When will I receive my Course Certificate?

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

Why can’t I audit this course?

This course is currently available only to learners who have paid or received financial aid, when available.

Is financial aid available?

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.

Foundations of Data Analysis with Pandas and Python

Foundations of Data Analysis with Pandas and Python

This course is part of Data Analysis with Pandas and Python Specialization

Instructor: Packt - Course Instructors

3,630 already enrolled

Included with Learn more

Ask Coursera

3 modules

Gain insight into a topic and learn the fundamentals.

31 reviews

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

31 reviews

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Explain how to navigate and utilize Jupyter Lab for Python programming.
Write Python code, including functions and data structures.
Manipulate and analyze data using Pandas Series and DataFrames.
Apply data cleaning and sorting techniques to prepare datasets for analysis.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is part of the Data Analysis with Pandas and Python 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 3 modules in this course

Embark on a comprehensive journey into data analysis with Python and Pandas. Learn to set up Anaconda and Jupyter Lab on macOS and Windows, navigate Jupyter Lab's interface, and execute code cells.

- You'll start by mastering essential Python programming concepts, including data types, operators, variables, functions, and classes. - Then, dive into Pandas to create and manipulate Series and DataFrames. The course covers data importing from sources like CSV, Excel, and SQL databases, along with techniques for sorting, filtering, and data extraction. - Advanced analysis methods, including group-by operations, merging, joining datasets, and pivot tables, are also explored to equip you with the skills for efficient and sophisticated data analysis. Ideal for aspiring data analysts and scientists, no prior programming knowledge is necessary with the included Python crash course.

In this module, we will guide you through the initial setup required for this course, including installing the Anaconda distribution on both macOS and Windows, and creating Python environments using Anaconda Navigator. You'll also learn to unpack the provided course materials, navigate the Jupyter Lab interface, execute code cells, and import necessary libraries to get you started on your data analysis journey.

What's included

8 videos3 readings1 assignment

8 videosTotal 74 minutes

Introduction to the Specialization11 minutes
macOS - Download and Install the Anaconda Distribution4 minutes
Windows - Download and Install the Anaconda Distribution4 minutes
Use Anaconda Navigator to Create a New Environment10 minutes
Unpack Course Materials + The Startdown and Shutdown Process12 minutes
Intro to the Jupyter Lab Interface10 minutes
Code Cell Execution14 minutes
Import Libraries into Jupyter Lab8 minutes

3 readingsTotal 30 minutes

Introduction to the Course 'Foundations of Data Analysis with Pandas and Python'10 minutes
Full Specialization Resources10 minutes
Note for Learners - Accessing the Pandas Folder10 minutes

1 assignmentTotal 15 minutes

Installation and Setup Assessment15 minutes

In this module, we will cover the essentials of Python programming, starting with the use of comments to enhance code readability. You'll gain familiarity with Python's basic data types, operators, variables, and built-in functions, laying the groundwork for effective coding. We will delve into custom functions, string methods, lists, indexing and slicing, dictionaries, and classes to build your programming skills. Finally, you will learn to navigate and use Python libraries within Jupyter Lab, a critical skill for data analysis.

What's included

12 videos1 assignment

12 videosTotal 184 minutes

Comments8 minutes
Basic Data Types15 minutes
Operators21 minutes
Variables13 minutes
Built-in Functions9 minutes
Custom Functions20 minutes
String Methods25 minutes
Lists15 minutes
Index Positions and Slicing18 minutes
Dictionaries17 minutes
Classes10 minutes
Navigating Libraries using Jupyter Lab12 minutes

1 assignmentTotal 15 minutes

Python Crash Course Assessment15 minutes

In this module, we will explore the creation and manipulation of Pandas Series objects from different data sources like lists and dictionaries. We will delve into essential methods and attributes of Series, understand the use of parameters and arguments, and learn techniques to import data into Series using 'pd.read_csv'. Additionally, we will cover methods for inspecting, sorting, and extracting Series values, along with advanced operations like broadcasting and applying functions to Series elements.

What's included

21 videos1 reading2 assignments

21 videosTotal 171 minutes

Create a Series Object from a List10 minutes
Create a Series Object from a Dictionary5 minutes
Intro to Series Methods5 minutes
Intro to Attributes11 minutes
Parameters and Arguments15 minutes
Import Series with the pd.read_csv Function23 minutes
The head and tail Methods3 minutes
Passing Series to Python Built-In Functions7 minutes
Check for Inclusion with Python's in Keyword7 minutes
The sort_values Method7 minutes
The sort_index Method5 minutes
Extract Series Values by Index Position11 minutes
Extract Series Values by Index Label6 minutes
The get Method7 minutes
Overwrite a Series Value7 minutes
The copy Method11 minutes
Math Methods on Series Objects7 minutes
Broadcasting4 minutes
The value_counts Method5 minutes
The apply Method8 minutes
The map Method9 minutes

1 readingTotal 10 minutes

Conclusion to the course 'Foundations of Data Analysis with Pandas and Python'10 minutes

2 assignmentsTotal 75 minutes

Exploring Pandas Series for Data Analysis Assessment15 minutes
Full Course Assessment60 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.

Instructor

Instructor ratings

(10 ratings)

Packt - Course Instructors

Packt

1,961 Courses603,836 learners

Offered by

Packt

Explore more from Data Analysis

Status: Free Trial
Packt
Data Analysis with Pandas and Python
Specialization
Packt
Data Science Foundations: NumPy, Pandas & Visualization
Course
Status: Free Trial
Coursera
Applying Python for Data Analysis
Course
Coursera
Python for Data Analysis: Pandas & NumPy
Guided Project

Why people choose Coursera for their career

Felipe M.

Learner since 2018

"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."

Jennifer J.

Learner since 2020

"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."

Larry W.

Learner since 2021

"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

5 stars
78.12%
4 stars
12.50%
3 stars
6.25%
2 stars
3.12%
1 star
0%

Showing 3 of 31

Reviewed on May 24, 2026

I only have one problem

View more reviews

Unlock access to 10,000+ courses with a subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 4,700 global companies that choose Coursera for Business

Frequently asked questions

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.