Hello, I am currently following a tutorial (Corey Schafer on YT) to learn the python pandas framework. I’m having an issue where my notebook cell outputs do not return user friendly data for certain numerical data. Its my understanding the pandas uses numpy internally, and that ints, floats, and booleans are returned as numpy dtype objects. for example, accessing a data cell in pandas (not a jupyter cell) with the value of 1.0 would return a numpy object “np.float64(1.0)”. I was under the impression that jupyter would automatically display these numpy objects in a user friendly way in jupyter output cells, ie just the data, but i am consistently getting either “np.int64(1)”, “np.float64(1.0)”, or “np.True_/np.False_” for booleans. This behaviour is not occuring in the instructors tutorial videos, and I seem to recall that it was not behaving this way on my machine when I began the tutorial. I do not recall making any settings changes in jupyter lab or anything that would have initiated this change, though it is possible I may have simply not understood the type of data i was working with in the earlier parts of the tutorial. Strings are of course unaffected, and its possible that I was just looking at string data. I did not notice it until later on when I ran the .median() method on a pandas.Series object. All values in the Series being numpy floats, the returned median was a np.float64 object, and displayed with explicit typing. if I call the .item() method on these objects, the expected value is returned without any explicit typing, just the data in the return cell. This feels like a work around though and does not explain why this is occuring in the first place, which is driving me nuts.
Am I mistaken in thinking jupyter automatically displays numpy dtypes as just the data? I cannot seem to find anything about this anywhere on the internet. If anyone here knows anything about this I would really appreciate any info.