![]() As we’ve explored, Python offers several built-in functions like int(), str(), float(), and complex() to convert data from one type to another. Data Type Conversions: A Pillar of Python’s Data Manipulationĭata type conversions form a significant part of Python’s data manipulation capabilities. This will output Cannot convert complex number to integer. Print('Cannot convert complex number to integer') Let’s see what happens when we try to convert this complex number to an integer: try: To tackle this, you can use the complex() function to convert the string into a complex number. Nonetheless, an attempt to convert a string that represents a complex number into an integer will result in a ValueError. Python is also capable of handling complex numbers. Converting Strings Representing Complex Numbers It’s important to note that the int() function truncates the decimal part and does not round off to the nearest integer. ![]() The solution is to first convert the string to a float, and then convert the float to an integer. This is because the int() function can only convert strings that represent valid integers, and ‘123.45’ is not one. number_string = '123.45'Įxecuting this code results in a ValueError: invalid literal for int() with base 10: '123.45'. Here’s what occurs when we employ the int() function. Imagine a scenario where you have a string that represents a floating-point number, like ‘123.45’, and you want to convert it to an integer. Let’s delve deeper into the realm of Python type conversion. While converting a basic numeric string to an integer in Python is straightforward, real-world scenarios often demand more complex conversions. In such instances, proficiency in data type conversion and error handling can prevent unexpected crashes, enhancing the robustness and reliability of your program. When reading user input or data from a file, there’s always a chance the data won’t be in the expected format. Now, instead of the program crashing, it will print ‘Invalid integer’ and continue executing the remaining code.Įxample of try/except block with a valid integer string: try: To circumvent such errors, we can use a try/except block to catch the ValueError and handle it gracefully. This highlights the significance of error handling in type conversion. In our case, ‘123a’ is not a valid integer, hence the error. This error arises because the int() function can only convert strings that represent valid integers. Here, executing the code results in a ValueError: invalid literal for int() with base 10: '123a'. However, it’s not without its potential pitfalls.Ĭonsider this example: number_string = '123a' The int() function is straightforward and highly effective. The output of number_int is 123, an integer, not a string. ![]() In this case, we convert the string ‘123’ into an integer using the int() function. Python’s built-in int() function is adept at converting a string into an integer.
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