diff --git a/Core/CoreTraidMath.py b/Core/CoreTraidMath.py
index dda9770..523a80e 100644
--- a/Core/CoreTraidMath.py
+++ b/Core/CoreTraidMath.py
@@ -12,18 +12,10 @@ import statistics
 
 
 import datetime 
-import matplotlib.dates as mdates
-import matplotlib.pyplot as plt
 
-import mplfinance as mpf
 
-import plotly
-#import plotly.plotly as py
-import plotly.graph_objs as go
-# these two lines allow your code to show up in a notebook
-from plotly.offline import init_notebook_mode, iplot
-from plotly.subplots import make_subplots
-init_notebook_mode()
+
+
 
 class CoreMath:
     
@@ -48,8 +40,10 @@ class CoreMath:
         
         if self.params['action']=='findExt':
             ans = self.getExtremumValue()
-        if self.params['action']=='findMean':
+        elif self.params['action']=='findMean':
             ans = self.getMeanValue()
+        elif self.params['action']=='findSTD':
+            ans=self.getSTD()
         
             
         return ans
@@ -102,6 +96,7 @@ class CoreMath:
         if self.params['actionOptions']['MeanType']=='SMA':
             ans=np.convolve(self.col, np.ones(self.params['actionOptions']['window']), 'valid') / self.params['actionOptions']['window']
             #ans=self.col.rolling(window=self.params['actionOptions']['window']).mean().to_list()
+            
         if self.params['actionOptions']['MeanType']=='EMA':
             ans=self.col.ewm(span=self.params['actionOptions']['span'], adjust=False).mean().to_list()
         if self.params['actionOptions']['MeanType']=='WMA':
@@ -114,4 +109,30 @@ class CoreMath:
         
         
         return(ans)
+    
+    def getSTD(self):
+        '''
+        actionOptions:
+            window
+        
+        
+        
+        
+        
+        '''
+        
+        ans=None
+
+
+        try:
+            window=self.params['actionOptions']['window']
+            ans=np.asarray([])
+            for i in range(len(self.col)-window+1):
+                ans=np.append(ans,np.std(self.col[i:i+window], ddof=1))
+            
+        except:
+            #window = len(self.col)
+            ans=np.std(self.col, ddof=1)
+
+        return ans