python pandas iterate over rows and columns

pandas is a powerful data manipulation library in python, and it provides various methods to iterate over rows and columns of a dataframe. in this tutorial, we'll explore different techniques to iterate over rows and columns using pandas.
the iterrows() method returns an iterator yielding index and row data as a pandas series. here's an example:
the apply() method can be used along with axis=1 to apply a function to each row. here's an example:
the iteritems() method returns an iterator for column name and data as a pandas series. here's an example:
you can use a simple for loop to iterate over column names and then access each column's data. here's an example:
these are some basic techniques for iterating over rows and columns in a pandas dataframe. depending on your specific use case, you may choose the method that best suits your needs. keep in mind that pandas is optimized for vectorized operations, so it's often better to use built-in functions when possible.
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