Refactor data processing in pipeline.py to standardize column names for renewable and fossil fuel energy consumption. Update visualizations and report generation to reflect these changes, enhancing clarity and consistency in the analysis.

Author: its-ammu

pipeline.py

@@ -58,12 +58,12 @@ def fetch_world_bank_data():
 def process_data(df):
     """Process and clean the energy data"""
     # Calculate year-over-year changes
-    df['Renewable Growth'] = df.groupby('country')['Renewable energy consumption (% of total final energy consumption)'].pct_change()
+    df['Renewable Growth'] = df.groupby('country')['Renewable energy consumption'].pct_change()
 
     # Calculate energy transition score (higher renewable %, lower fossil fuel %)
     df['Energy Transition Score'] = (
-        df['Renewable energy consumption (% of total final energy consumption)'] -
-        df['Fossil fuel energy consumption (% of total)']
+        df['Renewable energy consumption'] -
+        df['Fossil fuel energy consumption']
     )
 
     # Get latest data for each country
@@ -100,15 +100,16 @@ def create_visualizations(df, latest_data, regional_avg):
     # 1. Energy Transition Progress
     fig_transition = px.scatter(
         latest_data,
-        x='Fossil fuel energy consumption (% of total)',
-        y='Renewable energy consumption (% of total final energy consumption)',
-        size='Energy use per capita (kg of oil equivalent)',
+        x='Fossil fuel energy consumption',
+        y='Renewable energy consumption',
+        size='Energy use per capita',
         color='Region',
         hover_data=['country'],
         title='Energy Transition Progress by Country',
         labels={
-            'Fossil fuel energy consumption (% of total)': 'Fossil Fuel Consumption (%)',
-            'Renewable energy consumption (% of total final energy consumption)': 'Renewable Energy (%)'
+            'Fossil fuel energy consumption': 'Fossil Fuel Consumption (%)',
+            'Renewable energy consumption': 'Renewable Energy (%)',
+            'Energy use per capita': 'Energy Use per Capita (kg of oil equivalent)'
         }
     )
     fig_transition.write_html('output/energy_transition.html')
@@ -117,11 +118,11 @@ def create_visualizations(df, latest_data, regional_avg):
     fig_regional = px.line(
         regional_avg,
         x='date',
-        y='Renewable energy consumption (% of total final energy consumption)',
+        y='Renewable energy consumption',
         color='Region',
         title='Regional Renewable Energy Adoption Trends',
         labels={
-            'Renewable energy consumption (% of total final energy consumption)': 'Renewable Energy (%)',
+            'Renewable energy consumption': 'Renewable Energy (%)',
             'date': 'Year'
         }
     )
@@ -139,11 +140,11 @@ def generate_report(latest_data, transition_file, regional_file):
     Key Statistics:
     --------------
     Total Countries Analyzed: {len(latest_data)}
-    Global Average Renewable Energy Share: {latest_data['Renewable energy consumption (% of total final energy consumption)'].mean():.2f}%
+    Global Average Renewable Energy Share: {latest_data['Renewable energy consumption'].mean():.2f}%
     
     Top 5 Countries by Renewable Energy Share:
     ----------------------------------------
-    {latest_data.nlargest(5, 'Renewable energy consumption (% of total final energy consumption)')[['country', 'Renewable energy consumption (% of total final energy consumption)']].to_string()}
+    {latest_data.nlargest(5, 'Renewable energy consumption')[['country', 'Renewable energy consumption']].to_string()}
     
     Top 5 Countries by Energy Transition Score:
     ----------------------------------------