diff --git a/src/figures.py b/src/figures.py
new file mode 100644
index 0000000..51fa3a8
--- /dev/null
+++ b/src/figures.py
@@ -0,0 +1,87 @@
+import json
+
+import plotly.express as px
+import polars as pl
+
+
+def get_map_count_marches(lf):
+    lf = lf.with_columns(
+        pl.col("lieuExecution_code").str.head(2).str.zfill(2).alias("Département")
+    )
+    lf = (
+        lf.unique(subset="uid")
+        .select(["uid", "Département"])
+        .unique(subset="uid")
+        .group_by("Département")
+        .len("uid")
+    )
+    # Suppression des infos pour les DOM/TOM pour l'instant
+    lf = lf.remove(pl.col("Département").is_in(["97", "98"]))
+
+    with open("./data/departements-1000m.geojson") as f:
+        departements = json.load(f)
+
+    # Ajout de feature.id
+    for f in departements["features"]:
+        f["id"] = f["properties"]["code"]
+
+    df = lf.collect()
+
+    fig = px.choropleth(
+        df,
+        geojson=departements,
+        locations="Département",
+        color="uid",
+        color_continuous_scale="Reds",
+        title="Nombres de marchés attribués par département (lieu d'exécution)",
+        range_color=(df["uid"].min(), df["uid"].max()),
+        labels={"uid": "Marchés attribués"},
+        scope="europe",
+        width=1000,
+        height=800,
+    )
+
+    fig.update_geos(fitbounds="locations", visible=False)
+    fig.update_layout(
+        mapbox={
+            "style": "carto-positron",
+            "center": {"lon": 10, "lat": 10},
+            "zoom": 1,
+            "domain": {"x": [0, 1], "y": [0, 1]},
+        }
+    )
+    return fig
+
+
+def get_barchart_sources(lf: pl.LazyFrame, type_date: str):
+    labels = {
+        "dateNotification": "notification",
+        "datePublicationDonnees": "publication des données",
+    }
+
+    lf = lf.select("uid", type_date, "source")
+    lf = lf.unique("uid")
+    lf = lf.with_columns(pl.col(type_date).dt.year().alias("annee"))
+    lf = lf.filter(
+        pl.col(type_date).is_not_null() & pl.col("annee").is_between(2018, 2025)
+    )
+    lf = lf.sort(by=[type_date, "source"], descending=False)
+    lf = lf.with_columns(pl.col(type_date).cast(pl.String).str.head(7))
+
+    lf = lf.group_by([type_date, "source"]).len()
+    lf = lf.sort(by=[type_date, "source"], descending=False)
+    df: pl.DataFrame = lf.collect()
+
+    fig = px.bar(
+        df,
+        x=type_date,
+        y="len",
+        color="source",
+        title=f"Nombre de marchés attribués par date de {labels[type_date]} et source de données",
+        labels={
+            "len": "Nombre de marchés",
+            type_date: f"Mois de {labels[type_date]}",
+            "source": "Source de données",
+        },
+    )
+    return fig