Add support of Hourly data to trafic_analysis

apps/kpi_analysis/trafic_analysis.py

@@ -49,7 +49,10 @@ def preprocess_2g(df: pd.DataFrame) -> pd.DataFrame:
     df["2g_data_trafic"] = ((df["TRAFFIC_PS DL"] + df["PS_UL_Load"]) / 1000).round(1)
     df.rename(columns={"2G_Carried Traffic": "2g_voice_trafic"}, inplace=True)
     df["code"] = df["BCF name"].apply(extract_code)
-    df["date"] = pd.to_datetime(df["PERIOD_START_TIME"], format="%m.%d.%Y")
+    date_format = (
+        "%m.%d.%Y %H:%M:%S" if len(df["PERIOD_START_TIME"].iat[0]) > 10 else "%m.%d.%Y"
+    )
+    df["date"] = pd.to_datetime(df["PERIOD_START_TIME"], format=date_format)
     df["ID"] = df["date"].astype(str) + "_" + df["code"].astype(str)
     df = df.groupby(["date", "ID", "code"], as_index=False)[
         ["2g_data_trafic", "2g_voice_trafic"]
@@ -60,7 +63,10 @@ def preprocess_2g(df: pd.DataFrame) -> pd.DataFrame:
 def preprocess_3g(df: pd.DataFrame) -> pd.DataFrame:
     df = df[df["WBTS name"].str.len() >= 10].copy()
     df["code"] = df["WBTS name"].apply(extract_code)
-    df["date"] = pd.to_datetime(df["PERIOD_START_TIME"], format="%m.%d.%Y")
+    date_format = (
+        "%m.%d.%Y %H:%M:%S" if len(df["PERIOD_START_TIME"].iat[0]) > 10 else "%m.%d.%Y"
+    )
+    df["date"] = pd.to_datetime(df["PERIOD_START_TIME"], format=date_format)
     df["ID"] = df["date"].astype(str) + "_" + df["code"].astype(str)
     df.rename(
         columns={
@@ -82,7 +88,10 @@ def preprocess_lte(df: pd.DataFrame) -> pd.DataFrame:
         + df["4G/LTE UL Traffic Volume (GBytes)"]
     )
     df["code"] = df["LNBTS name"].apply(extract_code)
-    df["date"] = pd.to_datetime(df["PERIOD_START_TIME"], format="%m.%d.%Y")
+    date_format = (
+        "%m.%d.%Y %H:%M:%S" if len(df["PERIOD_START_TIME"].iat[0]) > 10 else "%m.%d.%Y"
+    )
+    df["date"] = pd.to_datetime(df["PERIOD_START_TIME"], format=date_format)
     df["ID"] = df["date"].astype(str) + "_" + df["code"].astype(str)
     df = df.groupby(["date", "ID", "code"], as_index=False)[["lte_data_trafic"]].sum()
     return df