Add initial Marimo EDA for LWF datasets

marimo_eda/Individual_LWF_Deposition.py

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+import marimo
+
+__generated_with = "0.24.0"
+app = marimo.App(width="medium")
+
+
+@app.cell
+def _():
+    import pandas as pd
+    import marimo as mo
+    from pathlib import Path
+
+    return Path, mo, pd
+
+
+@app.cell
+def _(Path, pd):
+    foliage_path = Path("lwf_foliage_dw100_i_2026-07-30.csv")
+
+    foliage = pd.read_csv(
+        foliage_path,
+        sep=";",
+    )
+    return (foliage,)
+
+
+@app.cell
+def _(foliage):
+    foliage.head()
+    return
+
+
+@app.cell
+def _(foliage, pd):
+    foliage["survey_date"] = pd.to_datetime(
+        foliage["survey_date"],
+        errors="coerce",
+    )
+    return
+
+
+@app.cell
+def _(foliage, mo):
+    plot_selector = mo.ui.dropdown(
+        options=["All"] + sorted(
+            foliage["plot_id"]
+            .dropna()
+            .unique()
+            .tolist()
+        ),
+        value="All",
+        label="LWF site",
+    )
+
+    species_selector = mo.ui.dropdown(
+        options=["All"] + sorted(
+            foliage["species"]
+            .dropna()
+            .unique()
+            .tolist()
+        ),
+        value="All",
+        label="Species",
+    )
+
+    leaf_type_selector = mo.ui.dropdown(
+        options=["All"] + sorted(
+            foliage["leaf_type"]
+            .dropna()
+            .unique()
+            .tolist()
+        ),
+        value="All",
+        label="Leaf type",
+    )
+
+    age_selector = mo.ui.dropdown(
+        options=["All"] + sorted(
+            foliage["leaf_age_class"]
+            .dropna()
+            .unique()
+            .tolist()
+        ),
+        value="All",
+        label="Leaf age class",
+    )
+
+    mo.vstack([
+        mo.hstack([
+            plot_selector,
+            species_selector,
+        ]),
+        mo.hstack([
+            leaf_type_selector,
+            age_selector,
+        ]),
+    ])
+    return age_selector, leaf_type_selector, plot_selector, species_selector
+
+
+@app.cell
+def _(
+    age_selector,
+    foliage,
+    leaf_type_selector,
+    plot_selector,
+    species_selector,
+):
+    filtered_foliage = foliage.copy()
+
+    if plot_selector.value != "All":
+        filtered_foliage = filtered_foliage[
+            filtered_foliage["plot_id"] == plot_selector.value
+        ]
+
+    if species_selector.value != "All":
+        filtered_foliage = filtered_foliage[
+            filtered_foliage["species"] == species_selector.value
+        ]
+
+    if leaf_type_selector.value != "All":
+        filtered_foliage = filtered_foliage[
+            filtered_foliage["leaf_type"] == leaf_type_selector.value
+        ]
+
+    if age_selector.value != "All":
+        filtered_foliage = filtered_foliage[
+            filtered_foliage["leaf_age_class"] == age_selector.value
+        ]
+
+    filtered_foliage
+    return (filtered_foliage,)
+
+
+@app.cell
+def _(filtered_foliage):
+    filtered_foliage["gew100"].describe()
+    return
+
+
+@app.cell
+def _(filtered_foliage):
+    filtered_foliage["gew100"].isna().sum()
+    return
+
+
+@app.cell
+def _(filtered_foliage):
+    import plotly.graph_objects as go
+
+    plot_data = (
+        filtered_foliage[
+            ["survey_date", "gew100", "sample_id"]
+        ]
+        .dropna(subset=["survey_date", "gew100"])
+        .sort_values("survey_date")
+    )
+
+    fig = go.Figure()
+
+    fig.add_trace(
+        go.Scatter(
+            x=plot_data["survey_date"],
+            y=plot_data["gew100"],
+            mode="markers",
+            name="Individual measurement",
+            marker=dict(size=7),
+            customdata=plot_data["sample_id"],
+            hovertemplate=(
+                "<b>Date:</b> %{x|%d %B %Y}"
+                "<br><b>gew100:</b> %{y:.2f} g"
+                "<br><b>Sample:</b> %{customdata}"
+                "<extra></extra>"
+            ),
+        )
+    )
+
+    fig.update_layout(
+        title="Foliage dry weight over time",
+        xaxis_title="Survey date",
+        yaxis_title="gew100 (g)",
+        hovermode="closest",
+    )
+
+    fig
+    return (go,)
+
+
+@app.cell
+def _(foliage):
+    samples_per_group = (
+        foliage
+        .groupby(
+            [
+                "survey_date",
+                "species",
+                "leaf_type",
+                "leaf_age_class",
+            ],
+            dropna=False,
+        )
+        .agg(
+            n_samples=("sample_id", "nunique"),
+            mean_gew100=("gew100", "mean"),
+            median_gew100=("gew100", "median"),
+            std_gew100=("gew100", "std"),
+        )
+        .reset_index()
+        .sort_values("survey_date")
+    )
+
+    samples_per_group
+    return
+
+
+@app.cell
+def _(go, samples_per_date):
+    fig_1 = go.Figure()
+
+    fig_1.add_trace(
+        go.Bar(
+            x=samples_per_date["survey_date"],
+            y=samples_per_date["n_samples"],
+            hovertemplate=(
+                "<b>Date:</b> %{x|%d %B %Y}"
+                "<br><b>Samples:</b> %{y}"
+                "<extra></extra>"
+            ),
+        )
+    )
+
+    fig_1.update_layout(
+        title="Number of foliage samples per survey date",
+        xaxis_title="Survey date",
+        yaxis_title="Number of individual samples",
+    )
+
+    fig_1
+    return
+
+
+if __name__ == "__main__":
+    app.run()