Streamlit comp updates

.gitignore

@@ -13,3 +13,6 @@
 
 /_inv/
 /objects.json
+
+.venv/
+__pycache__/

docs/apps/comp-streamlit/penguins/app-core.py

@@ -0,0 +1,37 @@
+from pathlib import Path
+
+import pandas as pd
+from palmerpenguins import load_penguins
+from plots import dist_plot, scatter_plot
+from shiny import App, reactive, render, ui
+
+app_ui = ui.page_sidebar(
+    ui.sidebar(
+        ui.input_slider("mass", "Mass", 2000, 8000, 6000),
+        ui.input_checkbox("smoother", "Add Smoother"),
+    ),
+    ui.card(ui.output_plot(id="scatter")),
+    ui.card(ui.output_plot(id="mass_distribution")),
+)
+
+
+def server(input, output, session):
+    df = load_penguins()
+    print(df)
+
+    @reactive.Calc
+    def filtered_data():
+        filt_df = df.copy()
+        filt_df = filt_df.loc[df["body_mass_g"] < input.mass()]
+        return filt_df
+
+    @render.plot
+    def mass_distribution():
+        return dist_plot(filtered_data())
+
+    @render.plot
+    def scatter():
+        return scatter_plot(filtered_data(), input.smoother())
+
+
+app = App(app_ui, server)

docs/apps/comp-streamlit/penguins/app-express.py

@@ -0,0 +1,34 @@
+from pathlib import Path
+
+import pandas as pd
+from palmerpenguins import load_penguins
+from plots import dist_plot, scatter_plot
+from shiny import reactive, render, ui
+from shiny.express import input, ui
+
+df = load_penguins()
+
+with ui.sidebar():
+    ui.input_slider("mass", "Mass", 2000, 8000, 6000)
+    ui.input_checkbox("smoother", "Add Smoother")
+
+
+@reactive.Calc
+def filtered_data():
+    filt_df = df.copy()
+    filt_df = filt_df.loc[df["body_mass_g"] < input.mass()]
+    return filt_df
+
+
+with ui.card():
+
+    @render.plot
+    def scatter():
+        return scatter_plot(filtered_data(), input.smoother())
+
+
+with ui.card():
+
+    @render.plot
+    def mass_distribution():
+        return dist_plot(filtered_data())

docs/apps/comp-streamlit/penguins/plots.py

@@ -0,0 +1,31 @@
+from plotnine import aes, geom_density, geom_point, ggplot, stat_smooth, theme_light
+
+
+def dist_plot(df):
+    plot = (
+        ggplot(df, aes(x="body_mass_g", fill="species"))
+        + geom_density(alpha=0.2)
+        + theme_light()
+    )
+    return plot
+
+
+def scatter_plot(df, smoother):
+    plot = (
+        ggplot(
+            df,
+            aes(
+                x="bill_length_mm",
+                y="bill_depth_mm",
+                color="species",
+                group="species",
+            ),
+        )
+        + geom_point()
+        + theme_light()
+    )
+
+    if smoother:
+        plot = plot + stat_smooth()
+
+    return plot

docs/apps/comp-streamlit/penguins/requirements.txt

@@ -0,0 +1,4 @@
+shiny
+palmerpenguins
+plotnine
+pandas

docs/apps/comp-streamlit/slider-update/app-core.py

@@ -0,0 +1,39 @@
+from pathlib import Path
+
+import pandas as pd
+from palmerpenguins import load_penguins
+from plots import dist_plot, scatter_plot
+from shiny import App, reactive, render, ui
+
+app_ui = ui.page_sidebar(
+    ui.sidebar(
+        ui.input_slider("mass", "Mass", 2000, 8000, 6000),
+        ui.input_checkbox("smoother", "Add Smoother"),
+        ui.input_action_button("reset", "Reset Slider"),
+    ),
+    ui.card(ui.output_plot(id="scatter")),
+    ui.card(ui.output_plot(id="mass_distribution")),
+)
+
+
+def server(input, output, session):
+    df = load_penguins()
+
+    @reactive.calc
+    def filtered_data():
+        filt_df = df.copy()
+        filt_df = filt_df.loc[df["body_mass_g"] < input.mass()]
+        return filt_df
+
+    @output
+    @render.plot
+    def mass_distribution():
+        return dist_plot(filtered_data())
+
+    @output
+    @render.plot
+    def scatter():
+        return scatter_plot(filtered_data(), input.smoother())
+
+
+app = App(app_ui, server)

docs/apps/comp-streamlit/slider-update/app-express.py

@@ -0,0 +1,40 @@
+from pathlib import Path
+
+import pandas as pd
+from palmerpenguins import load_penguins
+from plots import dist_plot, scatter_plot
+from shiny import reactive, render
+from shiny.express import input, ui
+
+df = load_penguins()
+
+with ui.sidebar():
+    ui.input_slider("mass", "Mass", 2000, 8000, 6000)
+    ui.input_checkbox("smoother", "Add Smoother")
+    ui.input_action_button("reset", "Reset Slider")
+
+
+@reactive.effect
+@reactive.event(input.reset)
+def _():
+    ui.update_slider("mass", value=6000)
+
+
+@reactive.calc
+def filtered_data():
+    filt_df = df.copy()
+    filt_df = filt_df.loc[df["body_mass_g"] < input.mass()]
+    return filt_df
+
+
+with ui.card():
+
+    @render.plot
+    def scatter():
+        return scatter_plot(filtered_data(), input.smoother())
+
+
+with ui.card():
+    @render.plot
+    def mass_distribution():
+        return dist_plot(filtered_data())

docs/apps/comp-streamlit/slider-update/plots.py

@@ -0,0 +1,31 @@
+from plotnine import aes, geom_density, geom_point, ggplot, stat_smooth, theme_light
+
+
+def dist_plot(df):
+    plot = (
+        ggplot(df, aes(x="body_mass_g", fill="species"))
+        + geom_density(alpha=0.2)
+        + theme_light()
+    )
+    return plot
+
+
+def scatter_plot(df, smoother):
+    plot = (
+        ggplot(
+            df,
+            aes(
+                x="bill_length_mm",
+                y="bill_depth_mm",
+                color="species",
+                group="species",
+            ),
+        )
+        + geom_point()
+        + theme_light()
+    )
+
+    if smoother:
+        plot = plot + stat_smooth()
+
+    return plot

docs/apps/comp-streamlit/slider-update/requirements.txt

@@ -0,0 +1,4 @@
+shiny
+palmerpenguins
+plotnine
+pandas