diff --git a/pkg-py/CHANGELOG.md b/pkg-py/CHANGELOG.md
index 2c33cdf5..6600542b 100644
--- a/pkg-py/CHANGELOG.md
+++ b/pkg-py/CHANGELOG.md
@@ -19,6 +19,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 * The current SQL query and title can now be programmatically set through the `.sql()` and `.title()` methods of `QueryChat()`. (#98, #101)
 
+* New `querychat.data` module provides sample datasets (`titanic()` and `tips()`) to make it easier to get started without external dependencies. (#118)
+
 * Added a `.generate_greeting()` method to help you create a greeting message for your querychat bot. (#87)
 
 * Added `querychat_reset_dashboard()` tool for easily resetting the dashboard filters when asked by the user. (#81)
diff --git a/pkg-py/docs/CHANGELOG.md b/pkg-py/docs/CHANGELOG.md
index 2c33cdf5..6600542b 100644
--- a/pkg-py/docs/CHANGELOG.md
+++ b/pkg-py/docs/CHANGELOG.md
@@ -19,6 +19,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 * The current SQL query and title can now be programmatically set through the `.sql()` and `.title()` methods of `QueryChat()`. (#98, #101)
 
+* New `querychat.data` module provides sample datasets (`titanic()` and `tips()`) to make it easier to get started without external dependencies. (#118)
+
 * Added a `.generate_greeting()` method to help you create a greeting message for your querychat bot. (#87)
 
 * Added `querychat_reset_dashboard()` tool for easily resetting the dashboard filters when asked by the user. (#81)
diff --git a/pkg-py/docs/build.qmd b/pkg-py/docs/build.qmd
index 00c92290..71971b24 100644
--- a/pkg-py/docs/build.qmd
+++ b/pkg-py/docs/build.qmd
@@ -181,14 +181,13 @@ Thanks to Shiny's support for [Jupyter Widgets](https://shiny.posit.co/py/docs/j
 ```python
 import plotly.express as px
 
-from seaborn import load_dataset
 from shiny.express import render, ui
 from shinywidgets import render_plotly
 
 from querychat.express import QueryChat
+from querychat.data import titanic
 
-titanic = load_dataset("titanic")
-qc = QueryChat(titanic, "titanic")
+qc = QueryChat(titanic(), "titanic")
 qc.sidebar()
 
 with ui.layout_columns():
@@ -223,12 +222,11 @@ A more useful, but slightly more involved example like the one below might incor
 from shiny.express import render, ui
 from shinywidgets import render_plotly
 from querychat.express import QueryChat
-from seaborn import load_dataset
+from querychat.data import titanic
 from faicons import icon_svg
 import plotly.express as px
 
-titanic = load_dataset("titanic")
-qc = QueryChat(titanic, "titanic")
+qc = QueryChat(titanic(), "titanic")
 qc.sidebar()
 
 with ui.layout_column_wrap(fill=False):
@@ -356,11 +354,11 @@ You can use multiple QueryChat instances in a single app to explore different da
 from seaborn import load_dataset
 from shiny.express import render, ui
 from querychat.express import QueryChat
+from querychat.data import titanic
 
-titanic = load_dataset("titanic")
 penguins = load_dataset("penguins")
 
-qc_titanic = QueryChat(titanic, "titanic")
+qc_titanic = QueryChat(titanic(), "titanic")
 qc_penguins = QueryChat(penguins, "penguins")
 
 with ui.sidebar():
@@ -396,15 +394,12 @@ Here's a complete example bringing together multiple concepts - a Titanic surviv
 ```python
 from shiny.express import render, ui
 from querychat.express import QueryChat
-from seaborn import load_dataset
+from querychat.data import titanic
 import plotly.express as px
 
-# Load data
-titanic = load_dataset("titanic")
-
 # Create QueryChat
 qc = QueryChat(
-    titanic,
+    titanic(),
     "titanic",
     data_description="Titanic passenger data with survival outcomes",
 )
diff --git a/pkg-py/docs/context.qmd b/pkg-py/docs/context.qmd
index 24156ebf..840a233c 100644
--- a/pkg-py/docs/context.qmd
+++ b/pkg-py/docs/context.qmd
@@ -12,11 +12,9 @@ For full visibility into the full system prompt that Querychat generates for the
 
 ```python
 from querychat import QueryChat
-from seaborn import load_dataset
+from querychat.data import titanic
 
-titanic = load_dataset("titanic")
-
-qc = QueryChat(titanic, "titanic")
+qc = QueryChat(titanic(), "titanic")
 print(qc.system_prompt)
 ```
 
diff --git a/pkg-py/docs/data-sources.qmd b/pkg-py/docs/data-sources.qmd
index 9d040645..5ac97e27 100644
--- a/pkg-py/docs/data-sources.qmd
+++ b/pkg-py/docs/data-sources.qmd
@@ -160,12 +160,10 @@ Or, if you have a pandas DataFrame, you can create the DuckDB database like so:
 ```{.python filename="create-duckdb-from-pandas.py"}
 import duckdb
 import pandas as pd
-
-from seaborn import load_dataset
-titanic = load_dataset("titanic")
+from querychat.data import titanic
 
 conn = duckdb.connect("my_database.duckdb")
-conn.register('titanic_df', titanic)
+conn.register('titanic_df', titanic())
 conn.execute("""
     CREATE TABLE titanic AS
     SELECT * FROM titanic_df
diff --git a/pkg-py/docs/index.qmd b/pkg-py/docs/index.qmd
index 97ba65d8..3a569ddf 100644
--- a/pkg-py/docs/index.qmd
+++ b/pkg-py/docs/index.qmd
@@ -40,11 +40,10 @@ The quickest way to start chatting is to call the `.app()` method, which returns
 
 
 ```{.python filename="titanic-app.py"}
-from seaborn import load_dataset
 from querychat import QueryChat
+from querychat.data import titanic
 
-titanic = load_dataset("titanic")
-qc = QueryChat(titanic, "titanic", client="openai/gpt-4.1")
+qc = QueryChat(titanic(), "titanic", client="openai/gpt-4.1")
 app = qc.app()
 ```
 
diff --git a/pkg-py/docs/models.qmd b/pkg-py/docs/models.qmd
index 3d19e133..83268ebd 100644
--- a/pkg-py/docs/models.qmd
+++ b/pkg-py/docs/models.qmd
@@ -10,11 +10,10 @@ To use a particular model, pass a `"{provider}/{model}"` string to the `client`
 
 ```python
 from querychat import QueryChat
-from seaborn import load_dataset
-titanic = load_dataset("titanic")
+from querychat.data import titanic
 
 qc = QueryChat(
-    titanic,
+    titanic(),
     "titanic",
     client="anthropic/claude-sonnet-4-5"
 )
diff --git a/pkg-py/docs/tools.qmd b/pkg-py/docs/tools.qmd
index cd348eba..c4f68c53 100644
--- a/pkg-py/docs/tools.qmd
+++ b/pkg-py/docs/tools.qmd
@@ -23,10 +23,9 @@ Here's a basic example of this tool in action with the `.app()` method. Notice h
 
 ```{.python filename="titanic-app.py"}
 from querychat import QueryChat
-from seaborn import load_dataset
+from querychat.data import titanic
 
-titanic = load_dataset("titanic")
-qc = QueryChat(titanic, "titanic")
+qc = QueryChat(titanic(), "titanic")
 app = qc.app()
 ```
 
@@ -46,10 +45,9 @@ Here's an example of it in action:
 
 ```{.python filename="titanic-app.py"}
 from querychat import QueryChat
-from seaborn import load_dataset
+from querychat.data import titanic
 
-titanic = load_dataset("titanic")
-qc = QueryChat(titanic, "titanic")
+qc = QueryChat(titanic(), "titanic")
 app = qc.app()
 ```
 
diff --git a/pkg-py/examples/01-hello-app.py b/pkg-py/examples/01-hello-app.py
index 856c93bd..ac109a8f 100644
--- a/pkg-py/examples/01-hello-app.py
+++ b/pkg-py/examples/01-hello-app.py
@@ -1,6 +1,5 @@
-from seaborn import load_dataset
 from querychat import QueryChat
+from querychat.data import titanic
 
-titanic = load_dataset("titanic")
-qc = QueryChat(titanic, "titanic")
+qc = QueryChat(titanic(), "titanic")
 app = qc.app()
diff --git a/pkg-py/examples/02-prompt-app.py b/pkg-py/examples/02-prompt-app.py
index 832059f1..ff738025 100644
--- a/pkg-py/examples/02-prompt-app.py
+++ b/pkg-py/examples/02-prompt-app.py
@@ -1,15 +1,13 @@
 
 from pathlib import Path
-from seaborn import load_dataset
 from querychat import QueryChat
-
-titanic = load_dataset("titanic")
+from querychat.data import titanic
 
 greeting = Path(__file__).parent / "greeting.md"
 data_desc = Path(__file__).parent / "data_description.md"
 
 qc = QueryChat(
-    titanic,
+    titanic(),
     "titanic",
     greeting=greeting,
     data_description=data_desc,
diff --git a/pkg-py/examples/03-sidebar-core-app.py b/pkg-py/examples/03-sidebar-core-app.py
index b37dc750..ef6212e4 100644
--- a/pkg-py/examples/03-sidebar-core-app.py
+++ b/pkg-py/examples/03-sidebar-core-app.py
@@ -1,11 +1,9 @@
-from seaborn import load_dataset
 from shiny import App, render, ui
 from querychat import QueryChat
-
-titanic = load_dataset("titanic")
+from querychat.data import titanic
 
 # 1. Provide data source to QueryChat
-qc = QueryChat(titanic, "titanic")
+qc = QueryChat(titanic(), "titanic")
 
 app_ui = ui.page_sidebar(
     # 2. Create sidebar chat control
diff --git a/pkg-py/examples/03-sidebar-express-app.py b/pkg-py/examples/03-sidebar-express-app.py
index 8e0b7cac..78d8e632 100644
--- a/pkg-py/examples/03-sidebar-express-app.py
+++ b/pkg-py/examples/03-sidebar-express-app.py
@@ -1,11 +1,9 @@
-from seaborn import load_dataset
 from shiny.express import render, ui
 from querychat.express import QueryChat
-
-titanic = load_dataset("titanic")
+from querychat.data import titanic
 
 # 1. Provide data source to QueryChat
-qc = QueryChat(titanic, "titanic")
+qc = QueryChat(titanic(), "titanic")
 
 # 2. Add sidebar chat control
 qc.sidebar()
diff --git a/pkg-py/src/querychat/data/__init__.py b/pkg-py/src/querychat/data/__init__.py
new file mode 100644
index 00000000..fe9bec96
--- /dev/null
+++ b/pkg-py/src/querychat/data/__init__.py
@@ -0,0 +1,68 @@
+"""
+Sample datasets for getting started with querychat.
+
+This module provides easy access to sample datasets that can be used with QueryChat
+to quickly get started without needing to install additional dependencies.
+"""
+
+from __future__ import annotations
+
+from importlib.resources import files
+
+import pandas as pd
+
+
+def titanic() -> pd.DataFrame:
+    """
+    Load the Titanic dataset.
+
+    This dataset contains information about passengers on the Titanic, including
+    whether they survived, their class, age, sex, and other demographic information.
+
+    Returns
+    -------
+    pandas.DataFrame
+        A DataFrame with 891 rows and 15 columns containing Titanic passenger data.
+
+    Examples
+    --------
+    >>> from querychat.data import titanic
+    >>> from querychat import QueryChat
+    >>> df = titanic()
+    >>> qc = QueryChat(df, "titanic")
+    >>> app = qc.app()
+
+    """
+    # Get the path to the gzipped CSV file using importlib.resources
+    data_file = files("querychat.data") / "titanic.csv.gz"
+    return pd.read_csv(str(data_file), compression="gzip")
+
+
+def tips() -> pd.DataFrame:
+    """
+    Load the tips dataset.
+
+    This dataset contains information about restaurant tips, including the total
+    bill, tip amount, and information about the party (sex, smoker status, day,
+    time, and party size).
+
+    Returns
+    -------
+    pandas.DataFrame
+        A DataFrame with 244 rows and 7 columns containing restaurant tip data.
+
+    Examples
+    --------
+    >>> from querychat.data import tips
+    >>> from querychat import QueryChat
+    >>> df = tips()
+    >>> qc = QueryChat(df, "tips")
+    >>> app = qc.app()
+
+    """
+    # Get the path to the gzipped CSV file using importlib.resources
+    data_file = files("querychat.data") / "tips.csv.gz"
+    return pd.read_csv(str(data_file), compression="gzip")
+
+
+__all__ = ["tips", "titanic"]
diff --git a/pkg-py/src/querychat/data/tips.csv.gz b/pkg-py/src/querychat/data/tips.csv.gz
new file mode 100644
index 00000000..4d0d18f3
Binary files /dev/null and b/pkg-py/src/querychat/data/tips.csv.gz differ
diff --git a/pkg-py/src/querychat/data/titanic.csv.gz b/pkg-py/src/querychat/data/titanic.csv.gz
new file mode 100644
index 00000000..30bb696a
Binary files /dev/null and b/pkg-py/src/querychat/data/titanic.csv.gz differ
diff --git a/pkg-py/tests/test_data.py b/pkg-py/tests/test_data.py
new file mode 100644
index 00000000..0ee2f8f8
--- /dev/null
+++ b/pkg-py/tests/test_data.py
@@ -0,0 +1,127 @@
+"""Tests for the querychat.data module."""
+
+import pandas as pd
+from querychat.data import tips, titanic
+
+
+def test_titanic_returns_dataframe():
+    """Test that titanic() returns a pandas DataFrame."""
+    df = titanic()
+    assert isinstance(df, pd.DataFrame)
+
+
+def test_titanic_has_expected_shape():
+    """Test that the Titanic dataset has the expected number of rows and columns."""
+    df = titanic()
+    assert df.shape == (891, 15), f"Expected (891, 15) but got {df.shape}"
+
+
+def test_titanic_has_expected_columns():
+    """Test that the Titanic dataset has the expected column names."""
+    df = titanic()
+    expected_columns = [
+        "survived",
+        "pclass",
+        "sex",
+        "age",
+        "sibsp",
+        "parch",
+        "fare",
+        "embarked",
+        "class",
+        "who",
+        "adult_male",
+        "deck",
+        "embark_town",
+        "alive",
+        "alone",
+    ]
+    assert list(df.columns) == expected_columns
+
+
+def test_titanic_data_integrity():
+    """Test basic data integrity of the Titanic dataset."""
+    df = titanic()
+
+    # Check that survived column has only 0 and 1 values
+    assert set(df["survived"].dropna().unique()) <= {0, 1}
+
+    # Check that pclass has only 1, 2, 3
+    assert set(df["pclass"].dropna().unique()) <= {1, 2, 3}
+
+    # Check that sex has only 'male' and 'female'
+    assert set(df["sex"].dropna().unique()) <= {"male", "female"}
+
+    # Check that fare is non-negative
+    assert (df["fare"].dropna() >= 0).all()
+
+
+def test_titanic_creates_new_copy():
+    """Test that titanic() returns a new copy each time it's called."""
+    df1 = titanic()
+    df2 = titanic()
+
+    # They should not be the same object
+    assert df1 is not df2
+
+    # But they should have the same data
+    assert df1.equals(df2)
+
+
+def test_tips_returns_dataframe():
+    """Test that tips() returns a pandas DataFrame."""
+    df = tips()
+    assert isinstance(df, pd.DataFrame)
+
+
+def test_tips_has_expected_shape():
+    """Test that the tips dataset has the expected number of rows and columns."""
+    df = tips()
+    assert df.shape == (244, 7), f"Expected (244, 7) but got {df.shape}"
+
+
+def test_tips_has_expected_columns():
+    """Test that the tips dataset has the expected column names."""
+    df = tips()
+    expected_columns = [
+        "total_bill",
+        "tip",
+        "sex",
+        "smoker",
+        "day",
+        "time",
+        "size",
+    ]
+    assert list(df.columns) == expected_columns
+
+
+def test_tips_data_integrity():
+    """Test basic data integrity of the tips dataset."""
+    df = tips()
+
+    # Check that total_bill is positive
+    assert (df["total_bill"] > 0).all()
+
+    # Check that tip is non-negative
+    assert (df["tip"] >= 0).all()
+
+    # Check that sex has only expected values
+    assert set(df["sex"].dropna().unique()) <= {"Male", "Female"}
+
+    # Check that smoker has only expected values
+    assert set(df["smoker"].dropna().unique()) <= {"Yes", "No"}
+
+    # Check that size is positive
+    assert (df["size"] > 0).all()
+
+
+def test_tips_creates_new_copy():
+    """Test that tips() returns a new copy each time it's called."""
+    df1 = tips()
+    df2 = tips()
+
+    # They should not be the same object
+    assert df1 is not df2
+
+    # But they should have the same data
+    assert df1.equals(df2)
diff --git a/pkg-py/tests/test_querychat.py b/pkg-py/tests/test_querychat.py
index 893ff824..ebf5ec57 100644
--- a/pkg-py/tests/test_querychat.py
+++ b/pkg-py/tests/test_querychat.py
@@ -60,4 +60,3 @@ def test_querychat_custom_id(sample_df):
     )
 
     assert qc.id == "custom_id"
-