The standard deviation of column A is 0.52.
The standard deviation of column B is 0.57.
The standard deviation of column C is 0.56.

Distribution counts of 3458 draws for each column:
Value        A        B        C
0    350 N (10.12%)    347 N (10.03%)    347 N (10.03%)
1    338 N (9.77%)    338 N (9.77%)    324 C (9.37%)
2    332 N (9.6%)    337 N (9.75%)    368 H (10.64%)
3    325 C (9.4%)    330 N (9.54%)    321 C (9.28%)
4    389 H (11.25%)    343 N (9.92%)    352 N (10.18%)
5    337 N (9.75%)    395 H (11.42%)    369 H (10.67%)
6    351 N (10.15%)    354 N (10.24%)    362 N (10.47%)
7    365 H (10.56%)    315 C (9.11%)    336 N (9.72%)
8    339 N (9.8%)    353 N (10.21%)    316 C (9.14%)
9    332 N (9.6%)    346 N (10.01%)    363 N (10.5%)

Final classifier count summary:
A: 2 H - 7 N - 1 C
B: 1 H - 8 N - 1 C
C: 2 H - 5 N - 3 C

Classifications for the last 7 draws:
6 N    6 N    2 H
2 N    1 N    6 N
9 N    4 N    0 N
5 N    2 N    3 C
3 C    3 N    6 N
2 N    8 N    5 H
1 N    5 H    7 N

The output now adds bot calculating standard deviation and displaying it for each column. I no longer set the Hot and Cold thresholds by passing arguments, but rather by direct calculation. The number of draws is interesting that in the case of a discrete uniform distribution, this is how you would obtain a confidence level of 95% with a 1% margin of error. I am not exactly sure why I chose to use the Z score to come up with that number, but this script WAS written for experimentation.

Look how low the standard deviation got as the number of draws increased... at under 100 draws, it was giving a much higher standard deviation. Here is the run for 90 draws...

The standard deviation of column A is 2.48.
The standard deviation of column B is 3.44.
The standard deviation of column C is 2.77.

Distribution counts of 90 draws for each column:
Value        A        B        C
0    9 N (10.0%)    9 N (10.0%)    6 C (6.67%)
1    12 H (13.33%)    10 N (11.11%)    10 N (11.11%)
2    9 N (10.0%)    9 N (10.0%)    9 N (10.0%)
3    13 H (14.44%)    5 C (5.56%)    11 N (12.22%)
4    11 N (12.22%)    12 N (13.33%)    7 N (7.78%)
5    6 C (6.67%)    14 H (15.56%)    12 H (13.33%)
6    9 N (10.0%)    6 N (6.67%)    10 N (11.11%)
7    7 N (7.78%)    7 N (7.78%)    4 C (4.44%)
8    7 N (7.78%)    5 C (5.56%)    9 N (10.0%)
9    7 N (7.78%)    13 H (14.44%)    12 H (13.33%)

Final classifier count summary:
A: 2 H - 7 N - 1 C
B: 2 H - 6 N - 2 C
C: 2 H - 6 N - 2 C

Classifications for the last 7 draws:
6 N    6 N    2 N
2 N    1 N    6 N
9 N    4 N    0 C
5 C    2 N    3 N
3 H    3 C    6 N
2 N    8 C    5 H
1 H    5 H    7 C

Still trying to find that sweet spot to get just the right amount of variance...