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Data Analysis with NumPy and Pandas

  • Course Code: Data Analysis / BI - Data Analysis with NumPy and Pandas
  • Course Dates: Contact us to schedule.
  • Course Category: Big Data & Data Science Duration: 2 Days Audience: This course is geared for Python experienced developers, analysts or others who wants to Get to grips with the most popular Python packages that make Data Analysis possible.

Course Snapshot 

  • Duration: 2 days 
  • Skill-level: Foundation-level Data Analysis with NumPy and Pandas skills for Intermediate skilled team members. This is not a basic class. 
  • Targeted Audience: This course is geared for Python experienced developers, analysts or others who wants to Get to grips with the most popular Python packages that make Data Analysis possible.  
  • Hands-on Learning: This course is approximately 50% hands-on lab to 50% lecture ratio, combining engaging lecture, demos, group activities and discussions with machine-based student labs and exercises. Student machines are required. 
  • Delivery Format: This course is available for onsite private classroom presentation, or remote instructor led delivery, or CBT/WBT (by request). 
  • Customizable: This course may be tailored to target your specific training skills objectives, tools of choice and learning goals. 

Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning. Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python’s NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python’s pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this course, you will have learned to index and group your data for sophisticated data analysis and manipulation. 

Working in a hands-on learning environment, led by our Data Analysis with NumPy and Pandas expert instructor, students will learn about and explore: 

  • Explore the tools you need to become a data analyst 
  • Discover practical examples to help you grasp data processing concepts 
  • Walk through hierarchical indexing and grouping for data analysis 

Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below 

  • Understand how to install and manage Anaconda 
  • Read, sort, and map data using NumPy and pandas 
  • Find out how to create and slice data arrays using NumPy 
  • Discover how to subset your DataFrames using pandas 
  • Handle missing data in a pandas DataFrame 
  • Explore hierarchical indexing and plotting with pandas 

Audience & Pre-Requisites 

This course is geared for attendees with Python skills who wish to get to grips with the most popular Python packages that make Data Analysis possible 

Pre-Requisites:  Students should have  

  • developers with some knowledge of Python.  

Course Agenda / Topics 

  1. Setting Up a Python Data Analysis Environment 
  • Setting Up a Python Data Analysis Environment 
  • What is Anaconda? 
  • Installing Anaconda 
  • Exploring Jupyter Notebooks 
  • Exploring alternatives to Jupyter 
  • Package management with Conda 
  • Setting up a database 
  1. Diving into NumPY 
  • Diving into NumPY 
  • NumPy arrays 
  • Special numeric values 
  • Creating NumPy arrays 
  1. Operations on NumPy Arrays 
  • Operations on NumPy Arrays 
  • Selecting elements explicitly 
  • Advanced indexing 
  • Expanding arrays 
  • Arithmetic and linear algebra with arrays 
  • Linear algebra 
  • Employing array methods and functions 
  1. pandas are Fun! What is pandas? 
  • pandas are Fun! What is pandas? 
  • What does pandas do? 
  • Exploring series and DataFrame objects 
  • Subsetting your data 
  • Indexing methods 
  1. Arithmetic, Function Application, and Mapping with pandas 
  • Arithmetic, Function Application, and Mapping with pandas 
  • Arithmetic 
  • Handling missing data in a pandas DataFrame 
  1. Managing, Indexing, and Plotting 
  • Managing, Indexing, and Plotting 
  • Index sorting 
  • Hierarchical indexing 
  • Plotting with pandas 
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