import numpy as np
arr = np.arange(0, 11)
arr
arr[0:5] = 100
arr
# create slice of array
slice_of_array = arr[0:5]
#This will change the original array "arr"
slice_of_array[:] = 1
slice_of_array
arr
# creating copy of array
slice_of_array = arr[0:5].copy()
#This will change the original array "arr"
slice_of_array[:] = 200
slice_of_array
# the original array didnt change
arr
arr_2d = np.array(([5,10,15],[20,25,30],[35,40,45]))
#Show
arr_2d
# Get value 25
arr_2d[1][1]
# Other way to get values, using comma
arr_2d[1,1]
arr = np.arange(1,11)
arr
# get bool for each index in array
condition = arr > 6
condition
#filter only the true resuls
arr[condition]
# the same only one line
arr[arr>2]
arr2d = np.arange(0,100).reshape(10,10)
arr2d
# Get complety row
arr2d[[6, 2,4]]
np.full(shape=(2, 2), fill_value=5)
np.arange(0,10, dtype='float64')
#cambiar un array a un tipo de dato especifico
arr = np.arange(0,10)
arr.astype(np.float64)