Python Data Types

1.4. Python Data Types#

Python supports various data types, which we will introduce as we encounter them. Understanding data types is crucial because every value in Python has an associated type, and how values behave when combined is determined by their types.

To determine the data type of a value, use the type() function:

type(2) # Output: <class 'int'>
type(3.14) # Output: <class 'float'>

1.4.1. int and float#

  • Values such as 4 and -7 have the data type int (short for integer).

  • Values like 2.5 and -17.0 belong to the data type float (short for floating point).

  • The value 7j is an instance of the complex data type (used for complex numbers).

1.4.1.1. Key characteristics#

  1. int

    • Stores whole numbers (positive, negative, or zero) with unlimited precision.

    • Examples: -100, 0, 42.

  2. float

    • Stores numbers with decimal points (positive or negative).

    • Examples: 3.14, -0.001, 2.0.

1.4.1.2. Rules for numeric operations#

Python follows specific rules when performing operations with numeric data types:

  1. Two int operands produce an int

    1 + 2           # Output: 3
type(1 + 2)     # Output: <class 'int'>

  2. Two float operands produce a float

    1.0 + 2.0       # Output: 3.0
type(1.0 + 2.0) # Output: <class 'float'>

  3. Mixing int and float produces a float

    Python automatically converts the int to a float in mixed-type operations.

    17.0 - 10        # Output: 7.0
type(17.0 - 10)  # Output: <class 'float'>

17 - 10.0        # Output: 7.0
type(17 - 10.0)  # Output: <class 'float'>

  4. Omitting the 0 after the decimal point

    You can write 10. instead of 10.0, but this is generally considered poor style.

    10.   # Output: 10.0

1.4.1.3. Differences between int and float#

  1. Memory usage

    • float occupies a fixed amount of memory (commonly 24 bytes on many CPython builds; this can vary by platform and Python version).

    • int uses a variable amount of memory depending on the size of the number.

    Example:

    import sys
sys.getsizeof(2.0)     # Example output: 24 (bytes)
sys.getsizeof(2**30)   # Example output: 32
sys.getsizeof(2**130)  # Example output: 44

    Note: Python’s int is implemented as an arbitrary-precision integer (“bignum”), so it grows as needed.

  2. Precision

    • int values are exact.

    • float values are binary approximations of real numbers due to finite memory, which can lead to rounding behavior.

    Example:

    2 / 3  # Output: 0.6666666666666666
5 / 3  # Output: 1.6666666666666667

  3. Use cases

    • Use int when you do not need fractional values.

    • Use float when working with real numbers or when fractional values are required.

1.4.1.4. Additional notes#

  • The type() function is a handy way to inspect the data type of a value.

  • Python also supports the complex type for complex numbers (e.g., 7 + 3j), though it’s less common in everyday programming.

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