Dataframes have a few methods for applying numpy/scipy functions to entries (they work for regular python functions as well, but they're optimized for numpy/scipy).
For example, DataFrame.apply(function) will call your function on each column/row of your frame, with column being the default,
which means that
will (I think) do what you want.
Since you're using apply with a numpy/scipy function, you can also do
which will pass the underlying raw numpy array to your function, achieving much better performance.
As I mentioned above, you can also use apply with regular python functions, e.g.
df_with_values_squared = df.apply(lambda x: x **2)
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