Numpy data Types

Last Updated : 23 Jan, 2025

NumPy is a powerful Python library that can manage different types of data. Here we will explore the Datatypes in NumPy and How we can check and create datatypes of the NumPy array.

DataTypes in NumPy

A data type in NumPy is used to specify the type of data stored in a variable. Here is the list of characters available in NumPy to represent data types.

Character	Meaning
b	Boolean
f	Float
m	Time Delta
O	Object
U	Unicode String
i	Integer
u	Unsigned Integer
c	Complex Float
M	DateTime
S	String
V	A fixed chunk of memory for other types (void)

The list of various types of data types provided by NumPy are given below:

Data Type	Description
bool_	Boolean
int_	Default integer type (int64 or int32)
intc	Identical to the integer in C (int32 or int64)
intp	Integer value used for indexing
int8	8-bit integer value (-128 to 127)
int16	16-bit integer value (-32768 to 32767)
int32	32-bit integer value (-2147483648 to 2147483647)
int64	64-bit integer value (-9223372036854775808 to 9223372036854775807)
uint8	Unsigned 8-bit integer value (0 to 255)
uint16	Unsigned 16-bit integer value (0 to 65535)
uint32	Unsigned 32-bit integer value (0 to 4294967295)
uint64	Unsigned 64-bit integer value (0 to 18446744073709551615)
float_	Float values
float16	Half precision float values
float32	Single-precision float values
float64	Double-precision float values
complex_	Complex values
complex64	Represent two 32-bit float complex values (real and imaginary)
complex128	Represent two 64-bit float complex values (real and imaginary)

Checking the Data Type of NumPy Array

We can check the datatype of Numpy array by using dtype. Then it returns the data type all the elements in the array.

Python

import numpy as np

# Create a NumPy array
arr = np.array([1, 2, 3, 4, 5])

# Check the data type of the array
data_type = arr.dtype
print(data_type)

Output

int64

Create Arrays With a Defined Data Type

We can create an array with a defined data type by specifying "dtype" attribute in numpy.array() method while initializing an array.

Python

import numpy as np

arr1 = np.array([1, 2, 3, 4], dtype=np.float64)  

# Creating a 3x3 int32 array of zeros
arr2 = np.zeros((3, 3), dtype=np.int32)  

# Creating a 2x2 complex128 array of ones
arr3 = np.ones((2, 2), dtype=np.complex128)  

# Creating a 1D bool array
arr4 = np.empty((4,), dtype=np.bool_)  

# Print the arrays and their data types
print(arr1.dtype)
print(arr2.dtype)
print(arr3.dtype)
print(arr4.dtype)

Output

float64
int32
complex128
bool

Convert Data Type of NumPy Arrays

We can convert data type of an arrays from one type to another using astype() function.

Python

import numpy as np

arr1 = np.array([1.2, 2.5, 3.7])

# Converting to int32
arr2 = arr1.astype(np.int32)  

# Print new array and its type
print(arr2)
print(arr2.dtype)