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SWD_2019-09_Uncertainty.Rmd
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SWD_2019-09_Uncertainty.Rmd
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---
title: "SWD Challenge September 2019 - Visualizing Uncertainty"
author: "Cedric Scherer"
date: "8th of September 2019"
output:
html_document:
theme: paper
highlight: kate
editor_options:
chunk_output_type: console
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, warning=FALSE)
```
```{r prep}
library(tidyverse)
library(tidybayes)
library(patchwork)
library(cowplot)
library(extrafont)
extrafont::loadfonts(device = "win", quiet = TRUE)
theme_set(theme_minimal(base_family = "Bitter"))
```
```{r data}
## Data source: DWD (Deutscher Wetterdienst)
## https://www.dwd.de/DE/leistungen/_config/leistungsteckbriefPublication.zip?view=nasPublication&nn=16102&imageFilePath=157242051950877752011408908330930139598321949458353665338080907323067407358570939094063695252196106887026681320814526060536595251033063153662108661981192575715848535028223489905255018373803265100435386215906807083067001006526258509883339654785117109676510167984069504119&download=true
df_dwd_dahlem <-
readr::read_delim(
here::here("data", "produkt_klima_tag_19500101_20181231_00403_Dahlem.txt"),
delim = ";"
) %>%
dplyr::select(
station_id = STATIONS_ID,
date = MESS_DATUM,
t_avg = " TMK",
t_min = " TNK",
t_max = " TXK"
) %>%
mutate_all(as.numeric) %>%
mutate(
date = lubridate::ymd(date),
year = lubridate::year(date),
month = lubridate::month(date),
t_max_f = t_max * (9/5) + 32
)
```
```{r plot, fig.width = 13, fig.height = 8}
plot <-
df_dwd_dahlem %>%
filter(year >= 2000) %>%
ggplot(aes(t_max, month)) +
stat_intervalh(.width = c(.1, .25, .5, .75, 1),
height = 5, show.legend = F) +
rcartocolor::scale_color_carto_d(palette = "Peach") +
stat_halfeyeh(aes(t_max, month + 0.06),
.width = 0, fill = "tan", alpha = 0.2, height = 0.7,
size = 0.7, point_alpha = 1, point_color = "#590000") +
coord_flip(ylim = c(0.5, 13)) +
scale_x_continuous(expand = c(0, 0), limits = c(-13, 38),
breaks = seq(-10, 35, by = 5),
labels = glue::glue("{seq(-10, 35, by = 5)}°C")) +
scale_y_continuous(expand = c(0, 0), breaks = 1:12,
labels = c("January",
"February",
"March",
"April",
"May",
"June",
"July",
"August",
"September",
"October",
"November",
"December")) +
labs(x = "", y = "") +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major.y = element_line(size = 0.1),
axis.text.x = element_text(size = 11, face = "bold"),
axis.text.y = element_text(size = 9, color = "grey65"))
legend_text <-
tibble(
xt = c(5, 4.125, 3.125, 1.875, 0.625, 7.5),
yt = rep(1.02, 6),
text = c("10%", "25%", "50%", "75%", "100%", "of measured temperatures fall in this range")
)
legend <- ggplot(data = tibble(x = 0:10, y = rep(1, 11)), aes(x, y)) +
stat_intervalh(.width = c(.1, .25, .5, .75, 1), show.legend = F) +
rcartocolor::scale_color_carto_d(palette = "Peach") +
coord_cartesian(ylim = c(0.9, 1.1)) +
geom_text(data = legend_text, aes(xt, yt, label = text),
family = "Bitter", color = "grey65", size = 3) +
theme_void()
title <- ggplot(data.frame(x = 1:2, y = 1:10)) +
labs(x = NULL, y = NULL,
title = "Daily Temperatures in Berlin, Germany",
subtitle = "Range and distribution of maximum daily temperatures in Celsius per month from 2000 to 2018 measured in Berlin-Dahlem, Germany") +
theme(line = element_blank(),
plot.title = element_text(size = 26, hjust = 0, face = "bold", family = "Bitter"),
plot.subtitle = element_text(size = 13, hjust = 0, color = "grey65"),
panel.background = element_rect(fill = "transparent", color = "transparent"),
plot.background = element_rect(fill = "transparent", color = "transparent"),
panel.border = element_rect(color = "transparent"),
axis.text = element_blank())
caption <- ggplot(data.frame(x = 1:2, y = 1:10)) +
labs(x = NULL, y = NULL,
caption = "Visualization by Cédric Scherer | Data: DWD (Deutscher Wetterdienst)") +
theme(line = element_blank(),
plot.caption = element_text(size = 10, color = "grey65"),
panel.background = element_rect(fill = "transparent", color = "transparent"),
plot.background = element_rect(fill = "transparent", color = "transparent"),
panel.border = element_rect(color = "transparent"),
axis.text = element_blank())
plot_ins <- ggdraw(plot) +
draw_plot(legend, .275, .01, .525, .3)
title + plot_ins + caption + plot_layout(widths = c(0, 1, 0))
ggsave(here::here("plots", "2019_09", "SWD_2019_09_Uncertainty.pdf"),
width = 13, height = 8, device = cairo_pdf)
```
## Fahrenheit Version
```{r plot-fahrenheit, fig.width = 13, fig.height = 8}
plot_f <-
df_dwd_dahlem %>%
filter(year >= 2000) %>%
ggplot(aes(t_max_f, month)) +
stat_intervalh(.width = c(.1, .25, .5, .75, 1),
height = 5, show.legend = F) +
rcartocolor::scale_color_carto_d(palette = "PurpOr") +
stat_halfeyeh(aes(t_max_f, month + 0.06),
.width = 0, fill = "#f0c6c3", alpha = 0.2, height = 0.7,
size = 0.7, point_alpha = 1, point_color = "#3a004d") +
coord_flip(ylim = c(0.5, 13)) +
scale_x_continuous(expand = c(0, 0), limits = c(10, 105),
breaks = seq(20, 100, by = 20),
labels = glue::glue("{seq(20, 100, by = 20)}°F")) +
scale_y_continuous(expand = c(0, 0), breaks = 1:12,
labels = c("January",
"February",
"March",
"April",
"May",
"June",
"July",
"August",
"September",
"October",
"November",
"December")) +
labs(x = "", y = "") +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major.y = element_line(size = 0.1),
axis.text.x = element_text(size = 11, face = "bold"),
axis.text.y = element_text(size = 9, color = "grey65"))
legend_f <- ggplot(data = tibble(x = 0:10, y = rep(1, 11)), aes(x, y)) +
stat_intervalh(.width = c(.1, .25, .5, .75, 1), show.legend = F) +
rcartocolor::scale_color_carto_d(palette = "PurpOr") +
coord_cartesian(ylim = c(0.9, 1.1)) +
geom_text(data = legend_text, aes(xt, yt, label = text),
family = "Bitter", color = "grey65", size = 3) +
theme_void()
title_f <- ggplot(data.frame(x = 1:2, y = 1:10)) +
labs(x = NULL, y = NULL,
title = "Daily Temperatures in Berlin, Germany",
subtitle = "Range and distribution of maximum daily temperatures in Fahrenheit per month from 2000 to 2018 measured in Berlin-Dahlem, Germany") +
theme(line = element_blank(),
plot.title = element_text(size = 26, hjust = 0, face = "bold", family = "Bitter"),
plot.subtitle = element_text(size = 13, hjust = 0, color = "grey65"),
panel.background = element_rect(fill = "transparent", color = "transparent"),
plot.background = element_rect(fill = "transparent", color = "transparent"),
panel.border = element_rect(color = "transparent"),
axis.text = element_blank())
plot_ins_f <- ggdraw(plot_f) +
draw_plot(legend_f, .275, .03, .525, .35)
title_f + plot_ins_f + caption + plot_layout(widths = c(0, 1, 0))
ggsave(here::here("plots", "2019_09", "SWD_2019_09_Uncertainty_Fahrenheit.pdf"),
width = 13, height = 8, device = cairo_pdf)
```
## German Version
```{r plot-german, fig.width = 13, fig.height = 8}
plot_g <-
df_dwd_dahlem %>%
filter(year >= 2000) %>%
ggplot(aes(t_max, month)) +
stat_intervalh(.width = c(.1, .25, .5, .75, 1),
height = 5, show.legend = F) +
rcartocolor::scale_color_carto_d(palette = "Teal") +
stat_halfeyeh(aes(t_max, month + 0.06),
.width = 0, fill = "paleturquoise3", alpha = 0.2, height = 0.7,
size = 0.7, point_alpha = 1, point_color = "#003537") +
coord_flip(ylim = c(0.5, 13)) +
scale_x_continuous(expand = c(0, 0), limits = c(-13, 38),
breaks = seq(-10, 35, by = 5),
labels = glue::glue("{seq(-10, 35, by = 5)}°C")) +
scale_y_continuous(expand = c(0, 0), breaks = 1:12,
labels = c("Januar",
"Februar",
"März",
"April",
"Mai",
"Juni",
"Juli",
"August",
"September",
"Oktober",
"November",
"Dezember")
) +
labs(x = "", y = "") +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major.y = element_line(size = 0.1),
axis.text.x = element_text(size = 11, face = "bold"),
axis.text.y = element_text(size = 9, color = "grey65"))
legend_text_g <-
tibble(
xt = c(5, 4.125, 3.125, 1.875, 0.625, 7.3),
yt = rep(1.02, 6),
text = c("10%", "25%", "50%", "75%", "100%", "der Temperaturen liegen in diesem Bereich")
)
legend_g <- ggplot(data = tibble(x = 0:10, y = rep(1, 11)), aes(x, y)) +
stat_intervalh(.width = c(.1, .25, .5, .75, 1), show.legend = F) +
rcartocolor::scale_color_carto_d(palette = "Teal") +
coord_cartesian(ylim = c(0.9, 1.1)) +
geom_text(data = legend_text_g, aes(xt, yt, label = text),
family = "Bitter", color = "grey65", size = 3) +
theme_void()
title_g <- ggplot(data.frame(x = 1:2, y = 1:10)) +
labs(x = NULL, y = NULL,
title = "Maximale Tagestemperaturen in Berlin",
subtitle = "Verteilung der maximalen Tagestemperaturen in Berlin-Dahlem im Jahresverlauf von 1. Januar 2000 bis 31. Dezember 2018") +
theme(line = element_blank(),
plot.title = element_text(size = 26, hjust = 0, face = "bold", family = "Bitter"),
plot.subtitle = element_text(size = 13, hjust = 0, color = "grey65"),
panel.background = element_rect(fill = "transparent", color = "transparent"),
plot.background = element_rect(fill = "transparent", color = "transparent"),
panel.border = element_rect(color = "transparent"),
axis.text = element_blank())
caption_g <- ggplot(data.frame(x = 1:2, y = 1:10)) +
labs(x = NULL, y = NULL,
caption = "Visualisierung: Cédric Scherer | Daten: DWD (Deutscher Wetterdienst)") +
theme(line = element_blank(),
plot.caption = element_text(size = 10, color = "grey65"),
panel.background = element_rect(fill = "transparent", color = "transparent"),
plot.background = element_rect(fill = "transparent", color = "transparent"),
panel.border = element_rect(color = "transparent"),
axis.text = element_blank())
plot_ins_g <- ggdraw(plot_g) +
draw_plot(legend_g, .275, .01, .525, .3)
title_g + plot_ins_g + caption_g + plot_layout(widths = c(0, 1, 0))
ggsave(here::here("plots", "2019_09", "SWD_2019_09_Uncertainty_ger.pdf"),
width = 13, height = 8, device = cairo_pdf)
```
***
```{r}
sessionInfo()
```