Add post-period total voice and data traffic columns to multi-RAT availability analysis output

apps/kpi_analysis/trafic_analysis.py

@@ -564,8 +564,11 @@ def analyze_multirat_availability(
 
     agg_dict = {col: "mean" for col in rat_cols}
 
-    pre = df[df["period"] == "pre"].groupby("code", as_index=False).agg(agg_dict)
-    post = df[df["period"] == "post"].groupby("code", as_index=False).agg(agg_dict)
+    df_pre = df[df["period"] == "pre"]
+    df_post = df[df["period"] == "post"]
+
+    pre = df_pre.groupby("code", as_index=False).agg(agg_dict)
+    post = df_post.groupby("code", as_index=False).agg(agg_dict)
 
     rename_map_pre = {
         "2g_tch_avail": "2g_avail_pre",
@@ -583,6 +586,25 @@ def analyze_multirat_availability(
 
     multi = pd.merge(pre, post, on="code", how="outer")
 
+    # Add post-period total traffic per site
+    if not df_post.empty and {
+        "total_voice_trafic",
+        "total_data_trafic",
+    }.issubset(df_post.columns):
+        post_traffic = (
+            df_post.groupby("code", as_index=False)[
+                ["total_voice_trafic", "total_data_trafic"]
+            ]
+            .sum()
+            .rename(
+                columns={
+                    "total_voice_trafic": "post_total_voice_trafic",
+                    "total_data_trafic": "post_total_data_trafic",
+                }
+            )
+        )
+        multi = pd.merge(multi, post_traffic, on="code", how="left")
+
     if "City" in df.columns:
         city_df = df[["code", "City"]].drop_duplicates("code")
         multi = pd.merge(multi, city_df, on="code", how="left")
@@ -635,6 +657,8 @@ def analyze_multirat_availability(
         "3g_avail_post",
         "lte_avail_pre",
         "lte_avail_post",
+        "post_total_voice_trafic",
+        "post_total_data_trafic",
         "ok_2g_post",
         "ok_3g_post",
         "ok_lte_post",