additional 3g parameters
Browse files- queries/process_wcdma.py +28 -1
queries/process_wcdma.py
CHANGED
|
@@ -38,6 +38,27 @@ WCEL_COLUMNS = [
|
|
| 38 |
"PtxOffset",
|
| 39 |
"PtxTarget",
|
| 40 |
"SmartLTELayeringEnabled",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 41 |
"SectorID",
|
| 42 |
"Code_Sector",
|
| 43 |
"code_wcel",
|
|
@@ -163,7 +184,10 @@ def process_wcdma_data_to_excel(file_path: str):
|
|
| 163 |
############################ANALYTICSS AND STATISTICS############################
|
| 164 |
|
| 165 |
|
| 166 |
-
def wcdma_analaysis(
|
|
|
|
|
|
|
|
|
|
| 167 |
"""
|
| 168 |
Process WCDMA data from the specified file path and convert it to Excel format
|
| 169 |
|
|
@@ -172,6 +196,9 @@ def wcdma_analaysis(filepath: str):
|
|
| 172 |
"""
|
| 173 |
wcdma_df = process_wcdma_data(filepath)
|
| 174 |
|
|
|
|
|
|
|
|
|
|
| 175 |
# df to count number of site per rnc
|
| 176 |
df_site_per_rnc = wcdma_df[["RNC", "code"]]
|
| 177 |
df_site_per_rnc = df_site_per_rnc.drop_duplicates(subset=["code"], keep="first")
|
|
|
|
| 38 |
"PtxOffset",
|
| 39 |
"PtxTarget",
|
| 40 |
"SmartLTELayeringEnabled",
|
| 41 |
+
"HSDPAFmcgIdentifier",
|
| 42 |
+
"NrtFmcgIdentifier",
|
| 43 |
+
"RtFmcgIdentifier",
|
| 44 |
+
"RTWithHSDPAFmcgIdentifier",
|
| 45 |
+
"HSDPAFmciIdentifier",
|
| 46 |
+
"NrtFmciIdentifier",
|
| 47 |
+
"RtFmciIdentifier",
|
| 48 |
+
"RTWithHSDPAFmciIdentifier",
|
| 49 |
+
"HSDPAFmcsIdentifier",
|
| 50 |
+
"HSPAFmcsIdentifier",
|
| 51 |
+
"NrtFmcsIdentifier",
|
| 52 |
+
"RtFmcsIdentifier",
|
| 53 |
+
"RTWithHSDPAFmcsIdentifier",
|
| 54 |
+
"RTWithHSPAFmcsIdentifier",
|
| 55 |
+
"Sintersearch",
|
| 56 |
+
"SintersearchConn",
|
| 57 |
+
"Sintrasearch",
|
| 58 |
+
"SintrasearchConn",
|
| 59 |
+
"Ssearch_RATConn",
|
| 60 |
+
"TreselectionFACH",
|
| 61 |
+
"TreselectionPCH",
|
| 62 |
"SectorID",
|
| 63 |
"Code_Sector",
|
| 64 |
"code_wcel",
|
|
|
|
| 184 |
############################ANALYTICSS AND STATISTICS############################
|
| 185 |
|
| 186 |
|
| 187 |
+
def wcdma_analaysis(
|
| 188 |
+
filepath: str,
|
| 189 |
+
# region_list: list
|
| 190 |
+
):
|
| 191 |
"""
|
| 192 |
Process WCDMA data from the specified file path and convert it to Excel format
|
| 193 |
|
|
|
|
| 196 |
"""
|
| 197 |
wcdma_df = process_wcdma_data(filepath)
|
| 198 |
|
| 199 |
+
# filter per list of regions
|
| 200 |
+
# wcdma_df = wcdma_df.loc[wcdma_df["Region"].isin(region_list)]
|
| 201 |
+
|
| 202 |
# df to count number of site per rnc
|
| 203 |
df_site_per_rnc = wcdma_df[["RNC", "code"]]
|
| 204 |
df_site_per_rnc = df_site_per_rnc.drop_duplicates(subset=["code"], keep="first")
|