Pedro A.
Before 365:
Industrial Engineer | NIBOL
After 365:
Data Manager | NIBOL
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Online Course
free
Data Ingestion with Pandas
with
Samson Afolabi
Start Your Data Journey and learn everything about ingesting data from various data storage formats like Flat Files, Excel Files, API's, JSON's and Relational Databases.
656 students already have enrolled
Skill level:
Basic
Duration:
1 hour
-
Lessons (1 hour)
- Lessons (1 hour)
CPE credits:
2.5
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
Accredited:
certificate
What You Learn
- Import CSV data using the pandas library.
- Read data from flat files and Excel spreadsheets.
- Load HTML and JSON datasets with pandas.
- Access data from databases using pandas.
- Retrieve and load data from APIs.
Topics & tools
pandas basicsdata engineeringdata analysispythonSQL
Your instructor
Data Scientist & Analytics Leader | Team Lead C Analytics at Free2move | Data Engineering & AI
Track record
Bringing real-world expertise from leading global companies
Academic background
Master's degree, Mathematics
Course OVERVIEW
Description
CPE Credits: 2.5
Field of Study: Information Technology
Delivery Method: QAS Self Study
Delivery Method: QAS Self Study
Data is everywhere, but before you can analyze it, you need to load it efficiently and correctly. "Data Ingestion with Pandas" is designed to help you master the art of importing data from various sources, including flat files, Excel, databases, APIs, and JSON sources, using Python’s powerful Pandas library.
This course takes you through every aspect of data ingestion, from reading simple CSV's and Excel files to handling large datasets efficiently. You’ll learn how to work with Excel files, including reading multiple sheets, selecting specific columns, and handling large files. As we progress, you'll dive into working with databases, where you'll connect to Relational databases, connect to them and retrieve data using queries, and seamlessly integrate it into Pandas.
In the modern data landscape, APIs and JSON are crucial sources of real-time data. This course will equip you with the skills to extract data from web APIs, parse complex JSON structures, and transform them into clean, structured DataFrames. Along the way, you’ll also learn how to handle common ingestion errors, such as encoding issues, missing values, and memory limitations, ensuring a smooth and efficient data-loading process.
Whether you’re a data analyst, data scientist, or software engineer, mastering data ingestion is an essential skill. This course is very practical, hands-on, and designed for both beginners and those looking to refine their Pandas expertise.
By the end, you’ll have the confidence to import and manage data from multiple sources efficiently, setting the stage for deeper analysis and machine learning workflows. Let’s dive in and unlock the power of data ingestion with Pandas.
Prerequisites
- Python (version 3.8 or later), pandas library, and a code editor or IDE (e.g., Jupyter Notebook, Spyder, or VS Code)
- Basic familiarity with Python programming is required.
- Familiarity with NumPy is helpful but not mandatory.
Advanced preparation
Curriculum
28 lessons
22 exercises
1 exam
- 2. Import Data From Flat Files16 Min
Learn how to read data from Flat Files using
pd.read_csv(). You’ll explore handling large datasets efficiently, troubleshooting common errors like encoding issues, and using parameters likeusecolsanddtypeto improve performance. - 3. Import Data From Excel Files16 Min
Master working with Excel spreadsheets using
pd.read_excel(). This section covers reading multiple sheets, selecting specific columns, writing back to Excel, and ensuring smooth data handling with Pandas. You’ll also learn how to deal with common formatting and date issues. - 4. Importing Json Data and APIs19 Min
Master working with Excel spreadsheets using
pd.read_excel(). This section covers reading multiple sheets, selecting specific columns, and ensuring smooth data handling with Pandas.
You’ll also learn how to deal with common formatting and date issues as well as dealing with Google sheets. - 5. Import Data from Databases14 Min
Go beyond flat files and connect Pandas to Relational databases.
Learn how to execute queries, fetch large datasets efficiently, and integrate SQL data into Pandas for further analysis. This section also covers more about other data ingestion libraries. - 6. Conclusion4 Min
Wrap up the course by revisiting key takeaways and best practices for efficient data ingestion. You’ll also get insights on next steps to deepen your Pandas knowledge and integrate your skills into real-world data workflows.
- 7. Course exam45 Min
Free preview
1.1 Introduction - Data Ingestion With Pandas
6 min
1.2 What You'll Learn and Getting Ready
1 min
$29,000
average salary increase
after moving to an AI and data science career
94%
of AI and data science graduates
successfully change
or advance their careers.
9 in 10
of our graduates landed a new AI & data job
after enrollment
ACCREDITED certificates
Craft a resume and LinkedIn profile you’re proud of—featuring certificates recognized by leading global
institutions.
Earn CPE-accredited credentials that showcase your dedication, growth, and essential skills—the qualities
employers value most.
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