Create visualizations.py

visualizations.py

@@ -0,0 +1,35 @@
+import plotly.express as px
+import pandas as pd
+
+def generate_notifying_map(df: pd.DataFrame):
+    # Carte des pays notifiants
+    return px.choropleth(
+        df.groupby('notification_from').size().reset_index(name='count'),
+        locations='notification_from',
+        locationmode='country names',
+        color='count',
+        scope="europe",
+        title="European Map of Notifying Countries",
+        color_continuous_scale='Blues'
+    )
+
+def generate_origin_map(df: pd.DataFrame):
+    # Carte des pays d'origine
+    return px.choropleth(
+        df.groupby('country_origin').size().reset_index(name='count'),
+        locations='country_origin',
+        locationmode='country names',
+        color='count',
+        title="World Map of Origin Countries",
+        color_continuous_scale='Reds'
+    )
+
+def generate_product_bar(df: pd.DataFrame):
+    # Graphique à barres pour les catégories de produits
+    product_counts = df['prodcat'].value_counts().head(10)
+    return px.bar(product_counts, x=product_counts.index, y=product_counts.values, title="Top Product Categories")
+
+def generate_hazard_pie(df: pd.DataFrame):
+    # Graphique en camembert pour les catégories de dangers
+    hazard_counts = df['hazcat'].value_counts().head(10)
+    return px.pie(hazard_counts, values=hazard_counts.values, names=hazard_counts.index, title="Top 10 Hazard Categories")