Working with Text Files in Python

Name: Working with Text Files in Python Course
Price: 36 USD

with Martin Ganchev

4.8/5

(426)

Take your data analyst skillset to the next level: master working with text files in Python

1 hour of content 2514 students

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What you get:

1 hour of content
15 Downloadable resources
World-class instructor
Closed captions
Q&A support
Future course updates
Course exam
Certificate of achievement

Working with Text Files in Python

A course by Martin Ganchev

Start for Free

What you get:

1 hour of content
15 Downloadable resources
World-class instructor
Closed captions
Q&A support
Future course updates
Course exam
Certificate of achievement

$99.00

Lifetime access

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Start for Free

What you get:

1 hour of content
15 Downloadable resources
World-class instructor
Closed captions
Q&A support
Future course updates
Course exam
Certificate of achievement

What You Learn

Gain essential Python skills crucial for advancing to full Python proficiency
Enhance your capabilities in manipulating, reading, and writing text files with Python
Master working with different types of text files and understand the difference between a file and file object, reading and parsing, structured and unstructured data
Gain proficiency in using Python and pandas for efficient loading and parsing of complex data sets
Understand diverse data organization methods, enhancing your ability to structure data effectively
Become a proficient Python programmer who can confidently manage text files and process data

Top Choice of Leading Companies Worldwide

Industry leaders and professionals globally rely on this top-rated course to enhance their skills.

Course Description

By completing this course, you’ll obtain a comprehensive set of theoretical and practical tools to understand and handle raw data. We will extensively cover the difference between a file and file object, reading and parsing, and structured and unstructured data. Then, we’ll dive into the complex world of data connectivity by solving hands-on tasks in Python with *.txt, *.json, *.xlsx, and *.csv formats. The more you learn about data science and become an authentic practitioner, the more you realize that you’ll be independent in your research and making your predictions if (and only if) you can manage your data by yourself.

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1.1 Introduction to Working with Text Files in Python

4 min

1.2 The Difference between File and File Object; Read vs. Parse

3 min

1.3 Defining Structured, Semi-Structured and Unstructured Data

3 min

1.4 What is Data Connectivity: A Text Files Perspective

3 min

2.1 Principles of Importing Data in Python

5 min

2.2 More on Working with Text Files (*.txt vs *.csv)

5 min

Curriculum

1. Introduction to Working with Text Files and Data

4 Lessons 13 Min

What do you need to know to manage text files in Python easily? Apart from learning about text files and data connectivity, there are several distinctions to clarify, among which include File vs File Object, Reading vs Parsing Data, Structured vs Semi-structured and Unstructured Data.

Introduction to Working with Text Files in Python
4 min
The Difference between File and File Object; Read vs. Parse
3 min
Defining Structured, Semi-Structured and Unstructured Data
3 min
What is Data Connectivity: A Text Files Perspective
3 min
2. Principles of Importing Data in Python

4 Lessons 15 Min

In this section, we dig deeper into the contents of a text file and learn about its various types—giving you some ideas on how to work with a messy dataset stored in a text file, regardless of the latter’s format. More precisely, we will clarify terms like ‘character’, ‘separator’, ‘delimiter’, ‘interpreter’, and ‘encoding’ and discuss the most notable types of text files: plain text files and flat files, and fixed-width files. To complete the principles you’ll need, we conclude this section with a presentation of the most widely used naming conventions in programming.

Principles of Importing Data in Python
5 min
More on Working with Text Files (*.txt vs *.csv)
5 min
What about Fixed-width Files?
1 min
Python Programming: Common Naming Conventions
4 min
3. Importing Text Files in Python

13 Lessons 58 Min

Once you’re equipped with general knowledge about working with text files and the specific skills to import them in Python, it’s time to see how things work in practice. In this section, we go into the details about importing data with Python’s open() function, *.csv files with pandas, *.json files in Python, and Excel files. We’ll also discuss several tips and tricks to improve the quality of your dataset in Python and show you how to save it.

Python: Importing Text Files ( open() )
9 min
Python: Importing Text Files ( with open() )
5 min
pandas: Importing *.csv Files - Part I
6 min
pandas: Importing *.csv Files - Part II
3 min
pandas: Importing *.csv Files - Part III
6 min
Python: Importing Data with the "index_col" Parameter
3 min
Python: Importing *.json Files
5 min
Introduction to Working with Excel Files in Python
4 min
Dealing with Excel Data (the *.xlsx Format)
2 min
Importing Data in Python - an Important Exercise
6 min
Python: Importing Data with the pandas' .squeeze() Method
3 min
Jupyter: A General Note on Importing Files
3 min
pandas: Saving Your Data
3 min
4. Conclusion

1 Lesson 1 Min

Through practice and taking certain risks while coding, one can become proficient in dealing with real-world raw text files.

Working with Text Files - Conclusion
1 min

Topics

JupyterPythonProgrammingImporting DataText FilesProgramming

Tools & Technologies

Course Requirements

Highly recommended to take the Intro to Python course first
You will need to install the Anaconda package, which includes Jupyter Notebook

Who Should Take This Course?

Level of difficulty: Intermediate

Aspiring data analysts, data scientists, data engineers, AI engineers
Existing data analysts, data scientists, data engineers who want to boost their Python programming skills
Graduate students who need Python for their studies
Everyone who wants to learn how to code in Python

Exams and Certification

A 365 Data Science Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.

Meet Your Instructor

Martin Ganchev

Worked at

15 Courses

37512 Reviews

555673 Students

Martin began working with 365 in 2016 as the company’s second employee. Martin’s resilience, hard-working attitude, attention to detail, and excellent teaching style played an instrumental role in 365’s early days. He authored some of the firm’s most successful courses. And besides teaching, Martin dreams about becoming an actor. In September 2021, he enrolled in an acting school in Paris, France.