python pandas get year from datetime
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Title: Extracting Year from Datetime in Python Pandas: A Step-by-Step Tutorial
Introduction:
Python Pandas is a powerful data manipulation library that provides various functions for working with datetime data. One common task is extracting the year from a datetime column in a Pandas DataFrame. In this tutorial, we'll walk through the process with step-by-step explanations and code examples.
Step 1: Import Pandas and Create a DataFrame
Start by importing the Pandas library and creating a sample DataFrame with a datetime column.
Step 2: Extracting Year using dt.year
Pandas provides the dt accessor, which allows us to access the components of datetime objects. We can use dt.year to extract the year from the datetime column.
This will output:
Step 3: Additional Tips
If your datetime column is not in the datetime format, you can convert it using pd.to_datetime() as shown in the example below:
Conclusion:
In this tutorial, we learned how to extract the year from a datetime column in a Pandas DataFrame using the dt.year accessor. This process is helpful when dealing with time-series data, allowing you to analyze and visualize trends over different years. Feel free to apply similar techniques to extract other components like month, day, hour, etc., based on your specific needs.
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