Series and DataFrames are complex data containers that have multiple attributes that use the indexing operator to select data in different ways. In addition to the indexing operator itself, the .iloc and .loc attributes are available and use the indexing operator in their own unique ways. Collectively, these attributes are called the indexers.
The indexing terminology can get confusing. The term indexing operator is used here to distinguish it from the other indexers. It refers to the brackets, [] directly after a Series or DataFrame. For instance, given a Series s, you can select data in the following ways: s[item] and s.loc[item]. The first uses the indexing operator. The second uses the .loc indexer.
Series and DataFrame indexers allow selection by integer location (like Python lists) and by label (like Python dictionaries). The .iloc indexer selects only by integer location and works similarly to Python lists. The .loc indexer selects only by index label, which is similar to how Python dictionaries work.