Overview

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Begin your journey into data analysis by mastering Python fundamentals and the basics of pandas. Learn to set up your environment and build a strong foundation for effective data manipulation. This course introduces you to the essential tools and concepts for data analysis using Python and pandas. You will start by setting up your programming environment and learning core Python skills, including data types, functions, and object-oriented programming. The course then guides you through the basics of pandas, focusing on Series and DataFrame structures, and teaches you how to perform fundamental data selection, cleaning, and transformation tasks. By the end, you will be equipped to handle and prepare data for deeper analysis. Through clear explanations and practical examples, this course guides you step-by-step from environment setup to foundational data manipulation techniques. Each topic builds on the previous, ensuring you develop both confidence and competence in Python and pandas. This course is part one of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Data Analysis with Pandas and Python, by Boris Paskhaver. This course is licensed and distributed by Packt. All rights reserved. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Syllabus

Installation and Setup
- This module provides step-by-step guidance on installing and setting up essential tools for Python development, including terminal navigation, package managers, and Jupyter Lab configurations for both macOS and Windows. Learners will gain hands-on experience with setting up their development environment and configuring tools for efficient coding.
Python Crash Course
- This module covers the fundamental concepts of Python programming, including data types, variables, operators, functions, and data structures. Learners will gain hands-on experience with writing and organizing code, as well as working with built-in and external libraries. The content prepares learners to build structured and efficient Python programs.
Series
- This module provides a comprehensive introduction to pandas Series, covering creation, manipulation, and analysis techniques. Learners will gain hands-on experience with methods for sorting, filtering, and performing mathematical operations on data. The module emphasizes practical skills for working with structured data in Python for data analysis.
DataFrames I: Introduction
- This module provides an in-depth exploration of pandas DataFrames, covering how to manipulate, clean, and structure tabular data. Learners will gain hands-on skills in selecting, modifying, and organizing data using various methods and functions. The focus is on practical techniques for managing real-world datasets efficiently.
DataFrames II: Filtering Data
- This module teaches learners how to filter and manipulate data using pandas in Python. It covers techniques such as boolean indexing, logical operators, and methods like isin, between, and query. Learners will gain practical skills in data cleaning and preprocessing.