Find out which observations are located in each "bar" of the histogram

[omario]

I am working with the R programming language.

Suppose I have the following data:

     a = rnorm(1000,10,1)
     b = rnorm(200,3,1)
     c = rnorm(200,13,1)
    
    d = c(a,b,c)
index <- 1:1400

my_data = data.frame(index,d)

I can make the following histograms of the same data by adjusting the "bin" length (via the "breaks" option):

hist(my_data, breaks = 10, main = "Histogram #1, Breaks = 10")
 hist(my_data, breaks = 100, main = "Histogram #2, Breaks = 100")
 hist(my_data, breaks = 5, main = "Histogram #3, Breaks = 5")

My Question: In each one of these histograms there are a different number of "bars" (i.e. bins). For example, in the first histogram there are 8 bars and in the third histogram there are 4 bars. For each one of these histograms, is there a way to find out which observations (from the original file "d") are located in each bar?

Right now, I am trying to manually do this, e.g. (for histogram #3)

histogram3_bar1 <- my_data[which(my_data$d < 5 & my_data$d > 0), ]
histogram3_bar2 <- my_data[which(my_data$d < 10 & my_data$d > 5), ]
histogram3_bar3 <- my_data[which(my_data$d < 15 & my_data$d > 10), ]
histogram3_bar4 <- my_data[which(my_data$d < 15 & my_data$d > 20), ]


head(histogram3_bar1)

    index        d
1001  1001 4.156393
1002  1002 3.358958
1003  1003 1.605904
1004  1004 3.603535
1006  1006 2.943456
1007  1007 1.586542

But is there a more "efficient" way to do this?

Thanks!

[FJCC]

You can capture the value returned by hist() and get the actual breaks and counts.

DF <- data.frame(index=1:1000,Value=rnorm(1000))
OUT <- hist(x = DF$Value, breaks = 20)
OUT$breaks
 [1] -3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5  0.0  0.5  1.0  1.5  2.0  2.5  3.0
[15]  3.5
OUT$counts
 [1]   1   6  17  44 102 155 192 183 155  81  39  19   5   1
DF$bin <- cut(DF$Value, breaks = OUT$breaks)
head(DF)
  index      Value       bin
1     1  0.3157736   (0,0.5]
2     2 -0.6178177 (-1,-0.5]
3     3  1.3705568   (1,1.5]
4     4 -0.5330028 (-1,-0.5]
5     5  0.8831283   (0.5,1]
6     6  1.2584396   (1,1.5]