Dodati su podaci o broju redova i kolona.

2 files changed, 14 insertions, 5 deletions

diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py
index ff803358..83741ce1 100644
--- a/backend/microservice/api/controller.py
+++ b/backend/microservice/api/controller.py
@@ -46,6 +46,11 @@ def returnColumnsInfo():
     dataset = json.loads(request.form["dataset"])
     file = request.files.get("file")
     data=pd.read_csv(file)
+    
+    #dataset={}
+    #f = request.json['filepath']
+    #data=pd.read_csv(f)
+
     preprocess = newmlservice.returnColumnsInfo(data)
     #samo 10 jedinstvenih posto ih ima previse, bilo bi dobro da promenimo ovo da to budu 10 najzastupljenijih vrednosti
     for col in preprocess["columnInfo"]:
@@ -53,6 +58,8 @@ def returnColumnsInfo():
     dataset["columnInfo"] = preprocess["columnInfo"]
     dataset["nullCols"] = preprocess["allNullColl"]
     dataset["nullRows"] = preprocess["allNullRows"]
+    dataset["colCount"] = preprocess["colCount"]
+    dataset["rowCount"] = preprocess["rowCount"]
     dataset["isPreProcess"] = True
     print(dataset)
     return jsonify(dataset)
diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py
index ea51b58e..77cc59d0 100644
--- a/backend/microservice/api/newmlservice.py
+++ b/backend/microservice/api/newmlservice.py
@@ -28,6 +28,9 @@ def returnColumnsInfo(dataset):
     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):
             uniquevalues=datafront[kolona].unique()
@@ -45,7 +48,7 @@ def returnColumnsInfo(dataset):
                         'mean':float(median),
                         'numNulls':int(nullCount),
                         'min':float(minimum),
-                        'max':float(maximum)
+                        'max':float(maximum),
             }
             dict.append(frontreturn)
         else:
@@ -63,15 +66,14 @@ def returnColumnsInfo(dataset):
                         'median':float(median),
                         'numNulls':int(nullCount),
                         'min':float(minimum),
-                        'max':float(maximum)
+                        'max':float(maximum),
             }
             dict.append(frontreturn)
         NullRows = datafront[datafront.isnull().any(axis=1)]
         #print(NullRows)
         #print(len(NullRows))
         allNullRows=len(NullRows)
-
-    return {'columnInfo':dict,'allNullColl':int(allNullCols),'allNullRows':int(allNullRows)}
+    return {'columnInfo':dict,'allNullColl':int(allNullCols),'allNullRows':int(allNullRows),'rowCount':int(rowCount),'colCount':int(colCount)}
 
 @dataclass
 class TrainingResultClassification:
@@ -118,7 +120,7 @@ def train(dataset, params, callback):
     null_values_replacers = params["nullValuesReplacers"]
     
     if(null_value_options=='replace'):
-        #print("replace null") # TODO
+        #print("replace null") #
         dict=params['null_values_replacers']
         while(len(dict)>0):
             replace=dict.pop()