Matplotlib Full Course in 2 Hours | Scatter | Bar | Line | Pie | Histogram | Stack | Box Plot

Dataset & Notes : https://consoleflare-1.gitbook.io/dat... Timestamp Introduction to Matplotlib and Installation (0:00-1:05) Overview of Matplotlib Chart Types (1:06-1:37) Simple Line Chart Example (Months & Sales) (1:38-4:46) Introduction to Scatter Plot (4:47-6:14) Creating a Scatter Plot (Months & Sales) (6:15-7:16) Customizing Scatter Plot (Colors, Title, Labels, Grid) (7:17-10:00) Multiple Values in Scatter Plot (iPhone & Samsung Sales) (10:01-13:28) Scatter Plot for Negative Relationship (Temperature & Tea Sales) (13:29-16:05) Scatter Plot for Mixed Relationships (Temperature, Tea & Ice Cream Sales) (16:06-18:27) Scatter Plot with Adidas Sales Dataset (Units Sold & Total) (18:28-24:59) Scatter Plot with Sleep Health & Lifestyle Dataset (Sleep Duration & Quality of Sleep) (25:00-29:11) Scatter Plot for Multiple Y-Values (Sleep Duration, Quality of Sleep & Stress Level) (29:12-31:59) Introduction to Line Chart (32:00-32:45) Creating a Line Chart (Months & iPhone Sales) (32:46-34:18) Multiple Values in Line Chart (iPhone & Samsung Sales) (34:19-35:40) Line Chart with Adidas Sales Dataset (Monthly Sales Trend) (35:41-41:06) Customizing Line Chart (Figure Size, X-axis Ticks, Month Labels) (41:07-45:07) Introduction to Bar Chart and its use for Categorical Data (45:08-47:00) Customizing Bar Chart (Colors, Title, Labels) (47:01-47:32) Creating Multiple Bar Charts (iPhone & Samsung Sales by City) (47:33-49:22) Bar Chart with Adidas Sales Dataset (Sales by Retailer) (49:23-53:11) Horizontal Bar Charts (53:12-55:25) Introduction to Pie Chart (55:26-56:32) Creating a Pie Chart (Gender Distribution) (56:33-58:53) Pie Chart Customization (Explode, Autopct, Shadow, Start Angle) (58:54-1:01:21) Pie Chart with Sleep Health Data (BMI Category Distribution) (1:01:22-1:04:14) Introduction to Histogram (1:04:15-1:05:46) Creating a Histogram (Age Distribution) (1:05:47-1:08:44) Histogram Customization (Bins, Color, Edgecolor) (1:08:45-1:10:04) Histograms for Skewness (Left-Skewed, Right-Skewed, Normal Distribution) (1:10:05-1:15:23) Histogram with Adidas Sales Data (Price Per Unit Distribution) (1:15:24-1:17:41) Histogram with Sleep Health Data (Sleep Duration Distribution) (1:17:42-1:20:00) Introduction to Stack Plot (1:20:01-1:21:40) Creating a Stack Plot (Daily Productivity) (1:21:41-1:24:28) Stack Plot with Adidas Sales Data (Sales Method Contribution) (1:24:29-1:29:43) Introduction to Box Plot (1:29:44-1:32:00) Creating a Box Plot (Sample Data) (1:32:01-1:33:14) Box Plot to Identify Outliers (1:33:15-1:35:46) Box Plot with Sleep Health Data (Sleep Duration by Gender) (1:35:47-1:39:56) Conclusion (1:39:57-1:40:40) Matplotlib Full Tutorial | Data Visualization in Python (Beginner to Advanced) In this video, you’ll learn Matplotlib from scratch and understand how to create powerful data visualizations using real-world datasets. This tutorial is beginner-friendly and also useful for Data Analysts, Data Scientists, and Python learners who want to visualize data properly and extract insights. 🔥 What You’ll Learn in This Video ✅ What is Matplotlib and why it’s used ✅ How to install Matplotlib ✅ Line Charts (Trend analysis over time) ✅ Scatter Plots (Finding relationships & correlations) ✅ Bar Charts (Category comparisons) ✅ Pie Charts (Percentage & contribution analysis) ✅ Histograms (Data distribution & skewness) ✅ Stack Plots (Cumulative trends) ✅ Box Plots (Outliers & spread analysis) 📁 Real-World Datasets Used ✔ Adidas US Sales Dataset ✔ Sleep Health & Lifestyle Dataset ✔ Sales, Temperature vs Demand, Age Distribution examples You’ll learn how to: Identify positive & negative relationships Understand seasonal trends Detect outliers Analyze normal, left-skewed & right-skewed distributions Convert raw data into business insights 🧠 Who Should Watch This? ✔ Data Analyst Aspirants ✔ Data Science Beginners ✔ Python Learners ✔ Working Professionals ✔ Students preparing for interviews ✔ Anyone learning Data Visualization