[Demo] Add lollipop chart to ViViVo

vizro-core/docs/pages/explanation/authors.md

@@ -46,7 +46,8 @@ Natalia Kurakina,
 [Rosheen C.](https://github.com/rc678),
 [Hilary Ivy](https://github.com/hxe00570),
 [Jasmine Wu](https://github.com/jazwu),
-[njmcgrat](https://github.com/njmcgrat)
+[njmcgrat](https://github.com/njmcgrat),
+[Jenelle Yonkman](https://github.com/yonkmanjl)
 
 with thanks to Sam Bourton and Kevin Staight for sponsorship, inspiration and guidance,
 

vizro-core/examples/scratch_dev/app.py

@@ -1,45 +1,59 @@
 """Dev app to try things out."""
 
 import pandas as pd
+import plotly.graph_objects as go
 import vizro.models as vm
 import vizro.plotly.express as px
 from vizro import Vizro
-from vizro._themes._color_values import COLORS
-
-pastry = pd.DataFrame(
-    {
-        "pastry": [
-            "Scones",
-            "Bagels",
-            "Muffins",
-            "Cakes",
-            "Donuts",
-            "Cookies",
-            "Croissants",
-            "Eclairs",
-            "Brownies",
-            "Tarts",
-            "Macarons",
-            "Pies",
-        ],
-        "Profit Ratio": [-0.10, -0.15, -0.05, 0.10, 0.05, 0.20, 0.15, -0.08, 0.08, -0.12, 0.02, -0.07],
-    }
-)
+from vizro.models.types import capture
+
+
+@capture("graph")
+def lollipop(data_frame: pd.DataFrame, x: str, y: str):
+    """Creates a lollipop chart using Plotly.
+
+    This function generates a scatter chart and then draws lines extending from each point to the x-axis.
+
+    Args:
+        data_frame (pd.DataFrame): The data source for the chart.
+        x (str): The column name to be used for the x-axis.
+        y (str): The column name to be used for the y-axis.
+
+    Returns:
+        go.Figure: : A Plotly Figure object representing the lollipop chart.
+    """
+    fig = go.Figure()
+
+    # Draw points
+    fig.add_trace(
+        go.Scatter(
+            x=data_frame[x],
+            y=data_frame[y],
+            mode="markers",
+            marker=dict(color="#00b4ff", size=12),
+        )
+    )
+
+    for i in range(len(data_frame)):
+        fig.add_trace(
+            go.Scatter(
+                x=[0, data_frame[x].iloc[i]],
+                y=[data_frame[y].iloc[i], data_frame[y].iloc[i]],
+                mode="lines",
+                line=dict(color="#00b4ff", width=3),
+            )
+        )
+    fig.update_layout(showlegend=False)
+    return fig
+
+
+gapminder = px.data.gapminder()
 
 
 page = vm.Page(
-    title="Charts UI",
+    title="Lollipop",
     components=[
-        vm.Graph(
-            figure=px.bar(
-                pastry.sort_values("Profit Ratio"),
-                orientation="h",
-                x="Profit Ratio",
-                y="pastry",
-                color="Profit Ratio",
-                color_continuous_scale=COLORS["DIVERGING_RED_CYAN"],
-            ),
-        ),
+        vm.Graph(figure=lollipop(gapminder.query("year == 2007 and gdpPercap > 36000"), y="country", x="gdpPercap"))
     ],
 )
 

vizro-core/examples/visual-vocabulary/README.md

@@ -70,7 +70,7 @@ The dashboard is still in development. Below is an overview of the chart types f
 | Correlation matrix    | ❌     | Correlation              |                                                                                                                                 |                                                                                                                                                                                                 |
 | Histogram             | ✅     | Distribution             | [Histograms with px](https://plotly.com/python/histograms/)                                                                     | [px.histogram](https://plotly.github.io/plotly.py-docs/generated/plotly.express.histogram)                                                                                                      |
 | Line                  | ✅     | Time                     | [Line plot with px](https://plotly.com/python/line-charts/)                                                                     | [px.line](https://plotly.com/python-api-reference/generated/plotly.express.line)                                                                                                                |
-| Lollipop              | ❌     | Ranking, Magnitude       |                                                                                                                                 |                                                                                                                                                                                                 |
+| Lollipop              | ✅     | Ranking, Magnitude       | [Lollipop & Dumbbell Charts with Plotly](https://towardsdatascience.com/lollipop-dumbbell-charts-with-plotly-696039d5f85)       | [px.scatter](https://plotly.com/python-api-reference/generated/plotly.express.scatter)                                                                                                          |
 | Marimekko             | ❌     | Magnitude, Part-to-whole |                                                                                                                                 |                                                                                                                                                                                                 |
 | Network               | ❌     | Flow                     |                                                                                                                                 |                                                                                                                                                                                                 |
 | Ordered bar           | ✅     | Ranking                  | [Bar chart with px](https://plotly.com/python/bar-charts/)                                                                      | [px.bar](https://plotly.com/python-api-reference/generated/plotly.express.bar.html)                                                                                                             |

vizro-core/examples/visual-vocabulary/chart_groups.py

@@ -81,7 +81,6 @@ class ChartGroup:
     incomplete_pages=[
         IncompletePage("Ordered bubble"),
         IncompletePage("Slope"),
-        IncompletePage("Lollipop"),
         IncompletePage("Bump"),
     ],
     icon="Stacked Bar Chart",
@@ -117,7 +116,6 @@ class ChartGroup:
     pages=pages.magnitude.pages,
     incomplete_pages=[
         IncompletePage("Marimekko"),
-        IncompletePage("Lollipop"),
         IncompletePage("Pictogram"),
         IncompletePage("Bullet"),
         IncompletePage("Radial"),

vizro-core/examples/visual-vocabulary/custom_charts.py

@@ -310,3 +310,45 @@ def diverging_stacked_bar(data_frame: pd.DataFrame, **kwargs) -> go.Figure:
         fig.add_hline(y=0, line_width=2, line_color="grey")
 
     return fig
+
+
+@capture("graph")
+def lollipop(data_frame: pd.DataFrame, **kwargs):
+    """Creates a lollipop based on px.scatter.
+
+    A lollipop chart is a variation of a bar chart where each data point is represented by a line and a dot at the end
+    to mark the value.
+
+    Inspired by: https://community.plotly.com/t/how-to-make-dumbbell-plots-in-plotly-python/47762
+
+    Args:
+        data_frame: DataFrame for the chart. Can be long form or wide form.
+            See https://plotly.com/python/wide-form/.
+        **kwargs: Keyword arguments to pass into px.scatter (e.g. x, y, labels).
+            See https://plotly.com/python-api-reference/generated/plotly.scatter.html.
+
+    Returns:
+        go.Figure: Lollipop chart.
+    """
+    # Unlike the column_and_line chart, where all traces hold equal significance, here the traces differ in importance.
+    # The primary scatter plot is the main trace, while the additional traces merely serve as connecting lines.
+    # Therefore, should we apply the kwargs solely to the main scatter plot, as illustrated below?
+    fig = px.scatter(data_frame, **kwargs)
+
+    # Enable for both orientations
+    orientation = fig.data[0].orientation
+    x_array = fig.data[0]["x"]
+    y_array = fig.data[0]["y"]
+
+    for i in range(len(data_frame)):
+        fig.add_trace(
+            go.Scatter(
+                x=[0, x_array[i]] if orientation == "h" else [x_array[i], x_array[i]],
+                y=[y_array[i], y_array[i]] if orientation == "h" else [0, y_array[i]],
+                mode="lines",
+            )
+        )
+
+    fig.update_traces(marker_size=12, line_width=3, line_color=fig.layout.template.layout.colorway[0])
+    fig.update_layout(showlegend=False, yaxis_title="", yaxis_showgrid=False)
+    return fig

vizro-core/examples/visual-vocabulary/pages/_factories.py

@@ -7,7 +7,7 @@
 import vizro.models as vm
 
 from pages._pages_utils import PAGE_GRID, make_code_clipboard_from_py_file
-from pages.examples import butterfly, column_and_line, connected_scatter, waterfall
+from pages.examples import butterfly, column_and_line, connected_scatter, lollipop, waterfall
 
 
 def butterfly_factory(group: str):
@@ -179,3 +179,48 @@ def waterfall_factory(group: str):
             ),
         ],
     )
+
+
+def lollipop_factory(group: str):
+    """Reusable function to create the page content for the lollipop chart with a unique ID."""
+    return vm.Page(
+        id=f"{group}-lollipop",
+        path=f"{group}/lollipop",
+        title="Lollipop",
+        layout=vm.Layout(grid=PAGE_GRID),
+        components=[
+            vm.Card(
+                text="""
+
+                #### What is a lollipop chart?
+
+                A lollipop chart is a variation of a bar chart where each data point is represented by a line and a
+                dot at the end to mark the value. It functions like a bar chart but offers a cleaner visual,
+                especially useful when dealing with a large number of high values, to avoid the clutter of tall columns.
+                However, it can be less precise due to the difficulty in judging the exact center of the circle.
+
+                 
+
+                #### When should I use it?
+
+                Use a lollipop chart to compare values across categories, especially when dealing with many high values.
+                It highlights differences and trends clearly without the visual bulk of a bar chart. Ensure clarity by
+                limiting categories, using consistent scales, and clearly labeling axes. Consider alternatives if
+                precise value representation is crucial.
+            """
+            ),
+            vm.Graph(figure=lollipop.fig),
+            vm.Tabs(
+                tabs=[
+                    vm.Container(
+                        title="Vizro dashboard",
+                        components=[make_code_clipboard_from_py_file("lollipop.py", mode="vizro")],
+                    ),
+                    vm.Container(
+                        title="Plotly figure",
+                        components=[make_code_clipboard_from_py_file("lollipop.py", mode="plotly")],
+                    ),
+                ]
+            ),
+        ],
+    )

vizro-core/examples/visual-vocabulary/pages/examples/lollipop.py

@@ -0,0 +1,36 @@
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+from vizro.models.types import capture
+
+gapminder = px.data.gapminder()
+
+
+@capture("graph")
+def lollipop(data_frame: pd.DataFrame, **kwargs):
+    """Creates a lollipop chart using Plotly."""
+    fig = px.scatter(data_frame, **kwargs)
+
+    orientation = fig.data[0].orientation
+    x_array = fig.data[0]["x"]
+    y_array = fig.data[0]["y"]
+
+    for i in range(len(data_frame)):
+        fig.add_trace(
+            go.Scatter(
+                x=[0, x_array[i]] if orientation == "h" else [x_array[i], x_array[i]],
+                y=[y_array[i], y_array[i]] if orientation == "h" else [0, y_array[i]],
+                mode="lines",
+            )
+        )
+
+    fig.update_traces(marker_size=12, line_width=3, line_color=fig.layout.template.layout.colorway[0])
+    fig.update_layout(showlegend=False, yaxis_title="", yaxis_showgrid=False)
+    return fig
+
+
+fig = lollipop(
+    data_frame=gapminder.query("year == 2007 and gdpPercap > 36000").sort_values("gdpPercap"),
+    y="country",
+    x="gdpPercap",
+)

vizro-core/examples/visual-vocabulary/pages/magnitude.py

@@ -2,6 +2,7 @@
 
 import vizro.models as vm
 
+from pages._factories import lollipop_factory
 from pages._pages_utils import PAGE_GRID, make_code_clipboard_from_py_file
 from pages.examples import bar, magnitude_column, paired_bar, paired_column, parallel_coordinates, radar
 
@@ -238,4 +239,13 @@
     ],
 )
 
-pages = [bar_page, column_page, paired_bar_page, paired_column_page, parallel_coordinates_page, radar_page]
+lollipop_page = lollipop_factory("magnitude")
+pages = [
+    bar_page,
+    column_page,
+    paired_bar_page,
+    paired_column_page,
+    parallel_coordinates_page,
+    radar_page,
+    lollipop_page,
+]

vizro-core/examples/visual-vocabulary/pages/ranking.py

@@ -2,6 +2,7 @@
 
 import vizro.models as vm
 
+from pages._factories import lollipop_factory
 from pages._pages_utils import PAGE_GRID, make_code_clipboard_from_py_file
 from pages.examples import ordered_bar, ordered_column
 
@@ -85,4 +86,6 @@
 )
 
 
-pages = [ordered_bar_page, ordered_column_page]
+lollipop_page = lollipop_factory("deviation")
+
+pages = [ordered_bar_page, ordered_column_page, lollipop_page]