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Self-paced course
Self-paced course
Data Analysis with Python & Pandas
Data Analysis with Python & Pandas
Rating 4.6
258 reviews
258 reviews
258 reviews
Course Description
This is a hands-on, project-based course designed to help you learn two of the most popular Python packages for data analysis: NumPy and Pandas.
We’ll start with a NumPy primer to introduce arrays and array properties, practice common operations like indexing, slicing, filtering and sorting, and explore important concepts like vectorization and broadcasting.
From there we’ll dive into Pandas, and focus on the essential tools and methods to explore, analyze, aggregate and transform series and dataframes. You’ll practice plotting dataframes with charts and graphs, manipulating time-series data, importing and exporting various file types, and combining dataframes using common join methods.
Throughout the course you’ll play the role of Data Analyst for Maven Mega Mart, a large, multinational corporation that operates a chain of retail and grocery stores. Using the Python skills you learn throughout the course, you’ll work with members of the Maven Mega Mart team to analyze products, pricing, transactions, and more.
If you’re a data scientist, BI analyst or data engineer looking to add Pandas to your Python skill set, this is the course for you.
Course Description
This is a hands-on, project-based course designed to help you learn two of the most popular Python packages for data analysis: NumPy and Pandas.
We’ll start with a NumPy primer to introduce arrays and array properties, practice common operations like indexing, slicing, filtering and sorting, and explore important concepts like vectorization and broadcasting.
From there we’ll dive into Pandas, and focus on the essential tools and methods to explore, analyze, aggregate and transform series and dataframes. You’ll practice plotting dataframes with charts and graphs, manipulating time-series data, importing and exporting various file types, and combining dataframes using common join methods.
Throughout the course you’ll play the role of Data Analyst for Maven Mega Mart, a large, multinational corporation that operates a chain of retail and grocery stores. Using the Python skills you learn throughout the course, you’ll work with members of the Maven Mega Mart team to analyze products, pricing, transactions, and more.
If you’re a data scientist, BI analyst or data engineer looking to add Pandas to your Python skill set, this is the course for you.
Course Content
33.0 video hours
Skills you'll learn in this course
Load, join & reshape datasets efficiently using pandas
Perform aggregations, window functions & complex calculations
Handle dates, text & missing values like a pro
Export clean, analysis‑ready data for BI & machine learning
Meet your instructors
Chris Bruehl
Analytics Engineer & Lead Python Instructor
Chris is a Python expert, certified Statistical Business Analyst, and seasoned Data Scientist, having held senior-level roles at large insurance firms and financial service companies. He earned a Masters in Analytics at NC State's Institute for Advanced Analytics, where he founded the IAA Python Programming club.
Student reviews
I loved this course The instructor, Chris Breuhi, explained every concept in a very easy-to-understand way, starting from the basics. We began with NumPy and then moved on to Pandas Series and DataFrames, Aggregation.and lot other . Each chapter included exercises to help apply what we learned, which made the concepts clearer. The course also includes two projects — a mid-course project and a final project — where you can apply everything you've learned. It’s a great way to build confidence through practice. Thanks
asad ali
This course takes you through using Pandas really well. The assignments and project really help you put your newly learned skills to the test! I can see myself using Pandas and Python for Data Analysis. It pleased me to see how Pandas Pivot tables are created. Having used pivot tables in Excel I could relate to creating pivot tables in Pandas. Chris did an excellent job of taking me through the details. And I'm keen to put the information learned to good use.
Andrew Hubbard
Great course, definitely helped me learn some new Python skills I can use at work!
Gilbert Urgiles, CPA
Included learning paths
Course credential
You’ll earn the course certification by completing this course and passing the assessment requirements
Data Analysis with Python & Pandas
Data Analysis with Python & Pandas
CPE Accreditation
CPE Credits:
0
Field of Study:
Information Technology
Delivery Method:
QAS Self Study
Maven Analytics LLC is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org.
For more information regarding administrative policies such as complaints or refunds, please contact us at admin@mavenanalytics.io or (857) 256-1765.
*Last Updated: May 25, 2023
Course Description
This is a hands-on, project-based course designed to help you learn two of the most popular Python packages for data analysis: NumPy and Pandas.
We’ll start with a NumPy primer to introduce arrays and array properties, practice common operations like indexing, slicing, filtering and sorting, and explore important concepts like vectorization and broadcasting.
From there we’ll dive into Pandas, and focus on the essential tools and methods to explore, analyze, aggregate and transform series and dataframes. You’ll practice plotting dataframes with charts and graphs, manipulating time-series data, importing and exporting various file types, and combining dataframes using common join methods.
Throughout the course you’ll play the role of Data Analyst for Maven Mega Mart, a large, multinational corporation that operates a chain of retail and grocery stores. Using the Python skills you learn throughout the course, you’ll work with members of the Maven Mega Mart team to analyze products, pricing, transactions, and more.
If you’re a data scientist, BI analyst or data engineer looking to add Pandas to your Python skill set, this is the course for you.
Course Description
This is a hands-on, project-based course designed to help you learn two of the most popular Python packages for data analysis: NumPy and Pandas.
We’ll start with a NumPy primer to introduce arrays and array properties, practice common operations like indexing, slicing, filtering and sorting, and explore important concepts like vectorization and broadcasting.
From there we’ll dive into Pandas, and focus on the essential tools and methods to explore, analyze, aggregate and transform series and dataframes. You’ll practice plotting dataframes with charts and graphs, manipulating time-series data, importing and exporting various file types, and combining dataframes using common join methods.
Throughout the course you’ll play the role of Data Analyst for Maven Mega Mart, a large, multinational corporation that operates a chain of retail and grocery stores. Using the Python skills you learn throughout the course, you’ll work with members of the Maven Mega Mart team to analyze products, pricing, transactions, and more.
If you’re a data scientist, BI analyst or data engineer looking to add Pandas to your Python skill set, this is the course for you.
Curriculum
1
Orientation & Benchmark Assessment
1
Orientation & Benchmark Assessment
1
Orientation & Benchmark Assessment
2
Getting Started
2
Getting Started
2
Getting Started
3
NumPy Primer
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
3
NumPy Primer
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
3
NumPy Primer
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
4
Pandas Series
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
4
Pandas Series
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
4
Pandas Series
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
5
DataFrames
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
5
DataFrames
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
5
DataFrames
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6
Aggregating & Reshaping DataFrames
6 MIN
6 MIN
6 MIN
6 MIN
6
Aggregating & Reshaping DataFrames
6 MIN
6 MIN
6 MIN
6 MIN
6
Aggregating & Reshaping DataFrames
6 MIN
6 MIN
6 MIN
6 MIN
7
Basic Data Visualization
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
7
Basic Data Visualization
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
7
Basic Data Visualization
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
8
MID-COURSE PROJECT
8
MID-COURSE PROJECT
8
MID-COURSE PROJECT
9
Analyzing Dates & Times
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
9
Analyzing Dates & Times
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
9
Analyzing Dates & Times
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
10
Importing & Exporting Data
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
10
Importing & Exporting Data
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
10
Importing & Exporting Data
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
11
Joining DataFrames
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
11
Joining DataFrames
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
11
Joining DataFrames
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
12
FINAL PROJECT
12
FINAL PROJECT
12
FINAL PROJECT
13
Final Assessment
6 MIN
13
Final Assessment
6 MIN
13
Final Assessment
6 MIN
14
Course Feedback & Next Steps
14
Course Feedback & Next Steps
14
Course Feedback & Next Steps
Meet your instructors
Chris Bruehl
Analytics Engineer & Lead Python Instructor
Chris is a Python expert, certified Statistical Business Analyst, and seasoned Data Scientist, having held senior-level roles at large insurance firms and financial service companies. He earned a Masters in Analytics at NC State's Institute for Advanced Analytics, where he founded the IAA Python Programming club.
Student reviews
I loved this course The instructor, Chris Breuhi, explained every concept in a very easy-to-understand way, starting from the basics. We began with NumPy and then moved on to Pandas Series and DataFrames, Aggregation.and lot other . Each chapter included exercises to help apply what we learned, which made the concepts clearer. The course also includes two projects — a mid-course project and a final project — where you can apply everything you've learned. It’s a great way to build confidence through practice. Thanks
asad ali
This course takes you through using Pandas really well. The assignments and project really help you put your newly learned skills to the test! I can see myself using Pandas and Python for Data Analysis. It pleased me to see how Pandas Pivot tables are created. Having used pivot tables in Excel I could relate to creating pivot tables in Pandas. Chris did an excellent job of taking me through the details. And I'm keen to put the information learned to good use.
Andrew Hubbard
Great course, definitely helped me learn some new Python skills I can use at work!
Gilbert Urgiles, CPA
Included learning paths
Course credential
You’ll earn the course certification by completing this course and passing the assessment requirements
Data Analysis with Python & Pandas
Data Analysis with Python & Pandas
CPE Accreditation
CPE Credits:
0
Field of Study:
Information Technology
Delivery Method:
QAS Self Study
Maven Analytics LLC is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org.
For more information regarding administrative policies such as complaints or refunds, please contact us at admin@mavenanalytics.io or (857) 256-1765.
*Last Updated: May 25, 2023
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