ERR: could pandas suggest to use bitwise operators to filter instead of `and` and `or`, as on Kaggle?
Currently, if one writes
```python
>>> import pandas as pd
>>> df = pd.DataFrame([1,2,3])
>>> df
   0
0  1
1  2
2  3
>>> df[df[0].ge(0) and df[0].lt(0)]
```
then the traceback shows
```python-traceback
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/marco/pandas-dev/pandas/core/generic.py", line 1326, in __nonzero__
    raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
```

I've noticed that [Kaggle](https://www.kaggle.com) add their own warning when someone tries to do this:
```
To combine filtering conditions in Pandas, use bitwise operators ('&' and '|') not pure Python ones ('and' and 'or')
```

See below:

![image](https://user-images.githubusercontent.com/33491632/85942450-4facb780-b921-11ea-968d-3b1453ff200d.png)


----

Is this something that could be in pandas as well? Sure, there's no way of reading users' minds - perhaps they reached this error by some other means - but would the error message be clearer if there was an extra line reading
```
If you were trying to combine filtering conditions in Pandas, use bitwise operators ('&' and '|') instead of pure Python ones ('and' and 'or')
```
?