The histogram values can be saved as a data frame in R. Taking the example “list” of data “Example”, you could:
list_histo <- hist(list, breaks=length(list), freq=TRUE)
just typing
list_histo
back in R a new “meta” data frame will be shown containing histogram information (the data shown here are arbitrary and for illustration):
$breaks [1] 0.40 0.42 0.44 0.46 0.48 0.50 0.52 0.54 0.56 0.58 0.60 0.62 0.64 0.66 0.68 [16] 0.70 0.72 0.74 0.76 $counts [1] 1 15 112 878 4734 17995 51094 110146 178855 216454 [11] 194536 130591 64218 23017 6117 1070 144 23 $intensities [1] 0.00005 0.00075 0.00560 0.04390 0.23670 0.89975 2.55470 5.50730 [9] 8.94275 10.82270 9.72680 6.52955 3.21090 1.15085 0.30585 0.05350 [17] 0.00720 0.00115 $density [1] 0.00005 0.00075 0.00560 0.04390 0.23670 0.89975 2.55470 5.50730 [9] 8.94275 10.82270 9.72680 6.52955 3.21090 1.15085 0.30585 0.05350 [17] 0.00720 0.00115 $mids [1] 0.41 0.43 0.45 0.47 0.49 0.51 0.53 0.55 0.57 0.59 0.61 0.63 0.65 0.67 0.69 [16] 0.71 0.73 0.75 $xname [1] "list_histo" $equidist [1] TRUE attr(,"class") [1] "histogram"
calling the highest value is now simple - just using
max(list_histo$counts)
will return the maximum value.
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