UP my solution

pandas_questions.py

@@ -14,22 +14,38 @@
 
 
 def load_data():
-    """Load data from the CSV files referundum/regions/departments."""
-    referendum = pd.DataFrame({})
-    regions = pd.DataFrame({})
-    departments = pd.DataFrame({})
+    """Load data from the CSV files referendum/regions/departments."""
+    departments = pd.read_csv("data/departments.csv", delimiter=',')
+    referendum = pd.read_csv("data/referendum.csv", delimiter=';')
+    regions = pd.read_csv("data/regions.csv", delimiter=',')
+
+    departments["region_code"] = departments["region_code"].str.lstrip("0")
+    regions["code"] = regions["code"].str.lstrip("0")
+
+    print("regions shape", regions.shape)
 
     return referendum, regions, departments
 
 
 def merge_regions_and_departments(regions, departments):
-    """Merge regions and departments in one DataFrame.
-
-    The columns in the final DataFrame should be:
-    ['code_reg', 'name_reg', 'code_dep', 'name_dep']
-    """
+    """Merge regions and departments in one DataFrame."""
+    # Remove leading zeros
+
+    merged = departments.merge(
+        regions,
+        left_on="region_code",
+        right_on="code",
+        suffixes=("_dep", "_reg")
+    )
+    merged = merged.rename(columns={
+        "region_code": "code_reg",
+        "name": "name_reg",
+        "code_dep": "code_dep",
+        "name_dep": "name_dep"
+    })
 
-    return pd.DataFrame({})
+    merged = merged.loc[:, ~merged.columns.duplicated()]
+    return merged[["code_reg", "name_reg", "code_dep", "name_dep"]]
 
 
 def merge_referendum_and_areas(referendum, regions_and_departments):
@@ -38,8 +54,28 @@ def merge_referendum_and_areas(referendum, regions_and_departments):
     You can drop the lines relative to DOM-TOM-COM departments, and the
     french living abroad.
     """
-
-    return pd.DataFrame({})
+    regions_and_departments["code_dep"] = regions_and_departments[
+        "code_dep"
+    ].replace({
+        "01": "1",
+        "02": "2",
+        "03": "3",
+        "04": "4",
+        "05": "5",
+        "06": "6",
+        "07": "7",
+        "08": "8",
+        "09": "9"
+    })
+
+    # referendum = referendum[referendum["Department code"].str.isnumeric()]
+    merged = referendum.merge(
+        regions_and_departments,
+        left_on="Department code",
+        right_on="code_dep",
+        how="inner"
+    )
+    return merged
 
 
 def compute_referendum_result_by_regions(referendum_and_areas):
@@ -48,8 +84,16 @@ 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']
     """
+    grouped = referendum_and_areas.groupby(
+        ["code_reg", "name_reg"]
+    ).sum().reset_index()
 
-    return pd.DataFrame({})
+    grouped = grouped.drop(columns=['code_reg'], axis=1)
+    grouped = grouped[
+        ["name_reg", "Registered", "Abstentions",
+            "Null", "Choice A", "Choice B"]
+    ]
+    return grouped
 
 
 def plot_referendum_map(referendum_result_by_regions):
@@ -61,23 +105,39 @@ 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.
     """
+    geo_regions = gpd.read_file("data/regions.geojson")
+    geo_regions = geo_regions.rename(columns={"code": "name_reg"})
+    print(geo_regions.head())
+    print(referendum_result_by_regions.head())
+
+    merged = geo_regions.merge(
+        referendum_result_by_regions,
+        left_on="nom",
+        right_on="name_reg"
+    )
 
-    return gpd.GeoDataFrame({})
+    merged["ratio"] = merged["Choice A"] / (
+        merged["Choice A"] + merged["Choice B"]
+    )
 
+    merged.rename(columns={'nom': 'name_reg'}, inplace=True)
+
+    merged.drop(['name_reg_x'], inplace=True, axis=1)
+
+    merged.plot(column="ratio", legend=True, cmap="coolwarm")
+    return merged
 
-if __name__ == "__main__":
 
+if __name__ == "__main__":
     referendum, df_reg, df_dep = load_data()
-    regions_and_departments = merge_regions_and_departments(
-        df_reg, df_dep
-    )
-    referendum_and_areas = merge_referendum_and_areas(
-        referendum, regions_and_departments
-    )
-    referendum_results = compute_referendum_result_by_regions(
-        referendum_and_areas
-    )
-    print(referendum_results)
+    print("ref shape", referendum.shape)
+    regions_and_departments = merge_regions_and_departments(df_reg, df_dep)
+    print("reg dep shape", regions_and_departments.shape)
+    referendum_and_areas = merge_referendum_and_areas(referendum,
+                                                      regions_and_departments)
+    print("ref and areas ", referendum_and_areas.shape)
+    referendum_results = \
+        compute_referendum_result_by_regions(referendum_and_areas)
 
     plot_referendum_map(referendum_results)
     plt.show()