import numpy as np

import numpy as np vector = np.arange(5) vector

matrix = np.arange(9).reshape(3, 3) matrix

tensor = np.arange(12).reshape(3, 2, 2) tensor

my_first_vector = np.array([2, 5, 6, 23]) print(my_first_vector)

my_first_matrix = np.array([[2, 4,], [6, 8]]) print(my_first_matrix)

my_list = [0, 1, 2, 3, 4] print(np.array(my_list))

print(np.arange(start=2, stop=10, step=2))

print(np.arange(11, 1, -2))

print(np.linspace(start=11, stop=12, num=18))

print(np.linspace(0, 1, 11))

print(np.zeros(4))

print(np.zeros((2, 2)))

print(np.ones(6))

print(np.full(shape=(2, 2), fill_value=5))

print(np.full((2, 3, 4), 0.55))

base = np.linspace(2, 6, 4) print(np.full_like(base, np.pi))

import matplotlib.pyplot as plt uniform = np.random.uniform(0, 10, 10000) normal = np.random.normal(0, 3, 10000) plt.figure(figsize=(12,5)) plt.subplot(1, 2, 1) plt.hist(uniform, bins=50) plt.title('Distribución uniforme') plt.subplot(1, 2, 2) plt.hist(normal, bins=50) plt.title('Distribución normal') plt.show()

print(np.random.rand(2, 2))

rand = np.random.rand(10000) plt.hist(rand, bins=50) plt.show()

print(np.random.uniform(low=0, high=1, size=6))

uniform = np.random.uniform(low=0, high=1, size=10000) plt.hist(uniform, bins=50) plt.show()

print(np.random.randn(2, 2))

normal = np.random.randn(10000) plt.hist(normal, bins=50) plt.show()

print(np.random.normal(loc=0, scale=2, size=6))

normal2 = np.random.normal(0, 1, 10000) plt.hist(normal2, bins=50) plt.show()

print(np.random.randint(low=0, high=10, size=(3, 3)))

print(np.random.randint(1,100,10))

a = np.arange(1,10) B = np.reshape(a, [3,3]) print(B)

C = np.arange(1, 9).reshape(2, 2, 2) print(C)

print(B.shape)

print(B.dtype)

matrix_cool = np.arange(9).reshape(3, 3) print(matrix_cool)

print(matrix_cool[1, 2])

print(matrix_cool[0, :])

print(matrix_cool[:, 1])

print(matrix_cool[:, 1:])

print(matrix_cool[0:2, 0:2])

print(matrix_cool[:, :])

a1 = np.array([2, 4, 6]) a2 = a1 a1[0] = 8 print(a1) print(a2)

a1 = np.array([2, 4, 6]) a2 = a1.copy() a1[0] = 8 print(a1) print(a2)

# Suma A = np.arange(5, 11) print(A) print(A + 10)

# Resta B = np.full(4, 3) C = np.ones(4, dtype='int') print(B) print(C) print(B - C)

# Multiplicación y división print(A * 10) print(A / 10)

height_list = [74, 74, 72, 72, 73, 69, 69, 71, 76, 71, 73, 73, 74, 74, 69, 70, 73, 75, 78, 79, 76, 74, 76, 72, 71, 75] print(np.mean(height_list)) print(np.median(height_list)) print(np.std(height_list))

print(np.max(height_list)) print(np.min(height_list))

import pandas as pd df = pd.read_csv('Baseball_Players.csv') height = df['Height(inches)'].to_numpy(dtype='int64') weight = df['Weight(pounds)'].to_numpy(dtype='int64')

print(height) height.shape

print(weight) weight.shape