Python Data Analysis: NumPy & Pandas Masterclass

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Python Data Analysis: NumPy & Pandas Masterclass

About this course

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 DataFrames

What you'll learn

  • understand NumPy arrays and their properties
  • perform data manipulation and analysis using Pandas
  • apply vectorization and broadcasting concepts
  • create and manage Pandas DataFrames
  • visualize data using charts and graphs
  • work with time-series data
  • import and export different file types

Course objectives

  • equip students with practical skills in data analysis
  • provide hands-on experience through real-world projects
  • develop proficiency in NumPy and Pandas

Skills you'll gain

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