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Data Wrangling with Python

You're reading from   Data Wrangling with Python Creating actionable data from raw sources

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789800111
Length 452 pages
Edition 1st Edition
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Authors (2):
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Shubhadeep Roychowdhury Shubhadeep Roychowdhury
Author Profile Icon Shubhadeep Roychowdhury
Shubhadeep Roychowdhury
Dr. Tirthajyoti Sarkar Dr. Tirthajyoti Sarkar
Author Profile Icon Dr. Tirthajyoti Sarkar
Dr. Tirthajyoti Sarkar
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Table of Contents (12) Chapters Close

Data Wrangling with Python
Preface
1. Introduction to Data Wrangling with Python FREE CHAPTER 2. Advanced Data Structures and File Handling 3. Introduction to NumPy, Pandas, and Matplotlib 4. A Deep Dive into Data Wrangling with Python 5. Getting Comfortable with Different Kinds of Data Sources 6. Learning the Hidden Secrets of Data Wrangling 7. Advanced Web Scraping and Data Gathering 8. RDBMS and SQL 9. Application of Data Wrangling in Real Life 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...

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