What you'll learn:
- 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
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.
COURSEOUTLINE:
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-COURSEPROJECT
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
FINALCOURSEPROJECT
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 todayand get immediate, lifetime accessto the following:
13+ hours of high-quality video
Python NumPy &Pandas PDF ebook (350+pages)
Downloadable project files &solutions
Expert support and Q&Aforum
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)
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