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Python and Pandas for Data Engineering

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Python and Pandas for Data Engineering

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Gain insight into a topic and learn the fundamentals.
4.6

277 reviews

Beginner level

Recommended experience

Flexible schedule
5 weeks at 10 hours a week
Learn at your own pace
96%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.6

277 reviews

Beginner level

Recommended experience

Flexible schedule
5 weeks at 10 hours a week
Learn at your own pace
96%
Most learners liked this course

What you'll learn

  • Setup a provisioned Python project environment

  • Use Pandas libraries to read and write data into data structures and files

  • Employ Vim and Visual Studio Code to write Python code

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

25 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Python, Bash and SQL Essentials for Data Engineering Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

In this first course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will learn how to set up a version-controlled Python working environment which can utilize third party libraries. You will learn to use Python and the powerful Pandas library for data analysis and manipulation. Additionally, you will also be introduced to Vim and Visual Studio Code, two popular tools for writing software. This course is valuable for beginning and intermediate students in order to begin transforming and manipulating data as a data engineer.

In this module, you will learn how to set up an isolated Python environment with third party libraries and apply it by setting up a virtual environment including Pandas and Jupyter.

What's included

15 videos13 readings6 assignments1 discussion prompt6 ungraded labs

15 videos•Total 72 minutes
  • Overview of Python, Bash and SQL Essentials for Data Engineering•7 minutes
  • Meet your Course Instructor: Kennedy Behrman•1 minute
  • Overview of Key Concepts•6 minutes
  • Introduction to Setting Up Your Python Environment•0 minutes
  • Installing Packages with pip in Python•6 minutes
  • Saving Requirements File in Python•3 minutes
  • Creating and Using a Python Virtual Environment•6 minutes
  • Expression Statements in Python•3 minutes
  • Assignment Statements in Python•5 minutes
  • Import Statements in Python•4 minutes
  • Other Simple Statements in Python•5 minutes
  • Compound Statements in Python•5 minutes
  • If Statements in Python•7 minutes
  • While Loops in Python•5 minutes
  • Functions in Python•8 minutes
13 readings•Total 130 minutes
  • Key Terms•10 minutes
  • Report a problem with the course•10 minutes
  • Key Terms•10 minutes
  • Meet your Supporting Instructors: Alfredo Deza and Noah Gift•10 minutes
  • Course Structure and Discussion Etiquette•10 minutes
  • Getting Started and Best Practices•10 minutes
  • Key Terms•10 minutes
  • Lesson Reflection•10 minutes
  • Key Terms•10 minutes
  • Lesson Reflection•10 minutes
  • Key Terms•10 minutes
  • Evaluating to True or False•10 minutes
  • Lesson Reflection•10 minutes
6 assignments•Total 330 minutes
  • Python Statements•30 minutes
  • Quiz-Setting Up Your Python Environment•180 minutes
  • Assignment Statements•30 minutes
  • Import Statements•30 minutes
  • If Statements•30 minutes
  • While Loops•30 minutes
1 discussion prompt•Total 10 minutes
  • Meet and Greet (optional)•10 minutes
6 ungraded labs•Total 360 minutes
  • Install a Package with the pip Command•60 minutes
  • Export a Requirements File•60 minutes
  • Create a Virtual Environment•60 minutes
  • Practicing with Expression Statements•60 minutes
  • Decorator Functions•60 minutes
  • Setting up a Python Environment•60 minutes

In this module, you will learn how to create and use Python Sequences, Dictionaries, Sets, List Comprehensions, and Generators. Additionally, you will learn how to apply these by manipulating client data in a Jupyter notebook.

What's included

12 videos6 readings8 assignments5 ungraded labs

12 videos•Total 65 minutes
  • Introduction to Python Essentials•1 minute
  • Sequences in Python•8 minutes
  • Lists and Tuples in Python•6 minutes
  • Strings in Python•11 minutes
  • Creating Range Objects in Python•3 minutes
  • Creating Dictionaries in Python•5 minutes
  • Accessing Dictionary Data in Python•4 minutes
  • Dictionary Views in Python•3 minutes
  • Sets and Set Operations in Python•7 minutes
  • List Comprehensions in Python•7 minutes
  • Generator Expressions in Python•4 minutes
  • Generator Functions in Python•7 minutes
6 readings•Total 60 minutes
  • Key Terms•10 minutes
  • Lesson Reflection•10 minutes
  • Key Terms•10 minutes
  • Lesson Reflection•10 minutes
  • Key Terms•10 minutes
  • Lesson Reflection•10 minutes
8 assignments•Total 240 minutes
  • Essential Python Concepts•30 minutes
  • Sequence Operations•30 minutes
  • Lists and Tuples•30 minutes
  • Range Objects•30 minutes
  • Accessing Data in Dictionaries•30 minutes
  • Sets and Set Operations•30 minutes
  • List Comprehensions•30 minutes
  • Generator Expressions•30 minutes
5 ungraded labs•Total 300 minutes
  • Practicing with Strings in Python•60 minutes
  • Creating Dictionaries in Python•60 minutes
  • Dictionary Views in Python•60 minutes
  • Comprehensions and Generators in Python•60 minutes
  • Practicing Essential Python•60 minutes

In this module, you will learn how to load data into a Pandas DataFrame and write statements to select columns and rows from a DataFrame. Additionally, you will apply comparison and boolean operators as a method of selecting data.

What's included

10 videos7 readings4 assignments8 ungraded labs

10 videos•Total 63 minutes
  • Introduction to Data in Python: Pandas and Alternatives•1 minute
  • Creating Pandas DataFrames in Python•4 minutes
  • Investigating Data in a Pandas DataFrame•7 minutes
  • Selecting Data in a Pandas DataFrame•7 minutes
  • Manipulating Pandas DataFrames•5 minutes
  • Updating Pandas DataFrame Data•5 minutes
  • Applying Functions in a Pandas DataFrame•6 minutes
  • Creating NumPy Arrays in Python•16 minutes
  • Spark and PySpark DataFrames in Python•6 minutes
  • Creating Dask DataFrames in Python•7 minutes
7 readings•Total 70 minutes
  • Key Terms•10 minutes
  • Lesson Reflection•10 minutes
  • Key Terms•10 minutes
  • Lesson Reflection•10 minutes
  • Key Terms•10 minutes
  • Polars•10 minutes
  • Lesson Reflection•10 minutes
4 assignments•Total 120 minutes
  • Pandas and Alternatives•30 minutes
  • NumPy•30 minutes
  • PySpark•30 minutes
  • Dask•30 minutes
8 ungraded labs•Total 480 minutes
  • Creating DataFrames•60 minutes
  • Looking at Data in DataFrames•60 minutes
  • Selecting Data in a Pandas DataFrame•60 minutes
  • Manipulating DataFrames•60 minutes
  • Updating Data in a DataFrame•60 minutes
  • Applying Functions in a Pandas DataFrame•60 minutes
  • Manipulate DataFrames with Polars to gain insights•60 minutes
  • Pandas and Alternatives•60 minutes

This week, you will learn the basics of some popular development environments and apply it by writing code in Vim and Visual Studio Code. Additionally, you will learn how to check your code into a Git repository.

What's included

12 videos8 readings7 assignments8 ungraded labs

12 videos•Total 48 minutes
  • Introduction to Python Development Environments•0 minutes
  • Introduction to Vim Normal Mode•7 minutes
  • Switching from Normal to Insert and Visual Modes in Vim•5 minutes
  • Working with the Vim Command Line•7 minutes
  • Vim Configuration•4 minutes
  • Introduction to Visual Studio Code•2 minutes
  • Setting Up Visual Studio Code•3 minutes
  • Debugging Visual Studio Code•3 minutes
  • What is Version Control?•3 minutes
  • Introduction to Git and Git Concepts•8 minutes
  • Version Control with GitHub•6 minutes
  • Summary of Python and Pandas for Data Engineering•0 minutes
8 readings•Total 80 minutes
  • Key Terms•10 minutes
  • Lesson Reflection•10 minutes
  • Key Terms•10 minutes
  • Lesson Reflection•10 minutes
  • Key Terms•10 minutes
  • Lesson Reflection•10 minutes
  • Next Steps•10 minutes
  • Share your learning experience•10 minutes
7 assignments•Total 225 minutes
  • Cumulative Python and Pandas for Data Engineering Quiz•45 minutes
  • Insert and Visual Modes•30 minutes
  • Vim Command Line Mode•30 minutes
  • Features of Visual Studio Code•30 minutes
  • Version Control•30 minutes
  • Git Commands•30 minutes
  • Hosted Git•30 minutes
8 ungraded labs•Total 480 minutes
  • Basic Vim Commands•60 minutes
  • Explore Visual Studio Code•60 minutes
  • Visual Studio Code Debugger•60 minutes
  • Setup and Provision a Python Project•60 minutes
  • Pandas Final Challenge: Life Expectancy and Happiness•60 minutes
  • Final Jupyter Sandbox•60 minutes
  • Final VS Code Sandbox•60 minutes
  • Final Sandbox Linux Desktop•60 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Instructor ratings
4.7 (80 ratings)
Duke University
7 Courses•67,329 learners

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Showing 3 of 277

BZ
·

Reviewed on Mar 9, 2023

The lessons were laid out well and were easy to follow. I enjoyed how the labs reinforced the material that was covered.

BL
·

Reviewed on Jun 29, 2022

Good for quick basics of working with bash, github, python, virtual environments and such

CY
·

Reviewed on Jul 4, 2022

It's all overview tool that need to use for work in data engineer

Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,