How to Convert a String Into an Integer in Python

Data type errors are one of the most common obstacles in Python, especially for beginners. A common data type error happens when numbers are formatted as strings, leading to miscalculations, incorrect insights, or flat-out error messages.

In this tutorial, I’ll show you how to navigate these errors, and how to convert Python strings to integers.

The Quick Answer: How to Convert a Python String to an Integer

If your string represents a whole number (i.e., 12), use the int() function to convert a string into an integer. If your string represents a decimal number (i.e., 12.5), use the float() function to convert a string into a float. You can find examples below:

# Converting a string into an integer 
number_str = "10"
number_int = int(number_str)
print(number_int)  # Output: 10

# Converting a string into a float 
decimal_str = "10.5"
decimal_float = float(decimal_str)
print(decimal_float)  # Output: 10.5

Data Types in Python

Python is a dynamically typed language, featuring a variety of data types from strings and integers to floating-point numbers and booleans. Understanding these is crucial for effective programming. Below, is a non-exhaustive list of Python data types:

• String (str): Textual data enclosed in quotes. E.g., greeting = "Hello, World!"
• Integer (int): Whole numbers without a fractional component. E.g., age = 25
• Float (float): Numbers with a decimal point. E.g., height = 5.9
• Boolean (bool): Represents True or False
• List (list): An ordered collection of items that can be of mixed data types. Lists are mutable, allowing modification. For example, colors = ["red", "blue", "green"]
• Dictionary (dict): A collection of key-value pairs, allowing you to store and retrieve data using keys. For example, person = {"name": "Alice", "age": 30}

For more on data types, read this Data Structures in Python tutorial on DataCamp.

Why Convert a String Into an Integer?

Correct data types are essential for accurate calculations. Consider the following example. Let’s assume we have two numbers 5 and 10 which are strings. If we add them together, the answer would be 510, since they are being treated as strings that get concatenated with the + operator.

To get the accurate answer (in this case 15), they would need to be converted to integers before calculating the sum. This is a simple illustration, but imagine this is applied to a dataset of company revenue—this can lead to bad business decisions.

# Summing two numbers that are actually strings
'5'+'10'# This returns 510

# Converting them to integers before summing them
int('5') + int('10') # This returns 15

How to Convert Strings Into Integers in Python

When working with numerical data that are formatted as strings, it's often necessary to convert these strings into integers for calculations or other numerical operations. Python provides a straightforward way to achieve this using the int() function. This function takes a string as input and returns its integer representation, provided the string represents a valid whole number.

# Convert a string to an integer
numeric_string = "42"
converted_integer = int(numeric_string)
print(converted_integer)  # Output: 42

How to Convert Strings Into Floats in Python

In cases where the string represents a number with a decimal point, converting it to an integer would be inappropriate and result in an error. Instead, you can convert these strings to floats using the float() function in Python. Using float data types is crucial especially when working with highly precise data, such as financial data or sensor measurement data.

# Convert a string to a float
decimal_string = "3.14"
converted_float = float(decimal_string)
print(converted_float)  # Output: 3.14

Issues When Converting Strings to Numericals in Python

When converting strings to numbers, a few pitfalls can lead to errors or unexpected results.

Converting non-numeric strings

Attempting to convert a non-numeric string, like 'hello world', to a number will raise an error. If you want to programmatically catch strings that can’t be converted to integers, try using a try/except block to handle such cases gracefully.

try:
    invalid_number = int("hello world")
except ValueError:
    print("This is not a number.")

Converting float strings to integers

Converting a string representing a float directly into an integer results in a ValueError. While you can convert a string representing an integer into a float, you cannot do the opposite. Here’s an example of the error you can get:

string_decimal = '13.5'
# Convert string_decimal into an integer
int(string_decimal) 
# Returns ValueError: invalid literal for int() with base 10: '13.5'

Strings with different bases

When we talk about "bases" in numbers, we're referring to the numbering system in which the number is expressed. The most common base is 10, also known as the decimal system, which is what we use in everyday life. It consists of 10 digits, from 0 to 9.

However, other bases exist and are used in various fields, particularly in computing. For example:

• Binary (Base 2): Uses only 0 and 1. It's the fundamental language of computers.
• Octal (Base 8): Uses digits from 0 to 7. It's less common today but was used in older computing systems.
• Hexadecimal (Base 16): Uses digits from 0 to 9 and letters from A to F (where A=10 and F=15). It's widely used in computing, especially for color codes in web design and memory addresses.

When you have a string representing a number in a base other than 10, you need to specify the base so Python can interpret it correctly. Here's an example using a hexadecimal number:

# Convert a hexadecimal string to an integer
hex_string = "1A"  # In base 16, 1A represents the decimal number 26
converted_int = int(hex_string, 16)  # The '16' tells Python it's in base 16
print(converted_int)  # Output: 26

Conclusion

Navigating data types and conversions in Python is a foundational skill for programming. By understanding how to accurately convert strings to integers and floats, you can avoid common pitfalls and ensure your data manipulation is correct. If you want more on Python, check out our Python Cheat Sheet for Beginners, our guide on How to Learn Python, and our Python Courses.