How to get the highest, lowest, and average values for each year in one table

This is the dataset that I'm using:

full_trains <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-02-26/full_trains.csv")

In this dataset, there is data from 2015 to 2018. I am trying to get a shorter table that only has the highest, lowest, and average of average journey time for each year.

Specific variables from dataset would be: year, journey_time_avg

I know how to use the min, max, mean functions separately but I don't know how to bring it all together in one table.

One way you can achieve this using the dplyr package. The workflow is:

1. Group your data by "year"
2. Use summarise() to return min, max, and mean values for each group

summary_data <- full_trains %>%
  group_by(year) %>%
  summarise(min_ave_time = min(journey_time_avg),
            max_ave_time = max(journey_time_avg),
            mean_ave_time = mean(journey_time_avg)) %>%
  ungroup()
summary_data
# A tibble: 4 × 4
   year min_ave_time max_ave_time mean_ave_time
  <dbl>        <dbl>        <dbl>         <dbl>
1  2015         46.8         341.          163.
2  2016         46.5         344.          163.
3  2017         46.2         454.          165.
4  2018         46.0         481           170.

Please note the values in result shown above are truncated, the actual "summary_data" object has the full and correct values.