Python Data Analysis

This is a hands-on, project-based course designed to help you master two of the most popular Python packages for data analysis and business intelligence: 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.

COURSE OUTLINE:

Intro to NumPy & Pandas
- Introduce NumPy and Pandas, two critical Python libraries that help structure data in arrays & DataFrames and contain built-in functions for data analysis
Pandas Series
- Introduce Pandas Series, the Python equivalent of a column of data, and cover their basic properties, creation, manipulation, and useful functions for analysis
Intro to DataFrames
- Work with Pandas DataFrames, the Python equivalent of an Excel or SQL table, and use them to store, manipulate, and analyze data efficiently
Manipulating Python DataFrames
- Aggregate & reshape data in DataFrames by grouping columns, performing aggregation calculations, and pivoting & unpivoting data
Basic Python Data Visualization
- Learn the basics of data visualization in Pandas, and use the plot method to create & customize line charts, bar charts, scatterplots, and histograms
MID-COURSE PROJECT
- Put your skills to the test with a brand new dataset, and use your Python skills to analyze and evaluate a new retailer as a potential acquisition target for Maven MegaMart
Analyzing Dates & Times
- Learn how to work with the datetime data type in Pandas to extract date components, group by dates, and perform time intelligence calculations like moving averages
Importing & Exporting Data
- Read in data from flat files and apply processing steps during import, create DataFrames by querying SQL tables, and write data back out to its source
Joining Python DataFrames
- Combine multiple DataFrames by joining data from related fields to add new columns, and appending data with the same fields to add new rows
FINAL COURSE PROJECT
- Put the finishing touches on your project by joining a new table, performing time series analysis, optimizing your workflow, and writing out your results

Join today and get immediate, lifetime access to the following:

13+ hours of high-quality video
Python NumPy & Pandas PDF ebook (350+ pages)
Downloadable project files & solutions
Expert support and Q&A forum
30-day Udemy satisfaction guarantee

If you're a data analyst, data scientist, business intelligence professional or data engineer looking to add Pandas to your Python skill set, this course is for you.

Happy learning.

-Chris Bruehl (Python Expert & Lead Python Instructor, Maven Analytics)

Looking for our full business intelligence stack? Search for "Maven Analytics" to browse our full course library, including Excel, Power BI, MySQL, Tableau and Machine Learning courses.

See why our courses are among the TOP-RATED on Udemy:

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What's inside

Learning objectives

Master the essentials of numpy and pandas, two of python's most powerful data analysis packages
Learn how to explore, transform, aggregate and join numpy arrays and pandas dataframes
Analyze and manipulate dates and times for time intelligence and time-series analysis

Visualize raw data using plot methods and common chart options like line charts, bar charts, scatter plots and histograms
Import and export flat files, excel workbooks and sql database tables using pandas
Build powerful, practical skills for modern analytics and business intelligence

Master the essentials of numpy and pandas, two of python's most powerful data analysis packages
Learn how to explore, transform, aggregate and join numpy arrays and pandas dataframes
Analyze and manipulate dates and times for time intelligence and time-series analysis
Visualize raw data using plot methods and common chart options like line charts, bar charts, scatter plots and histograms
Import and export flat files, excel workbooks and sql database tables using pandas
Build powerful, practical skills for modern analytics and business intelligence

Syllabus

Getting Started

Course Structure & Outline

READ ME: Important Notes for New Students

DOWNLOAD: Course Resources

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Develops real-world data analysis skills with NumPy and Pandas, which are fundamental Python libraries for data science

Taught by Maven Analytics, who are recognized experts in training data analysts and business intelligence professionals

Emphasizes hands-on practice through project-based learning, which helps learners apply their skills to real-world scenarios

May require prior Python experience, as it assumes some familiarity with the language

Intermediate-level course for those with some data analysis experience looking to enhance their NumPy and Pandas skills

Course may be less beneficial for those seeking a comprehensive introduction to data analysis as it focuses on advanced applications

Reviews summary

Practical numpy & pandas for data analysis

According to students, this is a largely positive course that provides a comprehensive and hands-on approach to mastering NumPy and Pandas. Learners particularly praise the instructor's clear and concise explanations, which simplify complex topics, making the course highly accessible for beginners. The inclusion of practical examples, engaging assignments, and a useful final project is consistently highlighted as effective for reinforcing learning and applying skills to real-world scenarios. While some recent feedback notes that certain functions or methods may be deprecated, requiring learners to adapt, the overall sentiment points to a well-structured and invaluable resource for data analysis.

Ideal for those new to data analysis with Python.

"Amazing course, very helpful for someone new to the topic."

"It's perfect for beginners, especially with the clear explanations."

"Great intro to Pandas and NumPy for beginners; the examples are clear and easy to follow."

The course excels with real-world applications and hands-on practice.

"The projects are practical and useful, allowing me to apply what I've learned."

"The practical examples and hands-on practice really helped solidify my understanding."

"I loved this course; the hands-on practice makes it easy to follow along."

Instructor Chris provides incredibly clear explanations.

"Awesome course with excellent and clear explanations provided by the instructor."

"Chris's teaching is exceptional and I highly recommend this course."

"The instructor explains complex topics clearly and simply, which helps a lot."

Pacing can be fast for some beginners; may lack advanced depth.

"Sometimes I felt it moved a bit too fast for a complete beginner."

"The course provides a good foundation... but some parts felt superficial, especially for advanced topics."

"I found some explanations were a little rushed, but overall the course was great."

Some code uses deprecated functions, requiring troubleshooting.

"The course content is incredibly outdated. Most of the code examples use deprecated functions and syntax which causes errors."

"My only criticism is that I wish the course was updated with the latest versions of Python and Pandas as some methods used are deprecated."

"The course needs to be updated. Some functions used are now deprecated."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python Data Analysis: NumPy & Pandas Masterclass with these activities:

Learn the fundamentals of NumPy arrays

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Refreshes understanding of NumPy arrays and their properties to prepare for more advanced operations in the course.

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Create and manipulate NumPy arrays

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Provides practice in creating, manipulating, and operating on NumPy arrays, reinforcing essential concepts early on.

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Create a NumPy array from a list of numbers and explore its properties.
Manipulate array elements using indexing and slicing.
Perform element-wise operations on arrays using NumPy methods.

Visualize data using Pandas

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Encourages practical application of Pandas for data visualization, reinforcing techniques and fostering a deeper understanding of data structures.

Browse courses on Pandas

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Create a Pandas DataFrame from a dictionary or list of lists.
Visualize data using the Pandas plot function to create histograms, line charts, and scatterplots.

Four other activities

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Show all seven activities

Perform data aggregation and manipulation

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Provides hands-on practice in data aggregation and manipulation, reinforcing techniques and enhancing proficiency in data analysis.

Browse courses on Pandas

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