أساسيات NumPy

import numpy as np
import time

prices = list(range(1_000_000))
arr = np.array(prices)

start = time.time()
with_vat_list = [p * 1.14 for p in prices]
list_time = time.time() - start

start = time.time()
with_vat_arr = arr * 1.14          # no loop! applies to every element
numpy_time = time.time() - start

print(f"list:  {list_time:.4f}s")
print(f"numpy: {numpy_time:.4f}s")
print(f"NumPy is ~{list_time / numpy_time:.0f}x faster")

import numpy as np

a = np.array([10, 20, 30])
print(a, a.dtype)                 # dtype = type of elements

print(np.zeros(4))                # [0. 0. 0. 0.]
print(np.ones((2, 3)))            # 2 rows, 3 columns of ones
print(np.arange(0, 10, 2))        # like range(), but an array
print(np.linspace(0, 1, 5))       # 5 evenly spaced numbers from 0 to 1

import numpy as np

temps_c = np.array([18, 24, 31, 36, 29])     # a week in Cairo
temps_f = temps_c * 9 / 5 + 32               # convert all at once
print(temps_f)

print("Mean:", temps_c.mean())
print("Max:", temps_c.max(), "on day", temps_c.argmax())  # argmax = index of max
print("Hot days:", temps_c > 30)              # comparison -> array of True/False

import numpy as np

rng = np.random.default_rng(seed=42)       # seed -> reproducible results

dice = rng.integers(1, 7, size=10)         # 10 dice rolls
heights = rng.normal(loc=170, scale=8, size=5)   # normal distribution
print(dice)
print(heights.round(1))