packages = ["bokeh", "pandas", "numpy", "networkx", "diagrams", "scikit-learn", "pillow", "matplotlib", "plotly"] [[fetch]] files = ["diagrams_base.py"] from = "../../python/diagrams/" [[fetch]] files = ["pyscript_manager.py", "data.py"] to_folder = "lib" from = "../../python/lib/" [[fetch]] files = ["bokeh_utils.py"] from = "../../python/bokeh/" [[fetch]] files = ["matplotlib_utils.py", "plotly_utils.py"] from = "../../python/matplotlib/" [[fetch]] files = ["agent.py", "trainer.py", "utils.py", "metrics_chart.py", "crossover.py", "__init__.py"] to_folder = "ml/neuro" from = "../../python/ml/neuro/" [[fetch]] files = ["trainer.py"] to_folder = "ml/grokking" from = "../../python/ml/grokking/"

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These interactive charts analyze over 20,000 AirBnb listings...

📊 Correlation Heatmap

Shows how different listing features relate...

Correlation analysis using Pandas and Bokeh:

🥧 Room Type Distribution

A pie chart showing the breakdown...

Room distribution using the SAME cached data:

💰 Price Analysis

Displays how prices vary...

Price distribution with jittered scatter:

🏠 Top Hosts

Bar chart showing the 10 most active hosts...

Top 10 hosts by listing count:

📍 Neighborhood Activity

Lollipop chart displaying listing counts...

Listings by neighborhood group:

Bokeh + Pandas

🐼 What is Pandas?

Pandas is Python's most popular data analysis library...

📊 The Dataset

We're analyzing 20,837 AirBnb listings...

  • Host ID and listing count
  • Neighborhood and borough
  • Room type (entire home, private room, shared)
  • Price per night
  • Number of reviews and review scores
  • Availability throughout the year

🔍 Data Analysis Patterns

Each chart demonstrates common Pandas operations:

  • Correlation: df.corr() finds relationships...
  • Value Counts: df.column.value_counts()...
  • Filtering: df[df.price < 500]...
  • Grouping: df.groupby('room_type').mean()...
  • Sorting: df.sort_values('price')...

💡 Loading Data

The CSV is loaded using Pandas' read_csv()...

🎨 Why Bokeh?

Bokeh excels at creating interactive visualizations...

View source files

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