NumPy, Pandas, & Python for Data Analysis: A Complete Guide

Learn Data Analysis Techniques with Python, NumPy, and Pandas: From Data Cleaning to Advanced Visualization

Learn Data Analysis Techniques with Python, NumPy, and Pandas: From Data Cleaning to Advanced Visualization

Overview

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

Anyone looking to enhance their data analysis skills using Python, Beginners interested in data analysis with Python, Data enthusiasts looking to gain in-demand skills

No prior knowledge is required.

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!

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