diff options
| -rw-r--r-- | backend/microservice/__pycache__/mlservice.cpython-310.pyc | bin | 5009 -> 7405 bytes | |||
| -rw-r--r-- | backend/microservice/api.py | 2 | ||||
| -rw-r--r-- | backend/microservice/mlservice.py | 32 |
3 files changed, 33 insertions, 1 deletions
diff --git a/backend/microservice/__pycache__/mlservice.cpython-310.pyc b/backend/microservice/__pycache__/mlservice.cpython-310.pyc Binary files differindex c079459a..ac93f3db 100644 --- a/backend/microservice/__pycache__/mlservice.cpython-310.pyc +++ b/backend/microservice/__pycache__/mlservice.cpython-310.pyc diff --git a/backend/microservice/api.py b/backend/microservice/api.py index 4768f34c..9a28b159 100644 --- a/backend/microservice/api.py +++ b/backend/microservice/api.py @@ -9,7 +9,7 @@ import csv import json import mlservice import h5py -from mlservice2 import unositok +from mlservice import unositok app = flask.Flask(__name__) diff --git a/backend/microservice/mlservice.py b/backend/microservice/mlservice.py index b2eafe9a..8f56fc3f 100644 --- a/backend/microservice/mlservice.py +++ b/backend/microservice/mlservice.py @@ -54,6 +54,38 @@ def obuka(dataunos,params,modelunos,dataunosdrugog): data[zeljenekolone[i]]=dataunos[zeljenekolone[i]] #print(data.head(10)) + ### 0.1) Povratne vrednosti statistike za front (za popunjavanje null vrednosti izabranih kolona) PART4 + datafront=data.copy() + svekolone=datafront.columns + kategorijskekolone=datafront.select_dtypes(include=['object']).columns + #print(kategorijskekolone ) + #kategorijskekolone=datacategorical.columns + #print(svekolone) + for i in range(len(svekolone)): + nazivkolone=svekolone[i] + if(nazivkolone in kategorijskekolone): + svekategorije=datafront[nazivkolone].unique() + medijana=None + srednjavrednost=None + frontreturn={'colName':nazivkolone, + 'colType':'categorical', + 'categoricalValues':svekategorije, + 'mean':medijana, + 'average':srednjavrednost + } + else: + svekategorije=None + medijana=datafront[nazivkolone].mean() + srednjavrednost=sum(datafront[nazivkolone])/len(datafront[nazivkolone]) + frontreturn={'colName':nazivkolone, + 'colType':'noncategorical', + 'categoricalValues':svekategorije, + 'mean':medijana, + 'average':srednjavrednost + } + + print(frontreturn) + #predvidetikol=input("UNETI NAZIV KOLONE ČIJU VREDNOST TREBA PREDVIDETI ") ###sta se cuva od promenjivih broj kolone ili naziv kolone??? |