Introduction to Pandas

Working with Pandas

Machine learning requires huge amounts of data and it requires an efficient way for processing this huge amount of data. Pandas helps us with the latter. It provides efficient data structures like Series, DataFrame and Panel for processing one, two and three dimensional data structures. It provides a good chunk of methods for manipulating the data in these structures. 
It has a good functionality for statistical processing of this data. It provides for indexing, selecting, grouping and filtering the data by columns and values - virtually everything that one would want to do while processing data. Pandas is also extensible and it has builtin capabilities to allow us to add more functionality. It works very well with its cousins - NumPy and Tensorflow. All this makes it the library of choice for data handling.
Let's now look into the important concepts in using Pandas.
These blogs can server as an Introduction. Google and StackOverflow help me with the rest! If you want specific solutions, you can check out the Cookbook on their website. And if you are interested in a formal training, Coursera offers some good courses for it - Applied Data Science and Applied Data Science with Python Scpecialization