diff --git a/src/spikeinterface/curation/model_based_curation.py b/src/spikeinterface/curation/model_based_curation.py
index 87b5693034..ebc12458cc 100644
--- a/src/spikeinterface/curation/model_based_curation.py
+++ b/src/spikeinterface/curation/model_based_curation.py
@@ -93,7 +93,7 @@ def predict_labels(self, label_conversion=None, input_data=None, export_to_phy=F
                 warnings.warn("Could not find `label_conversion` key in `model_info.json` file")
 
         # Prepare input data
-        input_data = input_data.map(lambda x: np.nan if np.isinf(x) else x)
+        input_data = input_data.applymap(lambda x: np.nan if np.isinf(x) else x)
         input_data = input_data.astype("float32")
 
         # Apply classifier
diff --git a/src/spikeinterface/curation/train_manual_curation.py b/src/spikeinterface/curation/train_manual_curation.py
index e905aa7646..6223fd1c4c 100644
--- a/src/spikeinterface/curation/train_manual_curation.py
+++ b/src/spikeinterface/curation/train_manual_curation.py
@@ -225,8 +225,8 @@ def process_test_data_for_classification(self):
             print("metrics_list contains invalid metric names")
             raise e
         self.X = self.testing_metrics.reindex(columns=self.metric_names)
+        self.X = self.X.applymap(lambda x: np.nan if np.isinf(x) else x)
         self.X = self.X.astype("float32")
-        self.X = self.X.map(lambda x: np.nan if np.isinf(x) else x)
         self.X.fillna(0, inplace=True)
 
     def apply_scaling_imputation(self, imputation_strategy, scaling_technique, X_train, X_val, y_train, y_val):