From 4858cd15ec093245e5febc39f3176370c9947ab4 Mon Sep 17 00:00:00 2001
From: TAMARA JERINIC <tamara.jerinic@gmail.com>
Date: Wed, 4 May 2022 21:02:50 +0200
Subject: Dodato računanje korelacione matrice.
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---
 backend/microservice/api/newmlservice.py | 17 +++++++++++++++--
 1 file changed, 15 insertions(+), 2 deletions(-)

(limited to 'backend/microservice/api/newmlservice.py')

diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py
index 9e26b03a..f5e5abcc 100644
--- a/backend/microservice/api/newmlservice.py
+++ b/backend/microservice/api/newmlservice.py
@@ -27,13 +27,26 @@ import matplotlib.pyplot as plt
 #from ann_visualizer.visualize import ann_viz;
 def returnColumnsInfo(dataset):
     dict=[]
+    
     datafront=dataset.copy()
+    dataMatrix=dataset.copy()
+    
+   
     svekolone=datafront.columns
     kategorijskekolone=datafront.select_dtypes(include=['object']).columns
+
     allNullCols=0
     rowCount=datafront.shape[0]#ukupan broj redova
     colCount=len(datafront.columns)#ukupan broj kolona
 
+    for kolona in svekolone:
+        if(kolona in kategorijskekolone):
+            encoder=LabelEncoder()
+            dataMatrix[kolona]=encoder.fit_transform(dataMatrix[kolona])
+
+    #print(dataMatrix.dtypes)
+    cMatrix=dataMatrix.corr()
+
     for kolona in svekolone:
         if(kolona in kategorijskekolone):
             unique=datafront[kolona].value_counts()
@@ -86,7 +99,7 @@ def returnColumnsInfo(dataset):
 
             #pretvaranje u kategorijsku
             datafront = datafront.astype({kolona: str})
-            print(datafront.dtypes)
+            #print(datafront.dtypes)
             unique=datafront[kolona].value_counts()
             uniquevaluesn=[]
             uniquevaluescountn=[]
@@ -117,7 +130,7 @@ def returnColumnsInfo(dataset):
         #print(NullRows)
         #print(len(NullRows))
         allNullRows=len(NullRows)
-    return {'columnInfo':dict,'allNullColl':int(allNullCols),'allNullRows':int(allNullRows),'rowCount':int(rowCount),'colCount':int(colCount)}
+    return {'columnInfo':dict,'allNullColl':int(allNullCols),'allNullRows':int(allNullRows),'rowCount':int(rowCount),'colCount':int(colCount),'cMatrix':str(np.matrix(cMatrix))}
 
 @dataclass
 class TrainingResultClassification:
-- 
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