In all seriousness this is an actual problem with numpy/pandas arrays where: ``` Python 3.8.10 (default, Jun 2 2021, 10:49:15) [GCC 9.4.0] on linux Type "help", "copyright", "credits" or "license" for more information.
import numpy numpy.array([1, 2, 3]) array([1, 2, 3]) bool(numpy.array([1, 2, 3])) Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() bool(numpy.array([])) <stdin>:1: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty. False import pandas df = pandas.DataFrame() bool(df) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/graingert/.virtualenvs/redacted/lib/python3.8/site-packages/pandas/core/generic.py", line 1537, in __nonzero__ raise ValueError( ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
eg https://pandas.pydata.org/pandas-docs/version/1.3.0/user_guide/gotchas.html#using-if-truth-statements-with-pandas
> Should it be True because it’s not zero-length, or False because there are False values? It is unclear, so instead, pandas raises a ValueError:
I'm not sure I believe the author here - I think it's clear. It should be True because it's not zero-length.