NumPy Datatypes
The NumPy provides a higher range of numeric data types than that provided by the Python. A list of numeric data types is given in the following table.
SN 
Data type 
Description 
1 
bool_ 
It represents the boolean value indicating true or false. It is stored as a byte. 
2 
int_ 
It is the default type of integer. It is identical to long type in C that contains 64 bit or 32bit integer. 
3 
intc 
It is similar to the C integer (c int) as it represents 32 or 64bit int. 
4 
intp 
It represents the integers which are used for indexing. 
5 
int8 
It is the 8bit integer identical to a byte. The range of the value is 128 to 127. 
6 
int16 
It is the 2byte (16bit) integer. The range is 32768 to 32767. 
7 
int32 
It is the 4byte (32bit) integer. The range is 2147483648 to 2147483647. 
8 
int64 
It is the 8byte (64bit) integer. The range is 9223372036854775808 to 9223372036854775807. 
9 
uint8 
It is the 1byte (8bit) unsigned integer. 
10 
uint16 
It is the 2byte (16bit) unsigned integer. 
11 
uint32 
It is the 4byte (32bit) unsigned integer. 
12 
uint64 
It is the 8 bytes (64bit) unsigned integer. 
13 
float_ 
It is identical to float64. 
14 
float16 
It is the halfprecision float. 5 bits are reserved for the exponent. 10 bits are reserved for mantissa, and 1 bit is reserved for the sign. 
15 
float32 
It is a single precision float. 8 bits are reserved for the exponent, 23 bits are reserved for mantissa, and 1 bit is reserved for the sign. 
16 
float64 
It is the double precision float. 11 bits are reserved for the exponent, 52 bits are reserved for mantissa, 1 bit is used for the sign. 
17 
complex_ 
It is identical to complex128. 
18 
complex64 
It is used to represent the complex number where real and imaginary part shares 32 bits each. 
19 
complex128 
It is used to represent the complex number where real and imaginary part shares 64 bits each. 
NumPy dtype
All the items of a numpy array are data type objects also known as numpy dtypes. A data type object implements the fixed size of memory corresponding to an array.
We can create a dtype object by using the following syntax.
The constructor accepts the following object.
Object: It represents the object which is to be converted to the data type.
Align: It can be set to any boolean value. If true, then it adds extra padding to make it equivalent to a C struct.
Copy: It creates another copy of the dtype object.
Example 1
Output:
Example 2
Output:
Creating a Structured data type
We can create a maplike (dictionary) data type which contains the mapping between the values. For example, it can contain the mapping between employees and salaries or the students and the age, etc.
Consider the following example.
Example 1
Output:
Example 2
Output:
[(10000.12,) (20000.5 ,)]
