Plot a continuous series with ggplot2

Problem

When we try to plot a continuous series, in our example WS (Winter Solstice), ggplot2 connects the last winter data point in March to the first winter data point in December.

• Data

library(ggplot2)

getSeason <- function(DATES) {
#found here https://stackoverflow.com/questions/9500114/find-which-season-a-particular-date-belongs-to
WS <- as.Date("2012-12-15", format = "%Y-%m-%d") # Winter Solstice
SE <- as.Date("2012-3-15",  format = "%Y-%m-%d") # Spring Equinox
SS <- as.Date("2012-6-15",  format = "%Y-%m-%d") # Summer Solstice
FE <- as.Date("2012-9-15",  format = "%Y-%m-%d") # Fall Equinox

# Convert dates from any year to 2012 dates
d <- as.Date(strftime(DATES, format="2012-%m-%d"))

ifelse (d >= WS | d < SE, "Winter",
  ifelse (d >= SE & d < SS, "Spring",
    ifelse (d >= SS & d < FE, "Summer", "Fall")))
}

zz <- sample(1:10000,365)/1000
dag <- seq(as.Date("2014-01-01"), as.Date("2014-12-31"), by = "day")
seas <-  getSeason(dag)
test <- data.frame(zz,dag,seas)

ggplot(data=test, aes(x=dag,ymax=zz,ymin=0,fill=seas))+
geom_ribbon()

Solution

We can solve it by subsetting our data in two, above and below WS, and plotting two layers with geom_ribbon. Thus you convert the continuous WS series into two discrete sections.

library(dplyr)
ggplot() +
  geom_ribbon(data = filter(test, dag >= "2014-12-15") ,
              aes(x = dag, ymax = zz, ymin = 0, fill = seas)) +
  geom_ribbon(data = filter(test, dag < "2014-12-15") ,
              aes(x = dag, ymax = zz, ymin = 0, fill = seas))

Results

References

• Spanish version
• stackoverflow
• English posts

Calcular y representar la duración del día con R

Problema

Queremos calcular y representar la duración del día con R en función de unas coordinadas geográficas.

Solución

1. Calculamos la salida y puesta de sol

Primero calculamos la salida y la puesta de sol con la función getSunlightTimes del paquete suncalc. Indicamos el intervalo deseado, las coordinadas (latitud y longitud), y el huso horario (tz, time zone) correspondiente.

library(suncalc) 
library(tidyverse)
library(scales)
df <-
  getSunlightTimes(
    date = seq.Date(as.Date("2017-12-01"), as.Date("2018-12-31"), by = 1),
    keep = c("sunrise", "sunriseEnd", "sunset", "sunsetStart"),
    lat = 39.8628,
    lon = 4.0273,
    tz = "CET"
  )

2. Gráfico de la salida y puesta de sol

Necesitamos manipular los datos originales para calcular la diferencia entre el inicio del día, y la salida y puesta de sol. Después representamos las dos nuevas variables usando geom_ribbon de ggplot2. Luego personalizamos los ejes y el título.

# Amanecer/ocaso
df %>%
  mutate(
    date = as.POSIXct(date) - 12 * 60 * 60 ,
    sunrise = sunrise - date,
    sunset =  sunset - date,
  ) %>%
  ggplot() +
  geom_ribbon(aes(x = date, ymin = sunrise, ymax = sunset),
              fill = "#FDE725FF",
              alpha = .8) + # "#ffeda0"
  scale_x_datetime(
    breaks = seq(as.POSIXct(min(df$date)), as.POSIXct(max(df$date)), "month"),
    expand = c(0, 0),
    labels = date_format("%b %y"),
    minor_breaks = NULL
  ) +
  scale_y_continuous(
    limits = c(0, 24),
    breaks = seq(0, 24, 2),
    expand = c(0, 0),
    minor_breaks = NULL
  ) +
  labs(
    x = "Date",
    y = "Hours",
    title = sprintf(
      "Sunrise and Sunset for %s\n%s ",
      "Toledo (Spain)",
      paste0(as.Date(range(df$date)), sep = " ", collapse = "to ")
    )
  ) +
  theme(
    panel.background = element_rect(fill = "#180F3EFF"),
    panel.grid = element_line(colour = "grey", linetype = "dashed")
  )

3. Duración del día

Muy similar al gráfico anterior. Ahora solamente necesitamos calcular la duración del día day_length y representar los resultados con geom_area and geom_line.

df %>%
  mutate(
    date = as.POSIXct(date),
    day_length = as.numeric(sunset - sunrise)
  ) %>%
  ggplot(aes(x = date, y = day_length)) +
  geom_area(fill = "#FDE725FF", alpha = .4) +
  geom_line(color = "#525252") +
  scale_x_datetime(
    expand = c(0, 0),
    labels = date_format("%b '%y"),
    breaks =  seq(as.POSIXct(min(df$date)), as.POSIXct(max(df$date)), "month"),
    minor_breaks = NULL
  ) +
  scale_y_continuous(
    limits = c(0, 24),
    breaks = seq(0, 24, 2),
    expand = c(0, 0),
    minor_breaks = NULL
  ) +
  labs(x = "Date", y = "Hours", title = "Toledo (Spain) - Daytime duration") +
  theme_bw()

Entradas relacionadas

• Versión en inglés: Calculate and plot sunrise and sunset times with R
• English posts

Referencias

• suncalc
• ggplot2 formats

Calculate and plot sunrise and sunset times with R

Problem

We would like to calculate and plot the sunrise and sunset times based on any location's latitude and longitude coordinates with R.

Solution

1. Compute sunrise and sunset times

First we calculate the sunrise and sunset times using the function getSunlightTimes from the package suncalc. We pass the desired date interval, the appropiate latitude and longitude coordinates, and time zone (tz).

library(suncalc) 
library(tidyverse)
library(scales)
df <-
  getSunlightTimes(
    date = seq.Date(as.Date("2017-12-01"), as.Date("2018-12-31"), by = 1),
    keep = c("sunrise", "sunriseEnd", "sunset", "sunsetStart"),
    lat = 39.8628,
    lon = 4.0273,
    tz = "CET"
  )

2. Sunrise and sunset times plot

We need to manipulate the original data frame to calculate the difference between midnight start of day, and the sunrise and sunset times. Then we plot those two new variables using geom_ribbon from ggplot2. We further customize the axes, and title.

# Sunrise/set
df %>%
  mutate(
    date = as.POSIXct(date) - 12 * 60 * 60 ,
    sunrise = sunrise - date,
    sunset =  sunset - date,
  ) %>%
  ggplot() +
  geom_ribbon(aes(x = date, ymin = sunrise, ymax = sunset),
              fill = "#FDE725FF",
              alpha = .8) + # "#ffeda0"
  scale_x_datetime(
    breaks = seq(as.POSIXct(min(df$date)), as.POSIXct(max(df$date)), "month"),
    expand = c(0, 0),
    labels = date_format("%b %y"),
    minor_breaks = NULL
  ) +
  scale_y_continuous(
    limits = c(0, 24),
    breaks = seq(0, 24, 2),
    expand = c(0, 0),
    minor_breaks = NULL
  ) +
  labs(
    x = "Date",
    y = "Hours",
    title = sprintf(
      "Sunrise and Sunset for %s\n%s ",
      "Toledo (Spain)",
      paste0(as.Date(range(df$date)), sep = " ", collapse = "to ")
    )
  ) +
  theme(
    panel.background = element_rect(fill = "#180F3EFF"),
    panel.grid = element_line(colour = "grey", linetype = "dashed")
  )

3. Daytime duration

Very similar to the preceding plot. This time we only need to calculate the day_length and plot the results using geom_area and geom_line.

df %>%
  mutate(
    date = as.POSIXct(date),
    day_length = as.numeric(sunset - sunrise)
  ) %>%
  ggplot(aes(x = date, y = day_length)) +
  geom_area(fill = "#FDE725FF", alpha = .4) +
  geom_line(color = "#525252") +
  scale_x_datetime(
    expand = c(0, 0),
    labels = date_format("%b '%y"),
    breaks =  seq(as.POSIXct(min(df$date)), as.POSIXct(max(df$date)), "month"),
    minor_breaks = NULL
  ) +
  scale_y_continuous(
    limits = c(0, 24),
    breaks = seq(0, 24, 2),
    expand = c(0, 0),
    minor_breaks = NULL
  ) +
  labs(x = "Date", y = "Hours", title = "Toledo (Spain) - Daytime duration") +
  theme_bw()

Related posts

• Spanish version: Cómo controlar la dispersión de puntos dentro de un diagrama de violín con ggplot2
• English posts

References

• suncalc
• ggplot2 formats

Representar serie continua con geom_ribbon de ggplot2

Problema

Cuando intentamos representar una serie continua, en nuestro ejemplo WS (Winter Solstice), ggplot2 une el último dato de WS (invierno) en marzo con el primero en diciembre, obteniendo el siguiente resultado indeseado.

• Datos

library(ggplot2)

getSeason <- function(DATES) {
#found here https://stackoverflow.com/questions/9500114/find-which-season-a-particular-date-belongs-to
WS <- as.Date("2012-12-15", format = "%Y-%m-%d") # Winter Solstice
SE <- as.Date("2012-3-15",  format = "%Y-%m-%d") # Spring Equinox
SS <- as.Date("2012-6-15",  format = "%Y-%m-%d") # Summer Solstice
FE <- as.Date("2012-9-15",  format = "%Y-%m-%d") # Fall Equinox

# Convert dates from any year to 2012 dates
d <- as.Date(strftime(DATES, format="2012-%m-%d"))

ifelse (d >= WS | d < SE, "Winter",
  ifelse (d >= SE & d < SS, "Spring",
    ifelse (d >= SS & d < FE, "Summer", "Fall")))
}

zz <- sample(1:10000,365)/1000
dag <- seq(as.Date("2014-01-01"), as.Date("2014-12-31"), by = "day")
seas <-  getSeason(dag)
test <- data.frame(zz,dag,seas)

ggplot(data=test, aes(x=dag,ymax=zz,ymin=0,fill=seas))+
geom_ribbon()

Solución

Dividimos los datos con dplyr en dos subconjuntos, igual o mayor que el 2014-12-15 y por debajo de dicha fecha. Así convertimos la serie WS en dos secciones discretas, evitando que una los dos extremos de WS.

library(dplyr)
ggplot() +
  geom_ribbon(data = filter(test, dag >= "2014-12-15") ,
              aes(x = dag, ymax = zz, ymin = 0, fill = seas)) +
  geom_ribbon(data = filter(test, dag < "2014-12-15") ,
              aes(x = dag, ymax = zz, ymin = 0, fill = seas))

Resultados

Referencias

• stackoverflow
• ggplot2 en Nube de datos