Description

This is a hands-on, project-based course designed to help you master 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.

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 DataFrames
       Aggregate & reshape data in DataFrames by grouping columns, performing aggregation calculations, and pivoting & unpivoting data
   Basic 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 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 & 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 scientist, BI analyst 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)
Who this course is for:

   Analysts or BI professionals looking to learn data analysis with NumPy and Pandas
   Aspiring data scientists who want to build or strengthen their Python skills
   Anyone interested in learning one of the most popular open source programming languages in the world
   Students looking to learn powerful, practical skills with unique, hands-on projects and course demos

Requirements

   We’ll use Anaconda & Jupyter Notebooks (a free, user-friendly coding environment)
   Familiarity with base Python is strongly recommended, but not a strict prerequisite

Last Updated 8/2022