Master EDA in Python with Jupyter Notebook 📊

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*What you’ll learn*
Unlock the full potential of your data with this comprehensive tutorial on Exploratory Data Analysis (EDA) using Python in Jupyter Notebook.

*This step-by-step guide covers*
• Loading and Inspecting Data: Learn how to import datasets and understand their structure.
• Handling Missing Values: Discover techniques to identify and manage incomplete data.
• Univariate Analysis: Explore individual variables to uncover underlying patterns.
• Bivariate Analysis: Examine relationships between two variables for deeper insights.
• Data Visualization: Utilize libraries like Matplotlib and Seaborn to create insightful plots.
• Correlation Analysis: Understand how variables interact with each other.
By the end of this tutorial, you'll be equipped with the skills to perform EDA confidently, setting a strong foundation for any data science project.

*Resources*
• Dataset Used: "https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv

• Anaconda Installation Video to use Jupyter Notebook: https://youtu.be/ImhtTEfQafo

*Continue your learning with Python*
https://learnpython.com/?ref=mgzmzjn

*Get free resources to continue learning: *
https://www.excelcampus.com/161.php

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⏳ *Timestamps* ⏳
00:00 Introduction
00:59 What we will cover in this video
01:27: What is Explanation of Master Exploratory Data Analysis (EDA)
02:18 Step 1: Import libraries & Set visual plot
05:10 Step 2: Load the dataset
06:00 Step 3: Basic Overview of the dataset
07:16 How to view the number of columns and rows using Python
07:28 How to view the datatypes for each variable in the dataset using Python code
07:53 How to view the summary statistics of a numerical variables in the dataset using Python.
09:03 Visualize the missing values
10:52 Step 5: Univariate Analysis
16:16 Create a Countplot for categorical column
19:00 Using a Groupby to compare rates in Python
20:32 Step 6: Bivariate Analysis (Comparing Two Variables with a barchart)
24:06 Bivariate Analysis (Comparing Two Variables with a scatterplot)
28:04 Step 7: Heat Map - Variable Correlation Matrix in Python
31:42 Closing and thank you for watching.

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