add data module

src/data/processing.py

@@ -0,0 +1,48 @@
+import numpy as np
+
+class Scaler():
+
+    def __init__(self, scaler='standard', range=(0,1)):
+        
+        if not scaler.lower() in ['minmax', 'standard']:
+            raise ValueError('Incorrect scaler. Please choose between minmax and standard.')
+        
+        self.scaler = scaler.lower()
+        self.min = range[0]
+        self.max = range[1]
+
+    def fit(self, X):
+        
+        if self.scaler == 'minmax':
+            self.data_min = np.nanmin(X)
+            self.data_max = np.nanmax(X)
+
+        else:
+            self.data_mean = np.nanmean(X)
+            self.data_std = np.nanstd(X)
+        
+        return self
+
+    def transform(self, X):
+
+        X = X.copy()
+        
+        if self.scaler == 'minmax':
+            X = (X-self.data_min)/(self.data_max - self.data_min)*(self.max-self.min) + self.min
+
+        else:
+            X = (X-self.data_mean)/self.data_std
+
+        return X
+    
+    def inverse_transform(self, X):
+        
+        X = X.copy()
+        
+        if self.scaler == 'minmax':
+            X = ((X-self.min)*(self.data_max-self.data_min)/(self.max-self.min)) + self.data_min
+
+        else:
+            X = X*self.data_std + self.data_mean
+        
+        return X