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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 & PandasIntroduce NumPy and Pandas, two critical Python libraries that help structure data in arrays & DataFrames and contain built-in functions for data analysisPandas SeriesIntroduce Pandas Series, the Python equivalent of a column of data, and cover their basic properties, creation, manipulation, and useful functions for analysisIntro to DataFramesWork with Pandas DataFrames, the Python equivalent of an Excel or SQL table, and use them to store, manipulate, and analyze data efficientlyManipulating Python DataFramesAggregate & reshape data in DataFrames by grouping columns, performing aggregation calculations, and pivoting & unpivoting dataBasic Python Data VisualizationLearn the basics of data visualization in Pandas, and use the plot method to create & customize line charts, bar charts, scatterplots, and histogramsMID-COURSE PROJECTPut 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 MegaMartAnalyzing Dates & TimesLearn how to work with the datetime data type in Pandas to extract date components, group by dates, and perform time intelligence calculations like moving averagesImporting & Exporting DataRead in data from flat files and apply processing steps during import, create DataFrames by querying SQL tables, and write data back out to its sourceJoining Python DataFramesCombine multiple DataFrames by joining data from related fields to add new columns, and appending data with the same fields to add new rowsFINAL COURSE PROJECTPut the finishing touches on your project by joining a new table, performing time series analysis, optimizing your workflow, and writing out your resultsJoin today and get immediate, lifetime access to the following:13+ hours of high-quality videoPython NumPy & Pandas PDF ebook (350+ pages)Downloadable project files & solutionsExpert support and Q & A forum30-day Udemy satisfaction guaranteeIf 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:"Some of the BEST courses I've ever taken. I've studied several programming languages, Excel, VBA and web dev, and Maven is among the very best I've seen!" Russ C."This is my fourth course from Maven Analytics and my fourth 5-star review, so I'm running out of things to say. I wish Maven was in my life earlier!" Tatsiana M."Maven Analytics should become the new standard for all courses taught on Udemy!" Jonah M.

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