Bug ommits data interval - possible causes?

I have encountered a strange bug and wanted to ask if someone has any idea what might be the cause.

The bug:

When I correlate the facial width-to-height ratio (FWHR) of NHL players with their penalty minutes per games played (PIM/GP), a section of the FWHR distribution is blank (between 1.98-2 and 2-2.022; see Figure 1). The FWHR is an int/int ratio where each int has two digits. It is extremely unlikely this reflects a true signal and is therefore most likely a bug in the code I am using.

Context: I know my PIM/P data is correct (retrieved from NHL's website) but the FWHR was calculated using an algorithm. The problem most likely lies within this facial measuring algorithm. I have not been able to locate the bug and therefore turn to you for advice.

Question: While the code for the facial measuring algorithm is far too long to be presented here, I wanted to ask if someone might have any ideas on what might have caused it/ what I could check for?

The Nature of Ratio Distributions

Idea: It should be impossible for a ratio of two 2-digit integers to fill all 2-decimal values between two integers. Could such impossible values be especially pronounced around 2.0? For example, maybe 1.99 can not be represented?

Method: Loop through 2-digit ints and append the ratio to a list. Then check if the list lacks values around 2.0 (e.g., 1.99).

import numpy as np 
from matplotlib import pyplot as plt

def int_ratio_generator():
    ratio_list = []
    for i in range(1,100):
        for j in range(1,100):
            ratio = i/j
            ratio_list.append(ratio)
    return ratio_list
    
ratio_list = int_ratio_generator()
key = 1.99 in ratio_list
print('\nis 1.99 a possible ratio from 2-digit ints?', key)
fig, ax = plt.subplots()
X = ratio_list
Y = np.random.rand(len(ratio_list),1)
plt.scatter(X, Y, color='C0')
plt.xlim(1.8, 2.2)
plt.show()

Conclusion:

• Ratios from positive 2-digit integers do not fill all possible 2-decimal values between integers, and impossible values include 1.99.
• It follows that previously impossible values can be filled by including a larger range of ints, or by introducing decimal numbers within the same range.
• Furthermore, as shown by the simulation above, ratio distributions with 2-digit integers will have relatively large ranges of impossible values on either side of each integer.