homework finished by chems

Author: chemousesi

pandas_questions.py

@@ -15,9 +15,10 @@
 
 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
 
@@ -27,9 +28,15 @@ def merge_regions_and_departments(regions, departments):
 
     The columns in the final DataFrame should be:
     ['code_reg', 'name_reg', 'code_dep', 'name_dep']
-    """
+    """ 
+    # target name code reg 
+
+    merged = departments.merge(regions, left_on='region_code', right_on='code', suffixes=('_dep', '_reg'))
+    result = merged[['code_reg', 'name_reg', 'code_dep', 'name_dep']]
+    result.columns = ['code_reg', 'name_reg', 'code_dep', 'name_dep']
+    
 
-    return pd.DataFrame({})
+    return result
 
 
 def merge_referendum_and_areas(referendum, regions_and_departments):
@@ -38,8 +45,13 @@ 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({})
+    referendum['Department code'] = referendum['Department code'].str.zfill(2)
+    merged_referendum = referendum.merge(
+        regions_and_departments,
+        left_on='Department code',
+        right_on='code_dep'
+    )
+    return merged_referendum
 
 
 def compute_referendum_result_by_regions(referendum_and_areas):
@@ -48,8 +60,10 @@ 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']
     """
-
-    return pd.DataFrame({})
+    print('refrenduma nd areas : ', referendum_and_areas.shape)
+    grouped = referendum_and_areas.groupby(by=['code_reg', 'name_reg']).sum(numeric_only=True).reset_index()
+    result = grouped[['code_reg', 'name_reg', 'Registered', 'Abstentions', 'Null', 'Choice A', 'Choice B']]
+    return result.set_index('code_reg')
 
 
 def plot_referendum_map(referendum_result_by_regions):
@@ -61,8 +75,18 @@ 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_data = gpd.read_file('data/regions.geojson')
+
+    total_votes = referendum_result_by_regions['Choice A']+ referendum_result_by_regions['Choice B']
+    referendum_result_by_regions['ratio'] = referendum_result_by_regions['Choice A']/total_votes
+
+    geo_merged = geo_data.merge(referendum_result_by_regions, left_on='code', right_on='code_reg')
+
+    geo_merged.plot(column='ratio', legend=True, cmap ='coolwarm')
+
 
-    return gpd.GeoDataFrame({})
+    return geo_merged
 
 
 if __name__ == "__main__":
@@ -81,3 +105,4 @@ def plot_referendum_map(referendum_result_by_regions):
 
     plot_referendum_map(referendum_results)
     plt.show()
+    plt.savefig('referendum_result')