In [1]:

    

import numpy as np


    

In [2]:

    

a = np.array([1, 2, 3], dtype=np.int64)
print(a.dtype)


    

    




int64

In [3]:

    

a = np.array([1, 2, 3], dtype='int64')
print(a.dtype)


    

    




int64

In [4]:

    

a = np.array([1, 2, 3], dtype='i8')
print(a.dtype)


    

    




int64

In [5]:

    

print(int is np.int)


    

    




True

In [6]:

    

a = np.array([1, 2, 3], dtype=int)
print(a.dtype)


    

    




int64

In [7]:

    

a = np.array([1, 2, 3], dtype='int')
print(a.dtype)


    

    




int64

In [8]:

    

a_str = np.array([1, 2, 3], dtype=str)
print(a_str)
print(a_str.dtype)


    

    




['1' '2' '3']
<U1

In [9]:

    

a_str[0] = 'abcde'
print(a_str)


    

    




['a' '2' '3']

In [10]:

    

a_str10 = np.array([1, 2, 3], dtype='U10')
print(a_str10.dtype)


    

    




<U10

In [11]:

    

a_str10[0] = 'abcde'
print(a_str10)


    

    




['abcde' '2' '3']

In [12]:

    

a_object = np.array([1, 0.1, 'one'], dtype=object)
print(a_object)
print(a_object.dtype)


    

    




[1 0.1 'one']
object

In [13]:

    

print(type(a_object[0]))
print(type(a_object[1]))
print(type(a_object[2]))


    

    




<class 'int'>
<class 'float'>
<class 'str'>

In [14]:

    

a_object[2] = 'oneONE'
print(a_object)


    

    




[1 0.1 'oneONE']

In [15]:

    

l = [1, 0.1, 'oneONE']
print(type(l[0]))
print(type(l[1]))
print(type(l[2]))


    

    




<class 'int'>
<class 'float'>
<class 'str'>

In [16]:

    

print(a_object * 2)


    

    




[2 0.2 'oneONEoneONE']

In [17]:

    

print(l * 2)


    

    




[1, 0.1, 'oneONE', 1, 0.1, 'oneONE']