NumPy, Pandas, & Python for Data Analysis: A Complete Guide
Learn Data Analysis Techniques with Python, NumPy, and Pandas: From Data Cleaning to Advanced Visualization
What you'll learn:
Introduction to Jupyter Notebook Basic Python programming concepts Installing NumPy & Pandas Creating NumPy arrays from Python lists Mathematical functions in NumPy Reading and writing files with NumPy Creating and understanding DataFrames DataFrame indexing and selection Adding, removing, and updating data Data filtering, sorting, and grouping Time series analysis and manipulation Identifying and handling missing data Merging, joining, and concatenating DataFrames Applying functions to DataFrames Customizing plots (titles, labels, colors) Creating complex visualizations (histograms, scatter plots, box plots) Memory optimization techniques
Description:
Unlock the full potential of data analysis with NumPy, Pandas, and Python in this comprehensive, hands-on course! Whether you're a beginner or looking to sharpen your skills, this course will guide you through everything you need to master data analysis using Python's most powerful libraries.
You will learn to:
Python for Data Analysis: Master the fundamentals of Python, the most popular language for data science, including core programming concepts and essential libraries.
NumPy Essentials: Dive deep into NumPy for fast numerical computations, array manipulation, and performance optimization.
Pandas Mastery: Learn how to efficiently work with large datasets using Pandas, the powerful data manipulation library. Handle, clean, transform, and analyze real-world data with ease.
Data Visualization: Understand how to represent your data visually to gain insights using Python libraries like Matplotlib and Seaborn.
Real-World Projects: Apply your knowledge to real-world datasets, tackling data challenges from start to finish—exploring, cleaning, and drawing insights.
What you'll learn:
Fundamentals of Python programming for data analysis
Introduction to NumPy: Arrays, operations, and performance techniques
Deep dive into Pandas: DataFrames, Series, and advanced data manipulation
Data cleaning and preprocessing techniques
Exploratory data analysis (EDA) with Pandas
Real-world case studies and hands-on projects
Enroll today and take the first step toward mastering data analysis with Python, NumPy, and Pandas!
Requirement:
No prior knowledge is required.