Python Pandas New Column Returns earliest data for each unique ID
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Certainly! Pandas is a powerful data manipulation library in Python, and adding a new column to return the earliest date for each unique ID involves several steps. Below is a tutorial that covers this task with code examples:
First, you need to import the required libraries: pandas for data manipulation and datetime for handling dates.
Let's create a sample DataFrame with columns 'ID' and 'Date' to demonstrate the process.
Next, group the DataFrame by the 'ID' column and find the earliest date for each group using the groupby() and agg() functions.
Now, merge the DataFrame containing the earliest dates back to the original DataFrame using the 'ID' column as a reference.
This will result in a DataFrame where each row contains the original data along with a new column 'earliest_date' showing the earliest date for each unique 'ID'.
This tutorial demonstrates how to add a new column returning the earliest date for each unique ID in a Pandas DataFrame.
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