Count mean subgroup occurrence within subgroup - r

Question

I have the following dataframe:
date hour_of_day distance weather_of_the_day
2017-06-13 6 10.32 1
2017-06-13 8 2.32 1
2017-06-14 10 4.21 2
2017-06-15 7 4.56 4
2017-06-15 7 8.92 4
2017-06-16 22 2.11 3
structure(list(startdat = structure(c(17272, 17272, 17272, 17272,17272, 17272, 17272, 17272, 17272, 17272, 17272, 17272, 17272,17272, 17272, 17272, 17273, 17273, 17273, 17273), class = "Date"), hOfDay = c(22L, 16L, 12L, 13L, 18L, 19L, 19L, 16L, 22L, 10L,
10L, 16L, 11L, 20L, 9L, 15L, 18L, 12L, 16L, 18L), tripDKM = c(0.2,
6.4, 3.4, 0.8, 2.4, 2.2, 2.2, 7.3, 2.6, 3.8, 7.5, 5.8, 3.7,
2.1, 2.6, 5.2, 2.9, 1.7, 3.2, 3.1), totDMIN = c(1.85, 27.4,
8.2, 4.21666666666667, 15.65, 8.91666666666667, 11.5666666666667,
29.5166666666667, 7.01666666666667, 12.2166666666667, 15.8833333333333,
19.5666666666667, 21.7166666666667, 8.66666666666667, 11.2333333333333,
13.4, 7.58333333333333, 10.6166666666667, 6.76666666666667,
17.7), weather_day = structure(c(3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L), .Label = c("1",
"2", "3", "4"), class = "factor")), row.names = c(1L, 2L,3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 15L, 16L, 17L, 19L, 20L, 21L, 22L), class = "data.frame")
My final goal is to have a line ggplot, where the x-axis shows the hour_of_day, the y-axis stands for the mean number of occurrences. Eventually the lines should represent the 4 weather conditions. So one line ought to represent weather_of_the_day=1, and the y axis shows how often, on average weather_day=1 has an occurrence with hour_of_day=6 (as an example) and so on for 7, 8, etc.. What I want, are not only the number of occurrences, but the average number of occurrences.
I've been struggling for 2 days with this. I've tried different approaches, with for loops and subgrouping. But non of them brought a usable solution. Thank you very much for your help in advance!

Answer 1

Your posted data set is a little small but this is what I would suggest. It only makes sense with more data points though. df is the set you posted.
library(dplyr)
library(ggplot2)
df_plot <- df %>%
mutate(weather_of_the_day = factor(weather_of_the_day)) %>%
group_by(hour_of_day, weather_of_the_day) %>%
summarize(occurances = n())
ggplot(data = df_plot,
aes(x = hour_of_day,
y = occurances,
group = weather_of_the_day,
color = weather_of_the_day)) +
geom_line()+
geom_point()

Answer 2

I'm not completely sure if this mathes your desired output, but I gave it a try:
#Importing packages
library(dplyr)
library(ggplot2)
d <- structure(list(startdat = structure(c(17272, 17272, 17272, 17272,17272, 17272, 17272, 17272, 17272, 17272, 17272, 17272, 17272,17272, 17272, 17272, 17273, 17273, 17273, 17273),
class = "Date"),
hOfDay = c(22L, 16L, 12L, 13L, 18L, 19L, 19L, 16L, 22L, 10L, 10L, 16L, 11L, 20L, 9L, 15L, 18L, 12L, 16L, 18L),
tripDKM = c(0.2, 6.4, 3.4, 0.8, 2.4, 2.2, 2.2, 7.3, 2.6, 3.8, 7.5, 5.8, 3.7, 2.1, 2.6, 5.2, 2.9, 1.7, 3.2, 3.1),
totDMIN = c(1.85, 27.4, 8.2, 4.21666666666667, 15.65, 8.91666666666667, 11.5666666666667, 29.5166666666667, 7.01666666666667, 12.2166666666667, 15.8833333333333, 19.5666666666667, 21.7166666666667, 8.66666666666667, 11.2333333333333, 13.4, 7.58333333333333, 10.6166666666667, 6.76666666666667, 17.7),
weather_day = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L),
.Label = c("1", "2", "3", "4"),
class = "factor")),
row.names = c(1L, 2L,3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 15L, 16L, 17L, 19L, 20L, 21L, 22L),
class = "data.frame")
#Count how often every weather_day occurs during every hOfDay
plot_data <- d %>%
group_by(hOfDay, weather_day) %>%
summarize(n_occurences = n())
#Create plot
ggplot(plot_data, aes(x = hOfDay, y = n_occurences)) +
geom_line(aes(col = weather_day))