Add column to a Python pandas DataFrame based on values in an other column
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Certainly! Let's create a tutorial on how to add a new column to a Python pandas DataFrame based on values in another column. We'll use a code example to illustrate each step.
First, you need to import the pandas library.
Let's create a sample DataFrame for demonstration purposes.
Now, define a function that takes a row as input and returns the value for the new column based on values in another column. In this example, let's create a new column 'Category' based on the 'Age' column.
Use the apply function to apply the logic defined in the function to each row of the DataFrame and create a new column.
Now, let's print the DataFrame to see the newly added 'Category' column.
In this tutorial, we covered the process of adding a new column to a Pandas DataFrame based on values in another column. This involved creating a sample DataFrame, defining a function to apply the new column logic, and using the apply function to create the new column.
Feel free to adapt the logic in the function according to your specific use case!
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