There is no operator.div in Python 3, no; that only existed in Python 2.

There is a operator.truediv() function instead, as well as a operator.floordiv() function. The reason for this division (no pun intended) is that the old Python 2 / operator would return an integer if both operands are integers, a float otherwise, while these two functions always return the same type, regardless of the type of inputs.

You can divide one dataframe by another and pandas will automagically aligned the index and columns and subsequently divide the appropriate values. EG df1 / df2

If you divide a dataframe by series, pandas automatically aligns the series index with the columns of the dataframe. It maybe that you want to align the index of the series with the index of the dataframe instead. If this is the case, then you will have to use the div method.

So instead of:

df / s

You use

df.div(s, axis=0)

Which says to align the index of s with the index of df then perform the division while broadcasting over the other dimension, in this case columns.

They have different behaviours.

a//b rounds down, so 5//-2 == -3.

int(a/b) rounds towards zero, so int(5/-2) == -2

Edit to add: I just realized something important! a/b always produces a float. If a is too large for the quotient to be represented by a float (i.e, the result is greater than about 10^308), then a/b will fail with an OverflowError. This does not happen with a//b. Observe:

>>> int(10**1000/3)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
OverflowError: integer division result too large for a float
>>> 10**1000//3
333333333333333333333333333333333333333333333333333...

Additionally, the floating point number resulting from the division will have rounding errors. Beyond about 2^53, 64-bit floating point numbers cannot accurately represent all integers, so you will get incorrect results:

>>> int(10**22/3)
3333333333333333508096
>>> 10**22//3
3333333333333333333333