NumPy Arrays

Agnieszka 
list = [2, 4, 6, 8, 14, 16]
vec1 = np.array(list)
print("vec1={}".format(vec1))
print(type(vec1))
print("vec1 shape={}".format(vec1.shape))
print(vec1.dtype)

#results:
vec1=[ 2 4 6 8 14 16]
class ‘numpy.ndarray’
vec1 shape=(6,)
int32

vec1 = np.array([1, 2, 3, 4], ndmin=5)
print("vec1={}".format(vec1))
print('number of dimensions :', vec1.ndim)

#results:
vec1=[[[[[1 2 3 4]]]]]
number of dimensions : 5

vec2 = np.array(list[:3])
print("vec2 = {}".format(vec2))
vec3 = np.array(list[3:])
print("vec3 = {}".format(vec3))
print("vec23 =", np.array(vec2),np.array(vec3))
print("vec2+vec3 =", np.array(vec2+vec3))

#results:
vec2 = [2 4 6]
vec3 = [ 8 14 16]
vec23 = [2 4 6] [ 8 14 16]
vec2+vec3 = [10 18 22] #2+8,4+14,6+16

vec4 = np.array([[1,2,3], [3,6,9]])
print('2nd element on 1st dim: ', vec4[0, 1])
print('3rd element on 2nd dim: ', vec4[1, 2])

#results:
2nd element on 1st dim: 2
3rd element on 2nd dim: 9

arr1 = np.array([1,3,5,7,9])
arr2 = (arr1.copy()) *2
arr3 = arr2 + arr1
arr4 = arr3.view()
arr4[0] = 11
print(arr1)
print(arr2)
print(arr3)
print(arr4)

#results:
[1 3 5 7 9]
[ 2 6 10 14 18]
[11 9 15 21 27]
[11 9 15 21 27]

Loops in one-, two-, three-dimensional arrays

arr1 = np.array([1, 2, 3])
arr2 = np.array([[1, 2, 3], [4, 5, 6]])
arr3 = np.array([[[1, 2, 3], [4, 5, 6]],
                 [[7, 8, 9], [10, 11, 12]]])

for x in arr1:
      print(x)

for x in arr2:
  for y in x:
      print(y)

for x in arr3:
  for y in x:
      for z in y:
          print(z)

Join, split, sort 

arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
arr3 = np.array([[3,2,1],[9,8,7]])
arr = np.concatenate((arr1, arr2))
arr_sp = np.array_split(arr,2)
print(arr)
print(arr_sp)
print(np.sort(arr3))

#Results:
[1 2 3 4 5 6]
[array([1, 2, 3]), array([4, 5, 6])]
[[1 2 3]
[7 8 9]]