The data used in analyses is typically provided from other systems via files that are created and updated at various intervals, dynamically via access over the Web, or from various types of databases. The pandas library provides powerful facilities for easy retrieval of data from a variety of data sources and converting it into pandas objects. Here, we will briefly demonstrate this ease of use by loading data from files and from financial web services.
The pandas library provides built-in support for loading data in
.csv format, a common means of storing structured data in text files. Provided with the code from this book is a file
data/test1.csv in the CSV format, which represents ...