gkaramanis

library(tidyverse)
library(ggforce)

bl_gradient <- grid::linearGradient(colours = rev(c("gray40", "#9B9B9B")),
                                    stops = c(0.12, 0.4, 0.6))

br_gradient <- grid::linearGradient(colours = rev(c("grey10",  "#484848")),
                                    x1 = unit(0, "npc"), y1 = unit(0, "npc"), 
                                    x2 = unit(1, "npc"), y2 = unit(1, "npc"),
                                    stops = c(0, 0.5, 0.8))

gkaramanis

library(tidyverse)
library(ggstream)

papers <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-09-28/papers.csv')
programs <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-09-28/programs.csv')
paper_programs <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-09-28/paper_programs.csv')

pp <- programs %>%
  mutate(program_category = replace_na(program_category, "Technical")) %>% 
  left_join(paper_programs) %>% 

gkaramanis

library(ggforce)
library(dplyr)

l <- data.frame(a = c(100, 50, 10)) %>% 
  mutate(
    r = sqrt(a/pi),
    x0 = 0,
    y0 = r
    )

gkaramanis

library(ggplot2)
library(cowplot)

p <- ggplot(mtcars, aes(cyl, disp)) +
  geom_point() +
  labs(title = "But  China  and  India") +
  theme(
    plot.background = element_rect(fill = "transparent")
  )

gkaramanis

library(ggfittext)
library(ggplot2)

sensor_data = data.frame(
  value = runif(8, min = 0, max = 120),
  label = paste0("sensor", 1:8)
)

ggplot(sensor_data) +
  geom_col(aes(x = label, y = value)) +

gkaramanis

--==============================
-- Send Keynote Text to Desktop Markdown File
-- Writted By: Richard Dooling https://github.com/RichardDooling/
-- Based on 
-- Send Keynote Presenter Notes to Evernote
-- Version 1.0.1
-- Written By: Ben Waldie <[email protected]>
-- http://www.automatedworkflows.com

-- Version 1.0.0 - Initial release

gkaramanis

library(ggplot2)
library(tidyr)
library(viridis)

df <- data.frame(x = 1:10, y = 1:10) %>% expand(x, y) %>% mutate(n = as.integer(runif(min = 0, max = 26, n = 100)))

pal <- c(viridis(n = 23), "black", "purple", "pink")

ggplot(df, aes(x, y, fill = factor(n))) +
  geom_tile() +

gkaramanis

library(ggplot2)
library(grid)

myGrob <- grobTree(rectGrob(gp = gpar(fill = "purple", alpha = 0.5)))

ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) +
  geom_point() +
  annotation_custom(myGrob, xmin = -10, xmax = -1, ymin = -10, ymax = Inf) + # x axis
  annotation_custom(myGrob, xmin = -10, xmax = Inf, ymin = -10, ymax = -1) + # y axis
  coord_cartesian(xlim = c(0, 10), ylim = c(0, 10), clip = "off") +

gkaramanis

library(ggplot2)

ggplot(data = data.frame(x = c(-4, 6)), aes(x)) +
  stat_function(fun = dnorm, n = 101, args = list(mean = 0, sd = 1), geom = "area", fill = "#F5BB87", alpha = 0.9) +
  stat_function(fun = dnorm, n = 101, args = list(mean = 2.7, sd = 1), geom = "area", fill = "#BBD4EB", alpha = 0.9) +
  coord_fixed(xlim = c(-5, 7), ratio = 8, clip = "off") +
  annotate("segment", x = -3.9, y = 0, xend = 6, yend = 0, color = "grey60", size = 1.3) +
  annotate("segment", x = -3.5, y = -0.04, xend = -3.5, yend = 0.42, color = "grey60", size = 1.3) +
  annotate("text", x = 0, y = 0.18, label = "what people\nactually do\nin R", family = "Arial Bold", color = "white", size = 5.2) +
  annotate("text", x = 2.75, y = 0.18, label = "what people\nassume others\ndo in R", family = "Arial Bold", color = "white", size = 5.2) +

gkaramanis

library(ggforce)
library(ggplot2)

leaf <- data.frame(
  x = c(1.6, 1.5, 1.8, 1.5, 1.6, 1.3),
  y = c(2, 2, 1.5, 1, 1, 1.5)
)

ggplot(leaf, aes(x, y)) +
  geom_polygon(fill = NA, colour = 'grey') +