How to loop over a DataFrame using Pandas
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Pandas gives you the ability to loop over columns and rows.
Here are the different ways to loop over columns or rows using the Pandas Library.
We define our DataFrame first
We define an example DataFrame.
Solution 1 : Loop over the columns name
Sometimes you might want to loop over the columns name. To perform any operation on the entirety of the DataFrame.
Here is how we loop over the column list of a DataFrame.
Solution 2 : Loop over a specific column
Now vertically, you might want to loop over the values of a specific column.
This is how we do it.
If you want to edit its records, I would rather use the solution 3.
Solution 3 : Loop over to edit a specific column
If you want to edit the column values, the fastest way is to apply a lambda function which performs the operation you want to apply on the column values.
Solution 4 : Loop over rows using apply
You might need to do an operation that combines two or more column values.
This is the method using apply. Watch out the axis=1.
Solution 5 : Loop over rows using iterrows()
If you want to check the full row of a Pandas DataFrame that is the solution the you are looking for.
for idx, row in df.iterrows():
print(f"{row['student']} : {row['gpa']}")
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