Indexing , Slicing & Subsetting DataFram in Python

1. Introduction

The Python and NumPy indexing operators [ ] and attribute operator ‘.’ (dot) provide quick and easy access to pandas data structures across a wide range of use cases. The index is like an address, that’s how any data point across the data frame or series can be accessed. Rows and columns both have indexes.

The axis labeling information in pandas objects serves many purposes:

· Identifies data (i.e. provides metadata) .

· Enables automatic and explicit data alignment.

· Allows intuitive getting and setting of subsets of the data.

2. Indexing in terms of analytics

3. Indexing in terms of programming