Encoder handle unknown

CHANGES.rst

@@ -10,6 +10,11 @@ new features
 
 - `extractor.scrape.FitsScraper.scrape_dataframe` method added for scraping Fits data from dataframe [#52]
 
+bug fixes
+---------
+
+- `preprocessor.encode.PairEncoder.handle_unknowns` create single new encoding value per unidentified variable [#53]
+
 
 1.0.1 (2024-04-03)
 ==================

spacekit/logger/log.py

@@ -68,7 +68,7 @@ def __init__(
         self.short_name = script_name
         self.console = console
         self.logfile = logfile
-        self.log_level = logging.DEBUG
+        self.log_level = logging.INFO
         self.console_log_output = console_log_output.lower()
         self.console_log_level = console_log_level.upper()
         self.console_log_color = console_log_color

spacekit/preprocessor/encode.py

@@ -108,12 +108,13 @@ def inverse_pairs(self):
         return self.invpairs
 
     def handle_unknowns(self, unknowns):
-        self.log.warning(f"Found unknown values:\n {self.arr[unknowns]}")
-        add_encoding = max(list(self.keypairs.values())) + 1
+        uvals = np.unique(self.arr[unknowns])
+        self.log.warning(f"Found unknown values:\n {uvals}")
         try:
-            self.keypairs[self.arr[unknowns][0]] = add_encoding
-            self.classes_ = list(self.keypairs.keys())
-            self.log.info("Successfully added encoding for unknown values.")
+            for u in uvals:
+                add_encoding = max(list(self.keypairs.values())) + 1
+                self.keypairs[u] = add_encoding
+                self.classes_ = list(self.keypairs.keys())
         except Exception as e:
             self.log.error("Unable to add encoding for unknown value(s)", e)
 
@@ -236,16 +237,17 @@ def _encode_features(self):
                 "encoding_pairs attr must be instantiated with key-value pairs"
             )
             return
-        self.log.info("Encoding categorical features...")
+        self.log.debug("Encoding categorical features...")
         for col, name in self.encodings.items():
             keypairs = self.encoding_pairs[col]
             enc = PairEncoder()
             enc.fit_transform(self.df, keypairs, axiscol=col)
             self.df[name] = enc.transformed
-            self.log.debug(f"*** {col} --> {name} ***")
-            self.log.debug(
-                f"\n\nORIGINAL:\n{self.df[col].value_counts()}\n\nENCODED:\n{self.df[name].value_counts()}\n"
-            )
+            if self.verbose:
+                self.log.debug(f"*** {col} --> {name} ***")
+                self.log.debug(
+                    f"\n\nORIGINAL:\n{self.df[col].value_counts()}\n\nENCODED:\n{self.df[name].value_counts()}\n"
+                )
         self.rejoin_original()
         return self.df