Python for Data Analysis guides readers about the ways in which Python can be used to analyze large sets of data. It provides readers with an introduction to practical data related problems and how Python can manipulate, crunch, clean and process that data. The book talks about various parts of the language and provides a fair idea of the libraries that one will be required to use while solving such problems.
Python for Data Analysis is suited for people who are not familiar with Python. The book makes use of a number of case studies, in order to make the explanations easy to understand. The author uses the IPython interactive shell as the primary development environment. One can learn the fundamental and advanced numerical Python techniques that will help them analyze data more efficiently. Readers are also informed about pandas library, which is replete with tools that can be used for data analysis. These high performance tools can be used to manipulate data in many ways and one can reshape, clean, transform or merge data. Python for Data Analysis also teaches readers how to measure data points at specific intervals or at specific instants. Through this book, one can learn to solve numerical analysis problems in social sciences, economics, finance and many other fields.