Unfortunately this doesn’t help either - at lest not in gpt 3.5 (can’t test in 4.0 right now).
import numpy as np
Create an example data set
data = np.array([50.6, 51.0, 51.1, 52.4, 53.1, 53.1, 53.3, 54.1, 54.6, 54.6,
55.3, 55.6, 55.8, 56.6, 57.4, 58.0, 58.2, 58.2, 58.6, 58.7,
59.6, 59.8, 60.3, 60.8, 60.9, 60.9, 61.1, 61.2, 61.3, 61.6,
61.6, 62.1, 62.2, 62.2, 63.0, 63.4, 63.6, 63.8, 63.9, 64.4,
64.6, 64.8, 65.0, 65.1, 65.3, 66.0, 66.6, 66.8, 66.8, 66.9,
67.0, 67.1, 67.8, 67.8, 67.9, 68.1, 68.3, 68.6, 68.7, 69.0,
69.4, 69.5, 69.8, 69.9, 70.4, 70.5, 70.6, 70.6, 70.9, 71.0,
71.3, 72.6, 72.9, 73.3, 73.7, 74.3, 75.2, 75.2, 75.3, 75.3,
75.9, 76.1, 78.0, 78.2, 79.1, 79.2, 81.2, 81.2, 81.6, 81.6,
81.7, 86.4, 93.4, 94.8, 102.0, 102.1])
Calculate the 95th percentile
p95 = np.percentile(data, 95)
Print the result
print("95th percentile: ", p95)
with the result of 102.1 - which is obviously wrong since it is th 100th value.
PS: And yeah… I really love how chatgpt replaced on many occasions long searches using google, bing, ddg and so on 