R Taking an average of a variable over intervals of another numeric variable

How would I go about calculating an average of column 2 for every x interval in column 1, when the number of rows for the intervals are not always equal?

It seems very simple but I'm not sure where to start.

df <- data.frame(dist = c(0.06,0.22,0.38,0.44,0.5,0.52,0.6,0.74,0.76,0.88,0.92,0.94,1,1.18,1.26,1.3,1.4,1.48,1.5), 
            value = c(12,54.6,46.6,59.7,65.4,66.4,67,76.5,77.3,94.5,95.5,95,93.7,106.5,112.3,112.4,112.6,114.3,114.2))

Let's say I want to know the block average of column 2 when column 1 goes from 0 - 0.5 then 0.5 - 1 and 1 - 1.5 and so on, but if 0 - 0.5 are 5 rows and 0.5 - 1 are 9 rows, what is the best way to do this without having to specify the row numbers?

I have tried searching but perhaps I'm not using the right key words.

You can use cut to group according to the value of dist:

tapply(df$value, cut(df$dist, seq(0, 1.5, .5)), FUN = mean)
# (0,0.5]  (0.5,1]  (1,1.5] 
# 47.6600  83.2375 112.0500 

Or, if you prefer dplyr:

df %>% 
  group_by(gp = cut(dist, seq(0, 1.5, .5))) %>% 
  summarise(mean = mean(value)) %>%
  ungroup()

#       gp     mean
#1 (0,0.5]  47.6600
#2 (0.5,1]  83.2375
#3 (1,1.5] 112.0500

Using aggregate in base R

 aggregate(value ~ grp, transform(df, grp = cut(dist, seq(0, 1.5, .5))), mean)

-output

  grp    value
1 (0,0.5]  47.6600
2 (0.5,1]  83.2375
3 (1,1.5] 112.0500