CODEWITHSUNDEEP
rggplot2
Ronny Efronny
Ronny Efronny

Reputation: 1508

ggplot: plot time series with repeating time values

I have some data over hours that looks like this:

df <- data.frame('hour' = rep(0:23, 2),
                 'mean' = rnorm(48),
                 'sd' = rnorm(48))

I wish to plot geom_smooth() over the entire period:

df %>%
  ggplot(aes(y = mean, x = hour)) +
  geom_smooth(aes(y = sd))

However, by default my hour parameter is being factored such that every hour only appears once, as can be seen if one adds geom_point(), but I want all 48 (many more in reality) values to appear on my x axis. I realize there must be a single argument I'm missing but can't find.

Upvotes: 1

Views: 344

Answers (2)

Jay Achar
Jay Achar

Reputation: 1271

If I understand correctly, you want the line of geom_smooth to represent the mean column in your data frame, and the error ribbon to represent the sd column.

I believe this should give the output you're looking for:

library(dplyr)
library(ggplot2)

df %>%
ggplot(aes(y = mean, x = hour)) +
  geom_point(alpha = 0.5) +
  geom_smooth(method = "loess", se = FALSE) +
  stat_summary(aes(y = sd), fun.data = mean_se, geom="ribbon", alpha=0.25)

Upvotes: 0

KoenV
KoenV

Reputation: 4283

You need to define the hour you use as a date_time object, where the hours in the second halve are on the next day

You may use the following code:

library(dplyr)
library(ggplot2)

set.seed(9876) # for reproducibility
df <- data.frame('hour' = seq(c(ISOdate(2019,12,1)), by = "hour", length.out = 48),
                 'mean' = rnorm(48),
                 'sd' = rnorm(48))

df %>%
  ggplot(aes(y = mean, x = hour)) +
  geom_smooth(aes(y = sd))

Please, let me know whether this is what you want.

Upvotes: 1

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