Q:

Is -0 an issue with min(), or something else?

Trying a task in python I encountered the following problem, as -0.0000 is interpreted for some reason as the lowest value: 
The following codes in Python and R show the issue and the difference:
# Python code
a1 = ['-0.0069', '-0.0201', '0.0194', '-0.0000']
a2 = ['-0.0069', '-0.0201', '0.0194']
print("Minimum value from ['-0.0069', '-0.0201', '0.0194', '-0.0000'] is " + min(a1))
print("Minimum value from ['-0.0069', '-0.0201', '0.0194'] is " + min(a2))

# R code
> a2 <- c(-0.0069, -0.0201, 0.0194)
> a1 <- c(-0.0069, -0.0201, 0.0194, -0.0000)
> min(a1)
[1] -0.0201
> min(a2)
[1] -0.0201

Python has the following results:
Minimum value from ['-0.0069', '-0.0201', '0.0194', '-0.0000'] is -0.0000
Minimum value from ['-0.0069', '-0.0201', '0.0194'] is -0.0069

whereas R, as shown in the code results below the lines, outputs correctly.
How is this explained? I believe -0 is not defined in general, but what does it mean for Python? Why is it not excluded or defined as invalid in the min() function? Does this apply to other similar functions as a general rule maybe?
R does it differently for some reason.
Thanks! 

A:

Those are strings. Remove the quotes around the numbers. 
a1 = [-0.0069, -0.0201, 0.0194, -0.0000]
a2 = [-0.0069, -0.0201, 0.0194]

print(f"Minimum value from {a1} is {min(a1)}")  # -0.0201
print(f"Minimum value from {a2} is {min(a2)}")  # -0.0201

