Pandas - Tutorial
Pandas is a fast, powerful, flexible and easy to use data analysis and data manipulation tool. It is written for the Python programming language. The name is derived from the econometrics term "panel data", which means data sets that include observations over multiple time periods for the variable. Wes McKinney started building pandas in 2008 when he was working at AQR Capital. It is open sourced software released under the three-clause BSD license. Python with Pandas is used in a wide range of domains including finance, economics, analytics and statistics etc.
This tutorial is intended for software programmers interested in studying basic and advanced concepts of Pandas. This tutorial covers all topics of Pandas which includes general functions, Series, DataFrame, indexing, pandas arrays and pandas tseries. We believe in learning by examples, therefore, each topic is explained with lots of examples that makes you learn Pandas in a very easy way. Along with this, almost all examples can be executed online which provides better understanding of the package and helps you to learn it faster. The classical example of creating a simple DataFrame is mentioned below for the illustration purpose:
import pandas as pd MyList = ['John', 'Marry', 'Jo', 'Sam'] info = pd.DataFrame(MyList) print(info)
The output of the above code will be:
0 0 John 1 Marry 2 Jo 3 Sam
A prior exposure of any programming language would be an added advantage while following this tutorial. Pandas library uses most of its functionality from NumPy library. Therefore, it is recommended to go through the NumPy Tutorial before following this tutorial.