Pandas is an open-source library build on top of NumPy library. It is a python package used for manipulating data and time series.
It is popular for importing data and it’s analytics in an easier way.
Pandas was released in 2008.
Today it is very popular in many domains including finance, analytics, statistics, etc.
Prerequisites: Before we start learning Pandas, it is advised to have a good knowledge of Python and NumPy.
Step1:
Begin with it’s installation in your computer. Learn about series, data structures, and data frames.
Step2:
Learn about panel, descriptive statistics, basic functionality, and function application.
Step3:
Once done with everything mentioned above. Start learning about reindexing, iteration, sorting, and to work with texts.
Step4:
We are halfaway done with it. Understand about the concepts of option & customization, indexing & selecting data.
Step5:
Move on to some more important concepts. Learn about statistical function, window function, aggregation, and missing data.
Step6:
Secret of success is found in your regular actions. Keep learning regulary to better grasp the concept of Pandas. Learn aggregate functions like GroupBy, Merging/joining, and concatenation.
Step7:
Learn data functionality, timedelta, categorial data, sparse data, caveats, and gotchas.
Step8:
Understand the concept of Visualization and IO tools.
Step9:
Whoa! We are done with Pandas. Keep exploring more in it to strengthen your knowledge in it.
