![]() ![]() There are a lot of classes in this module that helps us to work with dates and time. The datetime is a built-in module of Python which is used to work with dates and times. Let’s start with the datetime module Using datetime We will be using built-in datetime and third-party dateutil modules to convert the datetime string to datetime object. With that said let’s see different ways to convert a datetime string to a datetime object. There are plenty of scenarios like adding dates, subtracting, handling timezones, etc., where converting datetime string to datetime object makes our lives more easier than ever. This is only one scenario where converting to datetime format makes things easy. If they are in datetime format, we can use the comparison operators like numbers. If they are in string format, we can compare them correctly. It will have general string methods, which we won’t be needing while working with dates. It won’t have any special methods to work with dates. ![]() Dates in strings are like normal strings. Converting them to datetime format makes working with them very easy. When we have to work with dates, it’s not easy to work if they are in the string format. Why do we need to convert a datetime string to a datetime object? ![]() Before jumping into that, let’s see why we need to convert it in the first place. ![]() We will learn how to convert a datetime string to a datetime object in Python using different modules. Luckily, python has built-in modules to work with datetime. We need modules, especially for datetime conversions as working them was never been easy for programmers. Almost all programming languages support type conversions for built-in data types.Ĭustom data types like datetime need extra modules for conversions. "West" 06:12 254.09 9.Converting from one type of data to another type of data is crucial in any programming language. Region OutageTime Loss Customers RestorationTime Cause OutageDuration For example, you can calculate the durations of the power outages and attach them to the table as a duration array. "NorthEast" 05:54 0 0 NaT "equipment fault"Īs these table variables are datetime arrays, you can perform convenient calculations with them. Region OutageTime Loss Customers RestorationTime Cause ![]()
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