Exploratory Data Analysis with Pandas and Python 3.x [Video]

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  • Improve your understanding of descriptive statistics and apply them over a dataset
  • Learn how to deal with missing data and outliers to resolve data inconsistencies
  • Explore various visualization techniques for bivariate and multivariate analysis
  • Enhance your programming skills and master data exploration and visualization in Python
  • Learn multidimensional analysis and reduction techniques
  • Master advanced visualization techniques (such as heatmaps) for better analysis and rapidly broaden your understanding

How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on course shows non-programmers how to process information that’s initially too messy or difficult to access. Through various step-by-step exercises, you’ll learn how to acquire, clean, analyze, and present data efficiently.

This course will take you from Python basics to explore many different types of data. Throughout the course, you will be working with real-world datasets to retrieve insights from data. You'll be exposed to different kinds of data structure and data-related problems. You'll learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more!

All the code files and related files are placed on the GitHub at this link https://github.com/PacktPublishing/Exploratory-Data-Analysis-with-Pandas-and-Python-3.x

  • Build a solid foundation in data analytics and apply it to real-world datasets
  • Each section explores one key measure for exploring a given dataset and includes a case study to reinforce the topics you have learned
  • Master the various data exploration and visualization packages in Python and apply your knowledge to any real-world dataset
Course Length 5 hours 4 minutes
ISBN 9781789959116
Date Of Publication 30 Apr 2019


Mohammed kashif

Mohammed Kashif works as a data scientist at Nineleaps, India, dealing mostly with graph data analysis. Prior to this, he worked as a Python developer at Qualcomm. He completed his Master's degree in computer science at IIIT Delhi, with a specialization in data engineering. His areas of interest include recommender systems, NLP, and graph analytics. In his spare time, he likes to solve questions on StackOverflow and help debug other people out of their misery. He is also an experienced teaching assistant with a demonstrated history of working in the higher-education industry.