additional 3g parameters

queries/process_wcdma.py

@@ -38,6 +38,27 @@ WCEL_COLUMNS = [
     "PtxOffset",
     "PtxTarget",
     "SmartLTELayeringEnabled",
+    "HSDPAFmcgIdentifier",
+    "NrtFmcgIdentifier",
+    "RtFmcgIdentifier",
+    "RTWithHSDPAFmcgIdentifier",
+    "HSDPAFmciIdentifier",
+    "NrtFmciIdentifier",
+    "RtFmciIdentifier",
+    "RTWithHSDPAFmciIdentifier",
+    "HSDPAFmcsIdentifier",
+    "HSPAFmcsIdentifier",
+    "NrtFmcsIdentifier",
+    "RtFmcsIdentifier",
+    "RTWithHSDPAFmcsIdentifier",
+    "RTWithHSPAFmcsIdentifier",
+    "Sintersearch",
+    "SintersearchConn",
+    "Sintrasearch",
+    "SintrasearchConn",
+    "Ssearch_RATConn",
+    "TreselectionFACH",
+    "TreselectionPCH",
     "SectorID",
     "Code_Sector",
     "code_wcel",
@@ -163,7 +184,10 @@ def process_wcdma_data_to_excel(file_path: str):
 ############################ANALYTICSS AND STATISTICS############################
 
 
-def wcdma_analaysis(filepath: str):
+def wcdma_analaysis(
+    filepath: str,
+    # region_list: list
+):
     """
     Process WCDMA data from the specified file path and convert it to Excel format
 
@@ -172,6 +196,9 @@ def wcdma_analaysis(filepath: str):
     """
     wcdma_df = process_wcdma_data(filepath)
 
+    # filter per list of regions
+    # wcdma_df = wcdma_df.loc[wcdma_df["Region"].isin(region_list)]
+
     # df to count number of site per rnc
     df_site_per_rnc = wcdma_df[["RNC", "code"]]
     df_site_per_rnc = df_site_per_rnc.drop_duplicates(subset=["code"], keep="first")