Step-by-Step: Your First Python Program in Jupyter Notebook with Wine Dataset | 5-Minute Analytics

Welcome to our beginner-friendly tutorial on writing your first Python program in Jupyter Notebook! In this video, we will guide you step-by-step through the process of installing Anaconda Navigator, setting up your environment, and exploring the Wine dataset from the scikit-learn package library.

We'll start by showing you how to download and install Anaconda Navigator, a powerful tool that simplifies package management and deployment. Once Anaconda is set up, we'll dive into Jupyter Notebook, where you'll learn the basics of writing Python code.

Next, we'll explore the Wine dataset from the scikit-learn package library. This dataset is perfect for beginners to practice data analysis and machine learning techniques. We'll guide you through loading the dataset, examining its structure, and performing some basic data manipulation and visualization.

Whether you're new to Python or looking to sharpen your data science skills, this tutorial is perfect for you. Follow along and start your Python programming journey today!

Learn Python Programming: Your First Jupyter Notebook & Wine Dataset Exploration | Install Anaconda Navigator

Function: load_wine()
Purpose: Loads the Wine dataset for classification tasks.
Dataset Composition: Contains 178 samples of wine with 13 features, including alcohol, malic acid, and ash.
Target: Three classes of wine (0, 1, 2).
Return Type: Bunch object with attributes: data, target, frame, target_names, DESCR, feature_names, and filename.
Usage: Useful for practicing data analysis, feature selection, and machine learning techniques.

Chapters:
00:09 Installing Anaconda Navigator (a quick guidance)
00:42 Introduction to Jupyter Notebook Environment
05:05 Writing (Creating) Your First Python Program in Jupyter Notebook
07:00 Introduction to Pandas Library (Package)
07:38 Introduction to Numpy Package
08:50 Introduction to Sklearn datasets
09:10 Introducing Wine Dataset from scikit-learn package
10:00 Loading Wine Dataset
10:57 Viewing Wine Dataset
11:40 Access to Features and Labels of Wine Dataset
13:13 Print Features
13:35 Print Class Labels (Targets)

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Produced by: Dr Reza Rafiee; @5MinuteAnalytics
Music by @ClickRhythm  
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