Introduction To Numpy And Pandas

Python basics, Data Wrangling with NumPy, Data Analysis with Pandas

What you'll learn

Understand the basics of Python data structures including lists, tuples, dictionaries, and sets

Write Python programs using control flow, functions, and lambda expressions

Create and manipulate NumPy arrays, including indexing, slicing, and broadcasting

Perform mathematical and statistical operations with NumPy

Handle missing or special values in NumPy arrays

Load and explore datasets using Pandas DataFrames

Apply data filtering, sorting, and indexing techniques in Pandas

Perform data aggregation, grouping, and create pivot tables

Clean and manage missing data using Pandas methods

Requirements

Basic understanding of Python syntax (helpful but not mandatory)

A computer with internet access

Google Colab account (free) or Jupyter Notebook setup

Willingness to learn by doing – this course is hands-on and code-focused

Description

Do you want to work with real-world data using Python? Looking to master the most powerful libraries in the Python data ecosystem? You're in the right place.“Introduction to NumPy and Pandas” is a hands-on course designed to get you comfortable with the two most essential libraries in data science and analysis: NumPy and Pandas.This course is beginner-friendly and practical. Whether you're a student, aspiring data analyst, developer, or simply curious about data manipulation, this course will give you a strong foundation through real coding labs—no boring theory, just coding and learning by doing!What’s Inside:Python Fundamentals Refresher: Variables, data types, control flow, functions, and data structures like lists, tuples, sets, and dictionaries.NumPy Deep Dive: Learn how to create and manipulate arrays, perform mathematical operations, broadcasting, and handle missing values.Pandas Essentials: Load data, explore DataFrames, apply filters and indexing, use groupby and pivot tables, and handle missing data like a pro.All Demos in Google Colab: No installations required—just open your browser and start coding.Why This Course?Built for beginners with no prior experience in data librariesFully hands-on, project-oriented learning in Google ColabLearn the core libraries used in Data Science, Machine Learning, and AnalyticsBy the end of this course, you’ll be able to:Confidently use NumPy and Pandas in your data analysis projectsHandle, clean, and transform real datasetsBuild a solid foundation for advanced topics like Machine Learning or Data VisualizationLet’s start your journey into the world of data with Python, NumPy, and Pandas!

Overview

Section 1: Introduction & Setup

Lecture 1 Introduction

Lecture 2 Course Resources

Section 2: Python Basics

Lecture 3 Python Variables, Data Types & Operators

Lecture 4 Control Flow

Lecture 5 Functions & Lambda Expressions

Lecture 6 Working with Lists, Tuples, Sets, and Dictionaries

Section 3: Data Wrangling with NumPy

Lecture 7 NumPy Arrays – Creation, Indexing, Slicing

Lecture 8 Mathematical & Statistical Operations with NumPy

Lecture 9 Broadcasting and Vectorization in NumPy

Lecture 10 Handling Missing or Special Values in NumPy

Section 4: Data Analysis with Pandas

Lecture 11 Loading Data into Pandas

Lecture 12 Exploring DataFrames – head(), info(), describe()

Lecture 13 Filtering, Sorting, and Indexing Data in Pandas

Lecture 14 GroupBy, Aggregations, and Pivot Tables

Lecture 15 Handling Missing Data in Pandas

Beginners who want to get started with data analysis using Python,Students and professionals looking to learn NumPy and Pandas for data manipulation,Aspiring data scientists or analysts who want to build strong foundations in data wrangling,Developers transitioning to data roles who need practical Python skills,Anyone interested in learning how to work with real-world datasets in Python