paleolimbot

library(tidyverse)
library(ggdebug)

calls_use_method <- function(expr) {
  if (rlang::is_call(expr, "UseMethod")) {
    TRUE
  } else if (is.call(expr)) {
    any(map_lgl(expr, calls_use_method))
  } else {
    FALSE

paleolimbot

library(ggplot2)
library(dplyr)
library(tibble)

SortingRange <- ggproto(
  "SortingRange", ggplot2:::Range,
  counted_range = tibble(value = character(0), n = integer(0)),
  
  train = function(self, x, ...) {
    new_counted_range <- tibble(value = x) %>%

paleolimbot

# remotes::install_github("paleolimbot/ggplot2@2b2f4fb9ad8ada3c2f614185441db1d790b8db2e")
library(ggplot2)
ggplot(mpg, aes(class, hwy)) +
  geom_point() +
  guides(
    y = guide_axis(order = 2),
    y.sec = guide_axis(position = "left", order = 2, angle = 45)
  )

paleolimbot

# remotes::install_github("paleolimbot/ggplot2@2b2f4fb9ad8ada3c2f614185441db1d790b8db2e")
library(ggplot2)

# plot with overlapping text
p <- ggplot(mpg, aes(cty * 100, hwy * 100)) +
  geom_point() +
  facet_wrap(vars(class))

# axis guides can now be customized!

paleolimbot

library(ggplot2)

symmetric_range <- function(range) {
  max_abs <- max(abs(range))
  c(-max_abs, max_abs)
}

ggplot(mpg, aes(cty, hwy)) + 
  geom_point() +

paleolimbot

library(ggplot2)
library(ggdebug) # remotes::install_github("paleolimbot/ggdebug")

# the classic ggplot!
ggplot(mpg) +
  geom_point(aes(x = displ, y = hwy, colour = class)) 

# ...is really this:
p <- ggplot(mpg) +

paleolimbot

paleolimbot

library(tidyverse)

# best case: your data is already in the right form
perfect_data <- tibble(
  day_in_year = c(1, 101, 201, 1, 101, 201, 1, 101, 201),
  depth = c(1, 1, 1, 2, 2, 2, 3, 3, 3),
  temp = c(15, 16, 17, 14, 15, 16, 13, 14, 15)
)

ggplot(perfect_data, aes(x = day_in_year, y = depth, fill = temp)) +

paleolimbot

import sys

from PyQt5.QtWidgets import QMainWindow, QApplication


class MainWindow(QMainWindow):

    def __init__(self, parent=None):
        super().__init__(parent)

paleolimbot

library(tidyverse)

files <- crossing(
  tibble(station_id = 42583, timeframe = 1),
  tibble(year = 2018:2019),
  tibble(month = 1:12)
) %>%
  mutate(
    url = glue::glue(
      "http://climate.weather.gc.ca/climate_data/bulk_data_e.html?format=csv&Month={month}&stationID={station_id}&submit=Download%20Data&timeframe=1&Year={year}"