fix: raise in case of failed timestamp conversion

Author: nicokant

src/gps_logger_parser/gps/axytrek.py

@@ -61,7 +61,7 @@ class AXYTREKParser(GPSHarmonizationMixin, CSVParser):
     def harmonize_data(self, data):
         # Combine Date and Time columns into timestamp
         data["timestamp"] = pd.to_datetime(
-            data["Date"] + " " + data["Time"], errors="coerce"
+            data["Date"] + " " + data["Time"], errors="raise"
         )
         return super().harmonize_data(data)
 

src/gps_logger_parser/gps/base.py

@@ -57,7 +57,7 @@ class GPSParser(GPSHarmonizationMixin, CSVParser):
     def harmonize_data(self, data):
         # Combine Date and Time columns into timestamp
         data["timestamp"] = pd.to_datetime(
-            data["UTC_date"] + " " + data["UTC_time"], errors="coerce"
+            data["UTC_date"] + " " + data["UTC_time"], errors="raise"
         )
         return super().harmonize_data(data)
 

src/gps_logger_parser/gps/catlog.py

@@ -57,7 +57,7 @@ class GPSCatTrackParser(GPSHarmonizationMixin, CSVParser):
     def harmonize_data(self, data):
         # Combine Date and Time columns into timestamp
         data["timestamp"] = pd.to_datetime(
-            data["Date"] + " " + data["Time"], errors="coerce"
+            data["Date"] + " " + data["Time"], errors="raise"
         )
         return super().harmonize_data(data)
 

src/gps_logger_parser/gps/ho11.py

@@ -49,7 +49,7 @@ def harmonize_data(self, data):
         # Combine Date and Time columns into timestamp
         data["timestamp"] = pd.to_datetime(
             data["Date"] + " " + data["Time"],
-            errors="coerce",
+            errors="raise",
             format="%d.%m.%Y %H:%M:%S",
         )
         return super().harmonize_data(data)

src/gps_logger_parser/gps/igotu.py

@@ -47,7 +47,7 @@ class IGotU_GT_Parser(GPSHarmonizationMixin, CSVParser):
     def harmonize_data(self, data):
         # Combine Date and Time columns into timestamp
         data["timestamp"] = pd.to_datetime(
-            data["Date"] + " " + data["Time"], errors="coerce"
+            data["Date"] + " " + data["Time"], errors="raise"
         )
         return super().harmonize_data(data)
 

src/gps_logger_parser/gps/jm.py

@@ -107,14 +107,14 @@ def harmonize_data(self, data):
             data["timestamp"] = pd.to_datetime(
                 self.start_date + " " + data["__original__time"],
                 format="%d.%m.%Y %H:%M:%S",
-                errors="coerce",
+                errors="raise",
             )
         else:
             # Fallback if start_date not available
             data["timestamp"] = pd.to_datetime(
                 data["__original__date"].astype(str) + " " + data["__original__time"],
                 format="%d %H:%M:%S",
-                errors="coerce",
+                errors="raise",
             )
 
         # Recreate geometry column now that lat/lon are finalized
@@ -292,7 +292,7 @@ def harmonize_data(self, data):
         data["timestamp"] = pd.to_datetime(
             data["__original__UTC_date"] + " " + data["__original__UTC_time"],
             format="%d.%m.%Y %H:%M:%S",
-            errors="coerce",
+            errors="raise",
         )
         return data
 

src/gps_logger_parser/gps/mixin.py

@@ -61,14 +61,14 @@ def harmonize_data(self, data):
                     if data[col_name].dtype != "object":
                         data[col_name] = data[col_name].astype(str)
                 elif pd_dtype == "float64":
-                    data[col_name] = pd.to_numeric(data[col_name], errors="coerce")
+                    data[col_name] = pd.to_numeric(data[col_name], errors="raise")
                 elif pd_dtype == "Int64":
                     # Convert to numeric first, then to nullable Int64
-                    data[col_name] = pd.to_numeric(data[col_name], errors="coerce")
+                    data[col_name] = pd.to_numeric(data[col_name], errors="raise")
                     # Round to handle floating point values before conversion
                     data[col_name] = data[col_name].round().astype("Int64")
                 elif pd_dtype == "datetime64[ns]":
-                    data[col_name] = pd.to_datetime(data[col_name], errors="coerce")
+                    data[col_name] = pd.to_datetime(data[col_name], errors="raise")
 
         # Create geometry column from latitude and longitude (WGS84)
         # Note: This creates geometry from current lat/lon values

src/gps_logger_parser/gps/pathtrack.py

@@ -68,7 +68,7 @@ def harmonize_data(self, data):
             + ":"
             + data["second"].astype(str),
             format="%Y/%m/%d %H:%M:%S",
-            errors="coerce",
+            errors="raise",
         )
         return super().harmonize_data(data)
 
@@ -176,7 +176,7 @@ def harmonize_data(self, data):
             + ":"
             + data["second"].astype(str),
             format="%Y/%m/%d %H:%M:%S",
-            errors="coerce",
+            errors="raise",
         )
         return super().harmonize_data(data)
 

src/gps_logger_parser/gps/unknown.py

@@ -58,7 +58,7 @@ def harmonize_data(self, data):
         # Combine Date and Time columns into timestamp
         data["timestamp"] = pd.to_datetime(
             data["Date"] + " " + data["Time"],
-            errors="coerce",
+            errors="raise",
             format="%d.%m.%Y %H:%M:%S",
         )
         return super().harmonize_data(data)
@@ -81,7 +81,7 @@ def harmonize_data(self, data):
         # Combine Date and Time columns into timestamp
         data["timestamp"] = pd.to_datetime(
             data["Date"] + " " + data["Time"],
-            errors="coerce",
+            errors="raise",
             format="%d.%m.%Y %H:%M:%S",
         )
         return super().harmonize_data(data)