Book Image

Data Wrangling with Python

By : Dr. Tirthajyoti Sarkar, Shubhadeep Roychowdhury
Book Image

Data Wrangling with Python

By: Dr. Tirthajyoti Sarkar, Shubhadeep Roychowdhury

Overview of this book

For data to be useful and meaningful, it must be curated and refined. Data Wrangling with Python teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain. The book starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The book will further help you grasp concepts through real-world examples and datasets. By the end of this book, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently.
Table of Contents (12 chapters)
Data Wrangling with Python
Preface
Appendix

Basic File Operations in Python


In the previous topic, we investigated a few advanced data structures and also learned neat and useful functional programming methods to manipulate them without side effects. In this topic, we will learn about a few operating system (OS)-level functions in Python. We will concentrate mainly on file-related functions and learn how to open a file, read the data line by line or all at once, and finally how to cleanly close the file we opened. We will apply a few of the techniques we have learned about on a file that we will read to practice our data wrangling skills further.

Exercise 22: File Operations

In this exercise, we will learn about the OS module of Python, and we will also see two very useful ways to write and read environment variables. The power of writing and reading environment variables is often very important while designing and developing data wrangling pipelines.

Note

In fact, one of the factors of the famous 12-factor app design is the very idea...