Это не самое элегантное решение, но:
MIN_VALUE = 0
MAX_VALUE = 65535
NO_BINS = 2
# Create random dataset from [0,65535] interval
numbers = np.random.randint(0,65535+1,100)
# Create bin edges
bins = np.arange(0,65535, (MAX_VALUE-MIN_VALUE)/NO_BINS)
# Get bin values
_, bin_val = np.histogram(numbers, NO_BINS-1, range=(MIN_VALUE, MAX_VALUE))
# Change the values to the bin value
for iter_bin in range(1,NO_BINS+1):
numbers[np.where(digits == iter_bin)] = bin_val[iter_bin-1]
UPDATE
Выполняет ту же работу:
import pandas as pd
import numpy as np
# or bin_labels = [i*((MAX_VALUE - MIN_VALUE) / (NO_BINS-1)) for i in range(NO_BINS)]
_, bin_labels = np.histogram(numbers, NO_BINS-1, range=(MIN_VALUE, MAX_VALUE))
pd.cut(numbers, NO_BINS, right=False, labels=bin_labels)