adding more data filtering exception catching

rowers/dataroutines.py

@@ -679,6 +679,8 @@ def clean_df_stats_pl(datadf, workstrokesonly=True, ignorehr=True,
             datadf['workoutid'] = 0
         except TypeError:
             datadf = datadf.with_columns(pl.lit(0).alias("workoutid"))
+    except ColumnNotFoundError:
+        datadf = datadf.with_columns(pl.lit(0).alias("workoutid"))
 
     before = {}
     ids = list(datadf['workoutid'].unique())
@@ -689,39 +691,51 @@ def clean_df_stats_pl(datadf, workstrokesonly=True, ignorehr=True,
 
     # bring metrics which have negative values to positive domain
     if len(datadf) == 0:
-        return datadf
+        return data_orig
     try:
         datadf = datadf.with_columns((-pl.col('catch')).alias('catch'))
-    except (KeyError, TypeError, InvalidOperationError):
+    except (KeyError, TypeError):
         pass
+    except(ComputeError, InvalidOperationError, ColumnNotFoundError):
+        return data_orig
 
     try:
         datadf = datadf.with_columns((pl.col('peakforceangle')+1000).alias('peakforceangle'))
-    except (KeyError, TypeError, InvalidOperationError):
+    except (KeyError, TypeError):
         pass
+    except(ComputeError, InvalidOperationError, ColumnNotFoundError):
+        return data_orig
 
     try:
         datadf = datadf.with_columns((pl.col('hr')+10).alias('hr'))
-    except (KeyError, TypeError, InvalidOperationError):
+    except (KeyError, TypeError):
         pass
+    except(ComputeError, InvalidOperationError, ColumnNotFoundError):
+        return data_orig
 
     # protect 0 spm values from being nulled
     try:
         datadf = datadf.with_columns((pl.col('spm')+1.0).alias('spm'))
-    except (KeyError, TypeError, InvalidOperationError):
+    except (KeyError, TypeError):
         pass
+    except(ComputeError, InvalidOperationError, ColumnNotFoundError):
+        return data_orig
 
     # protect 0 workoutstate values from being nulled
     try:
         datadf = datadf.with_columns((pl.col('workoutstate')+1).alias('workoutstate'))
-    except (KeyError, TypeError, InvalidOperationError):
+    except (KeyError, TypeError):
         pass
+    except(ComputeError, InvalidOperationError, ColumnNotFoundError):
+        return data_orig
 
     try:
         datadf = datadf.select(pl.all().clip(lower_bound=0))
         #        datadf = datadf.clip(lower=0)
-    except TypeError:
+    except (TypeError):
         pass
+    except(ComputeError, InvalidOperationError, ColumnNotFoundError):
+        return data_orig
 
     # protect advanced metrics columns
     advancedcols = [