.out = 10) # 10 datapoints ascending from 0.0001 to 0.001 | |
format(x, scientific = FALSE) # 0.0001, 0.0002, 0.0003, [...], 0.0008, 0.0009, 0.001 | |
format(x, scientific = TRUE) # the same, but in scientific notation: 1e-04, 2e-04, 3e-04, [...], 8e-04, 9e-04, 1e-03 | |
plot(x, xlim = c(0, 10), ylim = c(0.0001, 0.001), pch = 20, log = "y") # plot log scale on y axis, (intervals are not equally spaced) | |
plot(x, xlim = c(0, 10), ylim = c(0.0001, 0.001), pch = 20) # plot linear scale, (equally spaced intervals) |
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# Causallang screening process animated plot | |
# author: Daloha Rodriguez-Molina @darokun | |
# load packages | |
library(tidyverse) | |
library(gganimate) | |
library(readxl) | |
library(here) | |
# data |
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# 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)), |
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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") |
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# 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), |
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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: |
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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 |
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