UP my solution

pandas_questions.py

@@ -15,9 +15,9 @@
 
 def load_data():
     """Load data from the CSV files referundum/regions/departments."""
-    referendum = pd.DataFrame({})
-    regions = pd.DataFrame({})
-    departments = pd.DataFrame({})
+    referendum = pd.read_csv("data/referendum.csv", sep=";")
+    regions = pd.read_csv("data/regions.csv", sep=",")
+    departments = pd.read_csv("data/departments.csv", sep=",")
 
     return referendum, regions, departments
 
@@ -28,18 +28,37 @@ def merge_regions_and_departments(regions, departments):
     The columns in the final DataFrame should be:
     ['code_reg', 'name_reg', 'code_dep', 'name_dep']
     """
+    merged_df = pd.merge(
+        departments,
+        regions,
+        left_on='region_code',
+        right_on='code',
+        suffixes=('_dep', '_reg')
+    )
+    result = merged_df[['code_reg', 'name_reg', 'code_dep', 'name_dep']]
 
-    return pd.DataFrame({})
+    return result
 
 
 def merge_referendum_and_areas(referendum, regions_and_departments):
     """Merge referendum and regions_and_departments in one DataFrame.
 
     You can drop the lines relative to DOM-TOM-COM departments, and the
-    french living abroad.
+    French living abroad.
     """
+    referendum = referendum[~referendum['Department code'].str.startswith('Z')]
+    referendum.loc[:, 'Department code'] = (
+        referendum['Department code'].astype(str).str.zfill(2)
+    )
 
-    return pd.DataFrame({})
+    merged_df = pd.merge(
+        referendum,
+        regions_and_departments,
+        left_on='Department code',
+        right_on='code_dep'
+    )
+
+    return merged_df
 
 
 def compute_referendum_result_by_regions(referendum_and_areas):
@@ -48,8 +67,16 @@ def compute_referendum_result_by_regions(referendum_and_areas):
     The return DataFrame should be indexed by `code_reg` and have columns:
     ['name_reg', 'Registered', 'Abstentions', 'Null', 'Choice A', 'Choice B']
     """
+    region_results = referendum_and_areas.groupby('code_reg').agg({
+        'name_reg': 'first',
+        'Registered': 'sum',
+        'Abstentions': 'sum',
+        'Null': 'sum',
+        'Choice A': 'sum',
+        'Choice B': 'sum'
+    })
 
-    return pd.DataFrame({})
+    return region_results
 
 
 def plot_referendum_map(referendum_result_by_regions):
@@ -61,8 +88,29 @@ def plot_referendum_map(referendum_result_by_regions):
       should display the rate of 'Choice A' over all expressed ballots.
     * Return a gpd.GeoDataFrame with a column 'ratio' containing the results.
     """
+    gdf = gpd.read_file("data/regions.geojson")
+
+    merged = gdf.merge(
+        referendum_result_by_regions,
+        left_on='code',
+        right_on='code_reg'
+    )
+
+    merged['expressed_ballots'] = (
+        merged['Registered'] - merged['Abstentions'] - merged['Null']
+    )
+    merged['ratio'] = merged['Choice A'] / merged['expressed_ballots']
+
+    merged.plot(
+        column='ratio',
+        cmap='coolwarm',
+        legend=True,
+        figsize=(10, 10),
+        legend_kwds={'label': "Choice A (%)"}
+    )
 
-    return gpd.GeoDataFrame({})
+    plt.title("Referendum Results: Choice A Ratio by Region")
+    return merged
 
 
 if __name__ == "__main__":