convert code to int and replace empty to 0 code

queries/process_lte.py

@@ -31,6 +31,40 @@ LNCEL_COLUMNS = [
 ]
 
 
+LNCEL_MOBILITY_COLUMNS = [
+    "ID_LNBTS",
+    "ID_LNCEL",
+    "MRBTS",
+    "LNBTS",
+    "LNCEL",
+    "final_name",
+    "name",
+    "cellName",
+    "code",
+    "SectorId",
+    "Code_Sector",
+    "administrativeState",
+    "lcrId",
+    "band",
+    "band_type",
+    "a3Offset",
+    "enableBetterCellHo",
+    "enableCovHo",
+    "threshold3",
+    "threshold3a",
+    "threshold4",
+    "threshold2InterFreq",
+    "threshold2Wcdma",
+    "threshold2a",
+    "threshold1",
+    "hysThreshold2InterFreq",
+    "hysThreshold2Wcdma",
+    "hysThreshold2a",
+    "hysThreshold3",
+    "hysThreshold4",
+]
+
+
 LNCEL_FDD_COLUMNS = [
     "ID_LNCEL",
     "dlChBw",
@@ -54,7 +88,7 @@ LNCEL_TDD_COLUMNS = [
 ]
 
 
-def process_lte_data(file_path: str):
+def process_lncel(file_path: str):
     """
     Process data from the specified file path.
 
@@ -64,7 +98,7 @@ def process_lte_data(file_path: str):
     # Read excel sheets into dataframes
     dfs = pd.read_excel(
         file_path,
-        sheet_name=["LNCEL", "LNBTS", "LNCEL_FDD", "LNCEL_TDD"],
+        sheet_name=["LNCEL"],
         engine="calamine",
         skiprows=[0],
     )
@@ -74,6 +108,9 @@ def process_lte_data(file_path: str):
     df_lncel.columns = df_lncel.columns.str.replace(r"[ ]", "", regex=True)
     df_lncel["final_name"] = df_lncel["name"].fillna(df_lncel["cellName"])
     df_lncel["code"] = df_lncel["final_name"].str.split("_").str[0]
+    df_lncel["code"] = (
+        pd.to_numeric(df_lncel["code"], errors="coerce").fillna(0).astype(int)
+    )
     df_lncel["SectorId"] = (
         df_lncel["lcrId"].map(UtilsVars.sector_mapping).fillna(df_lncel["lcrId"])
     )
@@ -93,6 +130,27 @@ def process_lte_data(file_path: str):
     df_lncel["Region"] = df_lncel["final_name"].str.split("_").str[1]
     df_lncel["band"] = df_lncel["final_name"].apply(get_band)
     df_lncel["band_type"] = np.where(df_lncel["band"] == "L2300", "TDD", "FDD")
+
+    return df_lncel
+
+
+def process_lte_data(file_path: str):
+    """
+    Process data from the specified file path.
+
+    Args:
+        file_path (str): The path to the file.
+    """
+    # Read excel sheets into dataframes
+    dfs = pd.read_excel(
+        file_path,
+        sheet_name=["LNBTS", "LNCEL_FDD", "LNCEL_TDD"],
+        engine="calamine",
+        skiprows=[0],
+    )
+
+    # Get LNCEL data
+    df_lncel = process_lncel(file_path)
     df_lncel = df_lncel[LNCEL_COLUMNS]
 
     # create band dataframe