Book Image

Learning pandas - Second Edition

By : Michael Heydt
Book Image

Learning pandas - Second Edition

By: Michael Heydt

Overview of this book

You will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance. With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science.
Table of Contents (16 chapters)

Working with CSV and text/tabular format data

CSV formatted data is likely to be one of the most common forms of data you may use in pandas. Many web-based services provide data in a CSV format, as well as many information systems within an enterprise. It is an easy format to use and is commonly used as an export format for spreadsheet applications such as Excel.

A CSV is a file consisting of multiple lines of text-based data, with values separated by commas. It can be thought of as a table of data similar to a single sheet in a spreadsheet program. Each row of the data is in its own line in the file, and each column for each row is stored in text format, with a comma separating the data in each column.

For more details on the specifics of CSV files, feel free to visit http://en.wikipedia.org/wiki/Comma-separated_values.

As CSV is so common and easily understood, we will spend...