Here is a minimal example:
import numpy as np
np.set_printoptions(linewidth=1000, precision=3)
# First attempt fails to limit the printed precision of x
x = np.array([None])
x[0] = 1/3
print(x)
# Second attempt succeeds
x = [None]
x[0] = 1/3
x = np.array(x)
print(x)
Running this script yields
[0.3333333333333333]
[0.333]
Why does the “First attempt” above fail to limit the printed precision of x while the second attempt succeeds?
When running:
x = np.array([None])
x[0] = 1/3
print(x)
x is an object dataframe (that contains python floats), not an array with a float dtype like your second attempt:
array([0.3333333333333333], dtype=object)
This ignores the print options.
You can reproduce this simply with:
print(np.array([1/3], dtype=object), np.array([1/3]))
Output: [0.3333333333333333] [0.333]
As a workaround, convert your array to float:
print(x.astype(np.float64))
# [0.333]