Parameters

bar-demo.py

@@ -1,29 +1,71 @@
+# /// script
+# requires-python = ">=3.11"
+# dependencies = [
+#     "altair==5.5.0",
+#     "marimo",
+#     "numpy==2.1.3",
+#     "pandas==2.2.3",
+#     "drawdata==0.3.6",
+# ]
+# ///
+
 import marimo
 
-__generated_with = "0.9.17"
+__generated_with = "0.9.18"
 app = marimo.App(width="medium")
 
 
+@app.cell(hide_code=True)
+def __(mo, widget):
+    mo.md(f"""## BarWidget demo 
+
+    Let's say that you've got a house with solar panels. During some parts of the day you may use more or less energy and the sun might not be shining. You can draw this out on the barwidget shown below. 
+
+    {widget}
+
+    As you update the bar widget the chart below will update. It shows you what the effect of a home battery might be if the day that you drew were to repeat itself. 
+    """)
+    return
+
+
 @app.cell
-def __():
-    import marimo as mo
-    from drawdata import BarWidget
-    return BarWidget, mo
+def __(out):
+    out
+    return
 
 
 @app.cell
 def __(BarWidget, mo):
-    widget = mo.ui.anywidget(BarWidget(height=400, width=700, n_bins=24))
-    widget
+    widget = mo.ui.anywidget(BarWidget(height=200, width=700, n_bins=24, collection_names=["usage", "sunshine"]))
     return (widget,)
 
 
+@app.cell(hide_code=True)
+def __(pltr):
+    import altair as alt
+
+    p1 = alt.Chart(pltr).mark_line(color="red", interpolate="step-after").encode(x="bin", y="cs")
+    p2 = alt.Chart(pltr).mark_area(interpolate="step-after").encode(x="bin", y="battery")
+
+    total = pltr["battery"].sum()
+
+    out = (p2 + p1).properties(width=700, title=f"Max battery cap: {pltr['battery'].max(): .2f} kWh, total: {total :.2f} kWh")
+    return alt, out, p1, p2, total
+
+
+@app.cell
+def __():
+    import marimo as mo
+    from drawdata import BarWidget
+    return BarWidget, mo
+
+
 @app.cell(hide_code=True)
 def __(widget):
     import numpy as np
 
     df = widget.data_as_pandas
-    subset = df.loc[lambda d: d["collection"].isin(["collection3", "collection1"])]
+    subset = df.loc[lambda d: d["collection"].isin(["usage", "sunshine"])]
     return df, np, subset
 
 
@@ -42,35 +84,20 @@ def add_stats(dfin):
         return (
             dfin
             .pivot(columns="collection", index="bin", values="value")
-            .assign(balance=lambda d: d["collection3"] - d["collection1"])
+            .assign(balance=lambda d: d["sunshine"] - d["usage"])
             .assign(cs=lambda d: d["balance"].cumsum())
+            .assign(cs=lambda d: np.where(d["cs"] > 5, 5, d["cs"]))
             .assign(battery=lambda d: np.where(d["cs"] > 0, d["cs"], 0))
             .reset_index()
     )
 
-        
+
     pltr = subset.pipe(concat_days).sort_values(["collection", "bin"]).pipe(add_stats)
     return add_stats, concat_days, pd, pltr
 
 
-@app.cell(hide_code=True)
-def __(pltr):
-    import altair as alt
-
-    p1 = alt.Chart(pltr).mark_line(color="red", interpolate="step-after").encode(x="bin", y="cs")
-    p2 = alt.Chart(pltr).mark_area(interpolate="step-after").encode(x="bin", y="battery")
-
-    total = pltr["battery"].sum()
-
-    (p2 + p1).properties(width=700, title=f"Max battery cap: {pltr['battery'].max(): .2f} kWh, total: {total :.2f} kWh")
-    return alt, p1, p2, total
-
-
 @app.cell
 def __():
-
-
-
     return
 
 

drawdata/__init__.py

@@ -63,6 +63,21 @@ class BarWidget(anywidget.AnyWidget):
     """
     A bar drawing widget that automatically can update a pandas/polars dataframe
     as your draw data.
+
+    Parameters
+    ----------
+    y_min : float
+        The minimum y value to display.
+    y_max : float
+        The maximum y value to display.
+    n_bins : int
+        The number of bins to display.
+    width : int
+        The width of the widget.
+    height : int
+        The height of the widget.
+    collection_names : list of str
+        The names of the collections to draw.
     """
     _esm = Path(__file__).parent / 'static' / 'bar_widget.js'
     _css = Path(__file__).parent / 'static' / 'bar_widget.css'
@@ -73,6 +88,10 @@ class BarWidget(anywidget.AnyWidget):
     width = traitlets.Int(800).tag(sync=True)
     height = traitlets.Int(550).tag(sync=True)
     collection_names = traitlets.List(["collection1", "collection2"]).tag(sync=True)
+
+    def __init__(self, y_min=0.0, y_max=1.0, n_bins=24, width=800, height=550, collection_names=["collection1", "collection2"]):
+        super().__init__(y_min=y_min, y_max=y_max, n_bins=n_bins, width=width, height=height, collection_names=collection_names)
+
     @property
     def data_as_pandas(self):
         import pandas as pd 

scatter-demo.py

@@ -1,7 +1,18 @@
+# /// script
+# requires-python = ">=3.11"
+# dependencies = [
+#     "altair==5.5.0",
+#     "marimo",
+#     "numpy==2.1.3",
+#     "pandas==2.2.3",
+#     "drawdata==0.3.6",
+# ]
+# ///
+
 import marimo
 
-__generated_with = "0.9.17"
-app = marimo.App(width="medium", layout_file="layouts/demo.grid.json")
+__generated_with = "0.9.18"
+app = marimo.App(width="medium")
 
 
 @app.cell
@@ -30,6 +41,12 @@ def __(ScatterWidget, mo):
     return (widget,)
 
 
+@app.cell
+def __(widget):
+    widget.data_as_pandas
+    return
+
+
 @app.cell(hide_code=True)
 def __(widget):
     import altair as alt

setup.py

@@ -12,7 +12,7 @@ def read(fname):
 
 setup(
     name="drawdata",
-    version="0.3.4",
+    version="0.3.6",
     description="draw a dataset from inside Jupyter",
     author="Vincent D. Warmerdam",
     packages=find_packages(exclude=["notebooks"]),