This is the code repository for Exploratory Data Analysis with Pandas and Python 3.x [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
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!
- 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
To fully benefit from the coverage included in this course, you will need:
This course is for Python developers, data analysts, and IT professionals who want to move toward a career as a full-fledged data scientist/analytics expert; anyone who wants to use data analytics/machine learning to enrich their current personal or professional projects will also benefit from it. Basic Python programming experience required.
This course has the following software requirements:
Minimum Hardware Requirements:
For successful completion of this course, students will require the computer systems with at least the following:
OS: Windows 10
Processor: Core i7-7700HQ
Memory: 500 gb
RAM: 16 GB
Software Requirements: Operating system: Windows, Mac or any Linux based OS Browser: Firefox, Chrome, IE, Edge or Safari Python 3.x Jupyter Notebook or any IDE of your choice