Adventures in Machine Learning

Python Programming: Data Types and Formatting Numbers Explained

Understanding Data Types in Python

Python is one of the most popular programming languages in the world because of its simple and powerful syntax. One of the key features of Python that makes it so versatile is its support for a wide range of data types.

In this article, we will explore the different data types in Python and how to format numbers to 2 decimal places.

Data Types in Python

Data types are an essential aspect of programming languages because they determine how the program stores and manipulates data. Python supports many data types, and we can categorize them into the following groups:

Numeric Types

These are data types that represent numeric values.

  • int: for integer values
  • float: for floating-point values (decimal numbers)
  • complex: for complex numbers with real and imaginary parts

Sequence Types

These are data types that represent a sequence of values.

  • lists: mutable (modifiable)
  • tuples: immutable (cannot be changed)
  • ranges: used to represent arithmetic progressions

Mapping Type

This is a data type that represents a collection of key-value pairs.

  • dictionaries: unordered collections of key-value pairs, where each key is unique

Set Types

These are data types that represent a set of unique values.

  • sets: mutable and unordered collections of unique values
  • frozensets: immutable and unordered sets

Text Type

This is a data type that represents a sequence of Unicode characters.

  • str (string): immutable (cannot be changed) and represent text values, such as names or messages

Boolean Type

This is a data type that represents a Boolean (True/False) value.

  • bool

Binary Types

These are data types that represent sequences of bytes.

  • bytes: immutable sequences of bytes
  • bytearray: mutable
  • memoryview

None Type

This is a data type that represents the absence of a value.

  • None

Getting the Datatype

Sometimes it’s necessary to know the data type of a value in Python. We can use the type() function to determine the type of a value.

x = 5
print(type(x))  # Output: 

Formatting a Number to 2 Decimal Places

When working with numeric data, we sometimes need to format the data for presentation. Python provides different ways to format numbers.

Using %f Formatter

The %f formatter is used to format a floating-point value to a string with a fixed number of decimal places. For instance, to format a float to two decimal places, use %.2f.

x = 3.14159265
print("The value of x is %.2f" % x)  # Output: The value of x is 3.14

Using str.format()

The str.format() method provides a more flexible way of formatting strings. We can also use the {:.2f} format specifier to round off a floating-point value to 2 decimal places.

x = 3.14159265
print("The value of x is {:.2f}".format(x))  # Output: The value of x is 3.14

We can use a combination of placeholders, format specifiers, and precision values to format strings. For example:

age = 19
height = 175.5
print("I am {} years old and my height is {:.0f} cm")

Here, the {} placeholders represent where the values will be inserted, while the {:.0f} specifier formats the height value to a whole number.

Conclusion

Python is known for its simplicity and versatility, and its support for a range of data types makes it an excellent language to work with for various tasks. Understanding the different data types and how to format numbers is essential for any Python programmer.

This article has given an overview of the most common data types in Python and two methods of formatting numbers to two decimal places.

In conclusion, this article has explored the different data types in Python, including numeric, sequence, mapping, set, text, boolean, binary, and None types, as well as how to get the data type of a value using the type() function.

Additionally, the article discussed two common methods for formatting numbers to two decimal places: the %f formatter and the str.format() method. Understanding data types and formatting numbers are crucial skills for Python programmers, and this article provided an overview of the key concepts.

As you continue to work with Python, it’s essential to remember these concepts to create effective and accurate programs.

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