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-rw-r--r--backend/microservice/api/controller.py18
1 files changed, 12 insertions, 6 deletions
diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py
index 9b83b8e7..41035cc7 100644
--- a/backend/microservice/api/controller.py
+++ b/backend/microservice/api/controller.py
@@ -107,26 +107,32 @@ def predict():
@app.route('/preprocess',methods=['POST'])
def returnColumnsInfo():
print("********************************PREPROCESS*******************************")
+
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)
-
+ dataset={}
+ '''
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"]:
- col["uniqueValues"] = col["uniqueValues"][0:10]
- col["uniqueValuesCount"] = col["uniqueValuesCount"][0:10]
+ col["uniqueValues"] = col["uniqueValues"][0:6]
+ col["uniqueValuesCount"] = col["uniqueValuesCount"][0:6]
+ col['uniqueValuesPercent']=col['uniqueValuesPercent'][0:6]
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)
+ #print(dataset)
+
+
+
return jsonify(dataset)
print("App loaded.")