Weights (rounded to the nearest kg) of a group of 13-year-old males

64, 66, 73, 86, 70, 75, 68, 86, 88, 63, 73, 70, 69, 66, 77, 80, 80, 77, 82, 61, 77, 71, 59, 84, 86, 70, 77, 70, 97, 68, 66, 70, 70, 68, 70, 68, 81, 73, 61, 73, 59, 70, 68, 67, 70, 68, 64, 82, 86, 66, 68, 74, 64, 64, 62, 56, 70

A = 55 B = 100   intervalli = 9   di ampiezza 5  -  pesi maschi 13-enni
n = 57   min = 56 max = 97   mediana = 70   1^|3^ quarto = 66|77   media = 71.7719298245614
percentuali:
| 5.26 | 14.04 | 22.81 | 28.07 | 8.77 | 10.53 | 8.77 | 0 | 1.75 |
corrispondenti alle frequenze:
3+8+13+16+5+6+5+0+1

The lengths of many broad beans (ie bean seeds) collected by a 12-year-old class

broad bean seed - lengths (cm):
1.35, 1.65, 1.80, 1.40, 1.65, 1.80, 1.40, 1.65, 1.85, 1.40, 1.65, 1.85, 1.50, 1.65, 1.90, 1.50, 1.65, 1.90, 1.50, 1.65, 1.90, 1.50, 1.70, 1.90, 1.50, 1.70, 1.90, 1.50, 1.70, 2.25, 1.55, 1.70, 1.55, 1.70, 1.55, 1.70, 1.60, 1.70, 1.60, 1.75, 1.60, 1.75, 1.60, 1.80, 1.60, 1.80, 1.60, 1.80, 1.60, 1.80, 1.00, 1.55, 1.70, 1.75, 1.30, 1.55, 1.70, 1.75, 1.40, 1.60, 1.70, 1.75, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.45, 1.60, 1.70, 1.80, 1.50, 1.60, 1.70, 1.80, 1.50, 1.60, 1.70, 1.85, 1.50, 1.60, 1.70, 1.85, 1.50, 1.60, 1.75, 1.90, 1.50, 1.60, 1.75, 1.90, 1.50, 1.65, 1.75, 1.90, 1.55, 1.65, 1.75, 1.95, 1.55, 1.65, 1.75, 2.00, 1.55, 1.65, 1.75, 2.30, 1.35, 1.65, 1.80, 1.40, 1.65, 1.80, 1.40, 1.65, 1.85, 1.40, 1.65, 1.85, 1.50, 1.65, 1.90, 1.50, 1.65, 1.90, 1.50, 1.65, 1.90, 1.50, 1.70, 1.90, 1.50, 1.70, 1.90, 1.50, 1.70, 2.25, 1.55, 1.70, 1.55, 1.70, 1.55, 1.70, 1.60, 1.70, 1.60, 1.75, 1.60, 1.75, 1.60, 1.80, 1.60, 1.80, 1.60, 1.80, 1.60, 1.80, 1.00, 1.55, 1.70, 1.75, 1.30, 1.55, 1.70, 1.75, 1.40, 1.60, 1.70, 1.75, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.40, 1.60, 1.70, 1.80, 1.45, 1.60, 1.70, 1.80, 1.50, 1.60, 1.70, 1.80, 1.50, 1.60, 1.70, 1.85, 1.50, 1.60, 1.70, 1.85, 1.50, 1.60, 1.75, 1.90, 1.50, 1.60, 1.75, 1.90, 1.50, 1.65, 1.75, 1.90, 1.55, 1.65, 1.75, 1.95, 1.55, 1.65, 1.75, 2.00, 1.55, 1.65, 1.75, 2.30

alternative:
1*2, 1.3*2, 1.35*2, 1.4*22, 1.45*2, 1.5*24, 1.55*16, 1.6*42, 1.65*22, 1.7*42, 1.75*22, 1.8*30, 1.85*8, 1.9*16, 1.95*2, 2*2, 2.25*2, 2.3*2

alternative (by using ord.htm):
1, 1, 1.3, 1.3, 1.35, 1.35, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.45, 1.45, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.55, 1.55, 1.55, 1.55, 1.55, 1.55, 1.55, 1.55, 1.55, 1.55, 1.55, 1.55, 1.55, 1.55, 1.55, 1.55, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.65, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.8, 1.85, 1.85, 1.85, 1.85, 1.85, 1.85, 1.85, 1.85, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.9, 1.95, 1.95, 2, 2, 2.25, 2.25, 2.3, 2.3

 I can get tighter rectangles with hist2 or hist3:

If you want other elaborations use this calculator.

Their volumes (cm³):
1.04, 1.27, 1.39, 1.08, 1.27, 1.39, 1.08, 1.27, 1.42, 1.08, 1.27, 1.42, 1.16, 1.27, 1.46, 1.16, 1.27, 1.46, 1.16, 1.27, 1.46, 1.16, 1.31, 1.46, 1.16, 1.31, 1.46, 1.16, 1.31, 1.73, 1.19, 1.31, 1.19, 1.31, 1.19, 1.31, 1.23, 1.31, 1.23, 1.35, 1.23, 1.35, 1.23, 1.39, 1.23, 1.39, 1.23, 1.39, 1.23, 1.39, 0.77, 1.19, 1.31, 1.35, 1.00, 1.19, 1.31, 1.35, 1.08, 1.23, 1.31, 1.35, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.12, 1.23, 1.31, 1.39, 1.16, 1.23, 1.31, 1.39, 1.16, 1.23, 1.31, 1.42, 1.16, 1.23, 1.31, 1.42, 1.16, 1.23, 1.35, 1.46, 1.16, 1.23, 1.35, 1.46, 1.16, 1.27, 1.35, 1.46, 1.19, 1.27, 1.35, 1.50, 1.19, 1.27, 1.35, 1.54, 1.19, 1.27, 1.35, 1.77, 1.04, 1.27, 1.39, 1.08, 1.27, 1.39, 1.08, 1.27, 1.42, 1.08, 1.27, 1.42, 1.16, 1.27, 1.46, 1.16, 1.27, 1.46, 1.16, 1.27, 1.46, 1.16, 1.31, 1.46, 1.16, 1.31, 1.46, 1.16, 1.31, 1.73, 1.19, 1.31, 1.19, 1.31, 1.19, 1.31, 1.23, 1.31, 1.23, 1.35, 1.23, 1.35, 1.23, 1.39, 1.23, 1.39, 1.23, 1.39, 1.23, 1.39, 0.77, 1.19, 1.31, 1.35, 1.00, 1.19, 1.31, 1.35, 1.08, 1.23, 1.31, 1.35, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.08, 1.23, 1.31, 1.39, 1.12, 1.23, 1.31, 1.39, 1.16, 1.23, 1.31, 1.39, 1.16, 1.23, 1.31, 1.42, 1.16, 1.23, 1.31, 1.42, 1.16, 1.23, 1.35, 1.46, 1.16, 1.23, 1.35, 1.46, 1.16, 1.27, 1.35, 1.46, 1.19, 1.27, 1.35, 1.50, 1.19, 1.27, 1.35, 1.54, 1.19, 1.27, 1.35, 1.77

 Classified data  vedi/see  →

Human body weight (peso corporeo); 4170 Italian males in their twenties, in the year 1990.   (here)

The data are truncated, so 0.5 must be added to the average; then it can be rounded up to tenths: 70.476... → 71.0.

 For histograms, you can use a more complex script: see

 Zombies A 1 long wall; a W wide hole in the wall; every second a zombie arrives in a completely random position of the wall.  Let W be 1/10; let's simulate 1 hour.  The distribution (in 5 sec intervals) of the waiting times between a pass through the hole of a zombie and the next pass. [the histogram tends to have the graph of  x → W·exp(−W·x)  as profile]

17, 10, 8, 36, 7, 21, 1, 6, 2, 8, 3, 5, 7, 3, 7, 2, 2, 6, 2, 15, 12, 10, 2, 18, 1, 19, 14, 22, 6, 2, 2, 7, 4, 8, 12, 6, 12, 2, 17, 4, 1, 3, 5, 15, 11, 1, 4, 16, 6, 11, 6, 20, 2, 14, 1, 15, 38, 1, 7, 23, 10, 4, 25, 1, 1, 4, 11, 7, 1, 4, 2, 6, 7, 15, 4, 20, 17, 3, 15, 8, 16, 2, 15, 3, 3, 3, 30, 13, 23, 19, 38, 18, 4, 17, 1, 1, 1, 21, 5, 45, 11, 3, 5, 2, 19, 9, 5, 16, 5, 1, 1, 35, 12, 6, 22, 29, 16, 13, 8, 9, 12, 4, 4, 1, 10, 1, 2, 10, 22, 2, 2, 16, 20, 12, 5, 5, 2, 12, 1, 9, 1, 26, 37, 1, 6, 2, 8, 7, 6, 1, 5, 8, 6, 6, 19, 4, 23, 12, 33, 4, 3, 8, 4, 2, 28, 20, 10, 15, 15, 4, 5, 2, 3, 1, 1, 18, 4, 2, 15, 10, 6, 1, 9, 5, 32, 1, 31, 20, 10, 5, 23, 1, 9, 11, 3, 20, 14, 5, 5, 5, 1, 18, 3, 23, 7, 10, 10, 14, 3, 8, 9, 3, 8, 1, 21, 3, 5, 2, 31, 1, 31, 1, 3, 37, 5, 7, 4, 21, 7, 7, 2, 13, 4, 4, 1, 1, 8, 25, 18, 4, 5, 6, 14, 17, 2, 11, 6, 5, 6, 8, 1, 9, 1, 6, 9, 4, 1, 5, 1, 14, 6, 12, 3, 3, 7, 6, 3, 10, 31, 3, 3, 4, 8, 4, 12, 5, 1, 3, 1, 18, 25, 6, 24, 14, 2, 1, 29, 23, 31, 15, 24, 2, 2, 5, 4, 5, 15, 3, 3, 14, 11, 5, 2, 9, 45, 3, 4, 4, 21, 9, 16, 4, 12, 17, 12, 4, 14, 3, 4, 20, 5, 8, 8, 6, 21, 19, 4, 5, 5, 5, 28, 18, 9, 10, 3, 12, 2, 2, 4, 15, 2, 7, 3, 4, 8, 6, 10, 14, 7, 14, 13, 9, 4, 5, 12, 1, 3, 4, 14, 8, 1, 6, 3, 16, 1, 6, 9, 2, 3, 6, 21, 15, 2, 20, 18, 9, 7, 3, 5, 7, 18

The study of the cast of a die made of thin cardboard:

5,5,4,3,3,1,6,2,5,6,2,5,3,6,5,6,3,2,1,6,1,6,6,3,5,2,1,5,2,5,5,3,6,6,4,6,6,5,6,2, 1,6,6,3,2,2,5,6,3,2,6,6,6,4,2,3,6,6,6,2,6,4,5,4,6,2,3,5,6,6,2,2,1,5,5,3,5,3,5,6, 2,1,4,3,6,6,6,4,3,4,6,6,4,5,4,4,2,2,6,4,4,6,2,5,3,6,6,3,3,2,2,6,1,4,6,5,3,3,4,1, 6,4,6,6,2,5,5,1,5,2,6,5,2,2,4,1,2,2,6,1,6,5,5,6,1,3,3,4,5,5,5,6,4,4,6,3,6,3,6,6, 4,2,6,6,6,1,4,5,6,5,6,5,5,5,6,6,2,1,6,3,6,6,5,3,5,2,2,4,6,6,5,2,5,5,6,6,5,2,6,1

In Italy in 1951, in the age intervals [0,5),[5,10),[10,20),[20,30),[30,40),[40,50),[50,60),[60,75),[75,100) are dead 729,35,77,132,134,285,457,1401,1569 thousand people.
 With a more complex script  -  see  -  I get the histogram:

How can I get similar histograms with this script? I can divide some classes so as to obtain all classes of equal size:

A = 0   B = 100   intervals = 20   their width = 5
n = 48190
2.5*7290, 7.5*350, 12.5*385, 17.5*385, 22.5*660, 27.5*660, 32.5*670, 37.5*670, 42.5*1425, 47.5*1425, 52.5*2285, 57.5*2285, 62.5*4670, 67.5*4670, 72.5*4670, 77.5*3138, 82.5*3138, 87.5*3138, 92.5*3138, 97.5*3138

 I can get tighter rectangles with hist2: