Error when trying to apply log method to pandas data frame column in Python
This happens when the datatype of the column is not numeric. Try
arr['retlog'] = log(arr['close'].astype('float64')/arr['close'].astype('float64').shift(1))I suspect that the numbers are stored as generic 'object' types, which I know causes log to throw that error. Here is a simple illustration of the problem:
In [15]: np.log(Series([1,2,3,4], dtype='object'))---------------------------------------------------------------------------AttributeError Traceback (most recent call last)<ipython-input-15-25deca6462b7> in <module>()----> 1 np.log(Series([1,2,3,4], dtype='object'))AttributeError: logIn [16]: np.log(Series([1,2,3,4], dtype='float64'))Out[16]: 0 0.0000001 0.6931472 1.0986123 1.386294dtype: float64Your attempt with math.log did not work because that function is designed for single numbers (scalars) only, not lists or arrays.
For what it's worth, I think this is a confusing error message; it once stumped me for awhile, anyway. I wonder if it can be improved.