Exploratory Data Analysis with AI 🔍📊

In this notebook, you’ll transform raw data into insights in three easy steps:

1. Load your dataset
2. Analyze with automated EDA
3. Discover deeper insights via AI chat

We will use skrub package for automated exploratory data analysis. If the package is not available in your system, don't worry it will be installed.

Step 1 – Load Your Dataset 📥

Choose how you’d like to bring your data into the notebook:

• Recipe: Read Excel — Click to use Code Recipe with UI for Excel file reading.
• AI Read File — Let the AI automatically detect data type and load your file into a pandas DataFrame called `df`.

After loading, you’ll see the first few rows to make sure everything looks good.

print('🍰 Recipe: Read Excel   or   🤖 AI Read File')

Step 2 – Automated EDA ⚙️

Run a one-click EDA report to:

• View summary statistics (mean, median, quartiles)
• Visualize distributions and correlations
• Detect missing values and outliers

Just the button below, wait a second and explore the interactive report!

print('🍰 Recipe: Exploratory data analysis')

Step 3 – Ask AI About Your Data 💬

Click the button below to use a ready prompt: What are the key insights from this dataset? or type your question in the chat on the left. The AI will provide the code and execute it to get insights.

print('🤖 Ask AI: What are the key insights from this dataset?')

Next steps

Feel free to use AI and ask more questions. You can ask AI to create visualization of data as well.

Good luck with data exploration! :)