How to Change Data Type in Python?


Python is dynamically typed, meaning that you don’t have to explicitly declare the type of a variable before assigning a value to it. However, sometimes you may need to convert a value from one type to another.

For example, you may have a string containing a number, and you need to convert it to an integer so that you can perform arithmetic operations on it. Or you may have a floating-point number that you need to convert to an integer so that it can be used as an index for a list or tuple. In this blog post, we will show you how to change the data type in Python.

To convert a value from one data type to another, you use the built-in functions str(), int(), and float().

The str() function converts a value from another data type to a string. It takes any value as an argument and returns a string representation of the value. If the value can’t be converted to a string, an error is raised.

a = 1.0 # float type b = str(a) print(type(b)) #output: <class 'str'>
Code language: PHP (php)

The int() function converts a value from another data type to an integer. It takes any value as an argument and returns an integer representation of the value. If the value can’t be converted to an integer, an error is raised.

The float() function converts a value from another data type to a floating-point number. It takes any value as an argument and returns a floating-point representation of the value. If the value can’t be converted to a floating-point number, an error is raised.

#Convert String to Float string_a = "1.0" print(float(string_a)) #Output: 1.0
Code language: PHP (php)

When converting from one data type to another, you should be aware of the possible loss of information due to conversion errors. For example, when converting from a float to an int, the decimal part of the float is truncated (i.e., everything after the decimal point is removed).

Similarly, when converting from an int to a float, there is no loss of information because all integers can be represented exactly as floating-point numbers. However, when converting from one data type with more precision (i.e., more bits) than another data type with less precision (i.e., fewer bits), information may be lost due to rounding errors.

To avoid these kinds of errors, it’s best to lose information by converting from a more precise data type to a less precise one rather than vice versa. For example, if you have floats with many decimal places and you want to convert them into integers, it’s best to Truncate them (i.e., remove the decimal places) rather than round them off because this avoids introducing rounding errors into your calculations.

In this blog post, we discussed how to change data types in python using three built-in functions str(), int(), and float(). We also covered how to know which direction avoids information lost due to issues like truncation and rounding; changing floats into integers loses less information than changing integers into floats.

Andy Avery

I really enjoy helping people with their tech problems to make life easier, ​and that’s what I’ve been doing professionally for the past decade.

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