Python and Pandas for Data Engineering

Python and Pandas for Data Engineering

This course is part of Python, Bash and SQL Essentials for Data Engineering Specialization

Instructors: Kennedy Behrman

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4 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

5 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

5 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

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

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

25 assignments

Taught in English

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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 videosTotal 72 minutes

Overview of Python, Bash and SQL Essentials for Data Engineering7 minutes
Meet your Course Instructor: Kennedy Behrman1 minute
Overview of Key Concepts6 minutes
Introduction to Setting Up Your Python Environment0 minutes
Installing Packages with pip in Python6 minutes
Saving Requirements File in Python3 minutes
Creating and Using a Python Virtual Environment6 minutes
Expression Statements in Python3 minutes
Assignment Statements in Python5 minutes
Import Statements in Python4 minutes
Other Simple Statements in Python5 minutes
Compound Statements in Python5 minutes
If Statements in Python7 minutes
While Loops in Python5 minutes
Functions in Python8 minutes

13 readingsTotal 130 minutes

Key Terms10 minutes
Report a problem with the course10 minutes
Key Terms10 minutes
Meet your Supporting Instructors: Alfredo Deza and Noah Gift10 minutes
Course Structure and Discussion Etiquette10 minutes
Getting Started and Best Practices10 minutes
Key Terms10 minutes
Lesson Reflection10 minutes
Key Terms10 minutes
Lesson Reflection10 minutes
Key Terms10 minutes
Evaluating to True or False10 minutes
Lesson Reflection10 minutes

6 assignmentsTotal 330 minutes

Quiz-Setting Up Your Python Environment180 minutes
Assignment Statements30 minutes
Import Statements30 minutes
If Statements30 minutes
While Loops30 minutes
Python Statements30 minutes

1 discussion promptTotal 10 minutes

Meet and Greet (optional)10 minutes

6 ungraded labsTotal 360 minutes

Install a Package with the pip Command60 minutes
Export a Requirements File60 minutes
Create a Virtual Environment60 minutes
Practicing with Expression Statements60 minutes
Decorator Functions60 minutes
Setting up a Python Environment60 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 videosTotal 65 minutes

Introduction to Python Essentials1 minute
Sequences in Python8 minutes
Lists and Tuples in Python6 minutes
Strings in Python11 minutes
Creating Range Objects in Python3 minutes
Creating Dictionaries in Python5 minutes
Accessing Dictionary Data in Python4 minutes
Dictionary Views in Python3 minutes
Sets and Set Operations in Python7 minutes
List Comprehensions in Python7 minutes
Generator Expressions in Python4 minutes
Generator Functions in Python7 minutes

6 readingsTotal 60 minutes

Key Terms10 minutes
Lesson Reflection10 minutes
Key Terms10 minutes
Lesson Reflection10 minutes
Key Terms10 minutes
Lesson Reflection10 minutes

8 assignmentsTotal 240 minutes

Sequence Operations30 minutes
Lists and Tuples30 minutes
Range Objects30 minutes
Accessing Data in Dictionaries30 minutes
Sets and Set Operations30 minutes
List Comprehensions30 minutes
Generator Expressions30 minutes
Essential Python Concepts30 minutes

5 ungraded labsTotal 300 minutes

Practicing with Strings in Python60 minutes
Creating Dictionaries in Python60 minutes
Dictionary Views in Python60 minutes
Comprehensions and Generators in Python60 minutes
Practicing Essential Python60 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 videosTotal 63 minutes

Introduction to Data in Python: Pandas and Alternatives1 minute
Creating Pandas DataFrames in Python4 minutes
Investigating Data in a Pandas DataFrame7 minutes
Selecting Data in a Pandas DataFrame7 minutes
Manipulating Pandas DataFrames5 minutes
Updating Pandas DataFrame Data5 minutes
Applying Functions in a Pandas DataFrame6 minutes
Creating NumPy Arrays in Python16 minutes
Spark and PySpark DataFrames in Python6 minutes
Creating Dask DataFrames in Python7 minutes

7 readingsTotal 70 minutes

Key Terms10 minutes
Lesson Reflection10 minutes
Key Terms10 minutes
Lesson Reflection10 minutes
Key Terms10 minutes
Polars10 minutes
Lesson Reflection10 minutes

4 assignmentsTotal 120 minutes

NumPy30 minutes
PySpark30 minutes
Dask30 minutes
Pandas and Alternatives30 minutes

8 ungraded labsTotal 480 minutes

Creating DataFrames60 minutes
Looking at Data in DataFrames60 minutes
Selecting Data in a Pandas DataFrame60 minutes
Manipulating DataFrames60 minutes
Updating Data in a DataFrame60 minutes
Applying Functions in a Pandas DataFrame60 minutes
Manipulate DataFrames with Polars to gain insights60 minutes
Pandas and Alternatives60 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 videosTotal 48 minutes

Introduction to Python Development Environments0 minutes
Introduction to Vim Normal Mode7 minutes
Switching from Normal to Insert and Visual Modes in Vim5 minutes
Working with the Vim Command Line7 minutes
Vim Configuration4 minutes
Introduction to Visual Studio Code2 minutes
Setting Up Visual Studio Code3 minutes
Debugging Visual Studio Code3 minutes
What is Version Control?3 minutes
Introduction to Git and Git Concepts8 minutes
Version Control with GitHub6 minutes
Summary of Python and Pandas for Data Engineering0 minutes

8 readingsTotal 80 minutes

Key Terms10 minutes
Lesson Reflection10 minutes
Key Terms10 minutes
Lesson Reflection10 minutes
Key Terms10 minutes
Lesson Reflection10 minutes
Next Steps10 minutes
Share your learning experience10 minutes

7 assignmentsTotal 225 minutes

Insert and Visual Modes30 minutes
Vim Command Line Mode30 minutes
Features of Visual Studio Code30 minutes
Version Control30 minutes
Git Commands30 minutes
Hosted Git30 minutes
Cumulative Python and Pandas for Data Engineering Quiz45 minutes

8 ungraded labsTotal 480 minutes

Basic Vim Commands60 minutes
Explore Visual Studio Code60 minutes
Visual Studio Code Debugger60 minutes
Setup and Provision a Python Project60 minutes
Pandas Final Challenge: Life Expectancy and Happiness60 minutes
Final Jupyter Sandbox60 minutes
Final VS Code Sandbox60 minutes
Final Sandbox Linux Desktop60 minutes

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Instructors

Kennedy Behrman

Duke University

7 Courses67,782 learners

Offered by

Duke University

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