What is the type of loc and iloc? (brackets vs parentheses)

Question

I'm from C++ background and started learning python recently. I was studying about indexing and selecting data. I came across .iloc[] in the class Series, DataFrame and Panel in the pandas library. I couldn't understand what is .iloc? Is it function or an attribute ? Many times I mistakenly use () instead of [] and don't get the actual result (but it doesn't throw me an error).

Example:

In [43]: s = pd.Series(np.arange(5), index=np.arange(5)[::-1], dtype='int64')

In [44]: s[s.index.isin([2, 4, 6])]
Out[44]: 
4    0
2    2
dtype: int64

In [45]: s.iloc(s.index.isin([2,4,6]))
Out[45]: <pandas.core.indexing._iLocIndexer at 0x7f1e68d53978>

In [46]: s.iloc[s.index.isin([2,4,6])]
Out[46]: 
4    0
2    2
dtype: int64

Could anyone tell me reference where to study much more about such type of operators.

Answer 1

The practical answer: You should think of iloc and loc as pandas extensions of the python list and dictionary respectively and treat them as lookups rather than function or method calls. Thus, keeping with python syntax, always use [] rather than ().

>>> ser = pd.Series( { 'a':3, 'c':9 } )

>>> ser.loc['a']    # pandas dictionary syntax (label-based)
3
>>> ser.iloc[0]     # pandas list/array syntax (location-based)
3

It's basically the same for dataframes, just with an extra dimension to specify, and that's also where iloc and loc become more useful, but that's getting beyond the scope of this question.

The deeper answer: If you are really trying to understand this at a deeper level, you need to understand __getitem__. You could perhaps start here for some basics. The answers in the second link provided in the comments above by @ayhan are also excellent and quite relevant to your question.