Which Python Library is Best? Automate Your Exploratory Data Analysis!

🚀 Speed up your Exploratory Data Analysis (EDA) with these 3 Python libraries! In this video, we compare pandas-profiling, sweetviz, and dataprep to see which one saves you the most time.

🔗 Get the code & benchmarks here: [GitHub Link]
📌 Bookmark this for your next data science project!

📌 **Libraries Covered:**
✔ pandas-profiling (now ydata-profiling) – Automated EDA reports
✔ sweetviz – One-line visualization for datasets
✔ dataprep – Fast profiling for large datasets

💡 **Use Cases:**
- Quick data exploration before machine learning
- Automating EDA for faster insights
- Comparing datasets (train vs test)

0:00 Intro
0:25 Setup
0:40 Pandas-Profiling
0:52 Sweetviz
1:03 DataPrep
1:15 Benchmark Results
1:40 Sweetviz Report Demo
2:20 DataPrep Report Demo

📂 **Resources:**
- Code & benchmarks: [GitHub Link]
- pandas-profiling docs: [Link]
- sweetviz tutorial: [Link]
- dataprep documentation: [Link]

📚 **Related Videos:**
- "5 Must-Know Python Libraries for Data Science"
- "How to Clean Data 10x Faster with Python"

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💬 **Which library do you prefer? Comment below!**