In this chapter, we'll cover the following topics:
Importing data from CSV
Importing data from Microsoft Excel files
Importing data from fixed-width data files
Importing data from tab-delimited files
Importing data from a JSON resource
Exporting data to JSON, CSV, and Excel
Importing and manipulating data with Pandas
Importing data from a database
Cleaning up data from outliers
Reading files in chunks
Reading streaming data sources
Importing image data into NumPy arrays
Generating controlled random datasets
Smoothing the noise in real-world data
Introduction
This chapter covers basics about importing and exporting data from various formats. We first introduce how to import data by just using only the capabilities of the Python standard library; then we introduce the powerful Pandas library which is becoming the de facto standard in data manipulation in Python. Also we've covered the ways of cleaning data such as normalizing values, adding missing data, live data inspection, and usage of some similar tricks to get data correctly prepared for visualization.