NumPy Data Types

Data Types in Python

By default, Python includes the following data types:

• Strings: Used to represent text data, enclosed in quotation marks (e.g., “ABCD”).
• Integer: Used to represent whole numbers (e.g., -1, -2, -3).
• Float: Used to represent real numbers (e.g., 1.2, 42.42).
• Boolean: Used to represent True or False values.
• Complex: Used to represent complex numbers (e.g., 1.0 + 2.0j, 1.5 + 2.5j).

Data Types in NumPy

NumPy offers additional data types and uses single-character identifiers to represent them, such as ‘i’ for integers and ‘u’ for unsigned integers.

Here is a list of all data types in NumPy along with their corresponding characters:

• i – integer
• b – boolean
• u – unsigned integer
• f – float
• c – complex float
• m – timedelta
• M – datetime
• O – object
• S – string
• U – Unicode string
• V – fixed-size memory block for other types (void)

Checking the Data Type of an Array

The NumPy array object includes a property called dtype that provides the data type of the array.

Example

Retrieve the data type of an array object.

Example

Obtain the data type of an array that contains strings.