Graphing Random Numbers
Generating 1000 pseudo-random numbers with Python, and then graphing them on a plot using Matplotlib.
The distribution of one instance of 1000 randomly generated numbers:
# of 0's: 9
# of 1's: 9
# of 2's: 14
# of 3's: 11
# of 4's: 8
# of 5's: 12
# of 6's: 13
# of 7's: 8
# of 8's: 11
# of 9's: 6
# of 10's: 7
# of 11's: 10
# of 12's: 8
# of 13's: 8
# of 14's: 13
# of 15's: 8
# of 16's: 7
# of 17's: 13
# of 18's: 10
# of 19's: 8
# of 20's: 11
# of 21's: 8
# of 22's: 12
# of 23's: 13
# of 24's: 9
# of 25's: 9
# of 26's: 8
# of 27's: 12
# of 28's: 8
# of 29's: 8
# of 30's: 11
# of 31's: 6
# of 32's: 16
# of 33's: 10
# of 34's: 8
# of 35's: 6
# of 36's: 9
# of 37's: 13
# of 38's: 9
# of 39's: 7
# of 40's: 10
# of 41's: 10
# of 42's: 12
# of 43's: 10
# of 44's: 13
# of 45's: 16
# of 46's: 13
# of 47's: 12
# of 48's: 10
# of 49's: 7
# of 50's: 8
# of 51's: 6
# of 52's: 9
# of 53's: 10
# of 54's: 12
# of 55's: 12
# of 56's: 11
# of 57's: 16
# of 58's: 12
# of 59's: 7
# of 60's: 14
# of 61's: 13
# of 62's: 7
# of 63's: 11
# of 64's: 10
# of 65's: 15
# of 66's: 14
# of 67's: 10
# of 68's: 9
# of 69's: 6
# of 70's: 11
# of 71's: 9
# of 72's: 8
# of 73's: 8
# of 74's: 11
# of 75's: 8
# of 76's: 12
# of 77's: 10
# of 78's: 10
# of 79's: 14
# of 80's: 7
# of 81's: 10
# of 82's: 7
# of 83's: 4
# of 84's: 6
# of 85's: 10
# of 86's: 6
# of 87's: 9
# of 88's: 17
# of 89's: 8
# of 90's: 13
# of 91's: 12
# of 92's: 10
# of 93's: 14
# of 94's: 7
# of 95's: 4
# of 96's: 10
# of 97's: 6
# of 98's: 8
# of 99's: 12
# of 100's: 8
And the corresponding graph:
The graph increasingly looks like a uniform distribution when a larger amount of random numbers are generated. The graph for 1000000 randomly generated numbers:
