Simplify Your Data Analysis with PandasAI, Matplotlib, Seaborn & Plotly 📊
Learn how to perform effective Exploratory Data Analysis effortlessly using popular Python libraries. Access course resources and datasets to get started today!
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Dataset Link - https://drive.google.com/drive/folders/1ceL5a8yF0wCr66Rl3ATcK39LvHO-9zPg?usp=sharing
Are you ready to take your data analysis skills to the next level? In this comprehensive tutorial, we'll explore the power of Exploratory Data Analysis (EDA) and show you how to master it using a variety of powerful Python libraries. Whether you're a beginner or an experienced data scientist, you'll learn valuable techniques to uncover insights, visualize data, and build better machine learning models.
[0:00] Introduction: The Modern EDA Roadmap
[2:49] Level 1: Traditional EDA with Python
[3:36] Step 1: Loading & Inspecting Data with Pandas
[15:18] Step 2: Feature Engineering for Deeper Insights
[19:03] Step 3: Univariate & Bivariate Analysis (Visualizing Data)
[23:34] Step 4: Uncovering Relationships with Heatmaps & Scatter Plots
[38:01] Level 2: Automated EDA with Sweetviz
[46:49] Level 3: AI-Powered EDA with PandasAI
[47:47] Step 1: Setting Up PandasAI & OpenAI
[51:57] Step 2: Asking Your Data Questions in Plain English
[56:00] Conclusion & Key Takeaways
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