Update plot_1_getting_started.py

Author: sylvaincom

examples/plot_1_getting_started.py

@@ -3,7 +3,7 @@
 Getting started with ``skore``
 ==============================
 
-*This example is work in progress!*
+This example builds on top of the :ref:`getting_started` guide.
 
 This guide provides a quick start to ``skore``, an open-source package that aims to enable data scientists to:
 
@@ -36,22 +36,85 @@
 Now that the project file exists, we can load it in our notebook so that we can
 read from and write to it:
 
-.. code-block:: python
-
-    from skore import load
-
-    project = load("project.skore")
-
-Storing some items
-------------------
-
-This will automatically open a browser at the UI's location:
-
-**CONTINUE WORKING HERE**
-
-#. On the top left, create a new ``View``.
-#. From the ``Elements`` section on the bottom left, you can add stored items to this view, either by double-cliking on them or by doing drag-and-drop.
-
-.. image:: https://raw.githubusercontent.com/sylvaincom/sylvaincom.github.io/master/files/probabl/skore/2024_10_14_skore_demo.gif
-   :alt: Getting started with ``skore`` demo
 """
+
+# %%
+# .. code-block:: python
+#
+#     from skore import load
+#
+#     project = load("project.skore")
+
+# %%
+# Storing some items
+# ------------------
+#
+# Storing an integer:
+#
+# .. code-block:: python
+#
+#     project.put("my_int", 3)
+#
+# Here, the name of my stored item is ``my_int`` and the integer value is 3.
+
+# %%
+# For a ``pandas`` data frame:
+
+# %%
+import numpy as np
+import pandas as pd
+
+my_df = pd.DataFrame(np.random.randn(3, 3))
+my_df.head()
+
+# %%
+# .. code-block:: python
+#
+#     project.put("my_df", my_df)
+
+# %%
+# For a ``matplotlib`` figure:
+
+# %%
+import matplotlib.pyplot as plt
+
+x = [0, 1, 2, 3, 4, 5]
+fig, ax = plt.subplots(figsize=(5, 3), layout="constrained")
+_ = ax.plot(x)
+
+# %%
+# .. code-block:: python
+#
+#     project.put("my_figure", fig)
+
+# %%
+# For a ``scikit-learn`` fitted pipeline:
+
+# %%
+from sklearn.datasets import load_diabetes
+from sklearn.linear_model import Lasso
+from sklearn.pipeline import Pipeline
+from sklearn.preprocessing import StandardScaler
+
+diabetes = load_diabetes()
+X = diabetes.data[:150]
+y = diabetes.target[:150]
+my_pipeline = Pipeline(
+    [("standard_scaler", StandardScaler()), ("lasso", Lasso(alpha=2))]
+)
+my_pipeline.fit(X, y)
+
+# %%
+# .. code-block:: python
+#
+#     project.put("my_fitted_pipeline", my_pipeline)
+#
+# Back to the dashboard
+# ---------------------
+#
+# #. On the top left, create a new ``View``.
+# #. From the ``Elements`` section on the bottom left, you can add stored items to this view, either by double-cliking on them or by doing drag-and-drop.
+#
+# .. image:: https://raw.githubusercontent.com/sylvaincom/sylvaincom.github.io/master/files/probabl/skore/2024_10_14_skore_demo.gif
+#    :alt: Getting started with ``skore`` demo
+#