Python for Data Analysis, 3rd Edition

Chapter 6. Data Loading, Storage, and File Formats

Reading data and making it accessible (often called data loading) is a necessary first step for using most of the tools in this book. The term parsing is also sometimes used to describe loading text data and interpreting it as tables and different data types. I’m going to focus on data input and output using pandas, though there are numerous tools in other libraries to help with reading and writing data in various formats.

Input and output typically fall into a few main categories: reading text files and other more efficient on-disk formats, loading data from databases, and interacting with network sources like web APIs.

6.1 Reading and Writing Data in Text Format

pandas features a number of functions for reading tabular data as a DataFrame object. Table 6-1 summarizes some of them; pandas.read_csv is one of the most frequently used in this book. We will look at binary data formats later in Section 6.2, “Binary Data Formats,”.

Table 6-1. Text and binary data loading functions in pandas

Function	Description
read_csv	Load delimited data from a file, URL, or file-like object; use comma as default delimiter
read_fwf	Read data in fixed-width column format (i.e., no delimiters)
read_clipboard	Variation of read_csv that reads data from the clipboard; useful for converting tables from web pages
read_excel	Read tabular data from an Excel XLS or XLSX file
read_hdf	Read HDF5 files written by pandas
read_html	Read all tables found in the given HTML document ...