AviSoori1x

import streamlit as st
import pandas as pd 
import numpy as np
from PIL import Image
from swat import CAS, options
import json
import altair as alt
import SessionState
import requests
import io

AviSoori1x

!pip install altair
import altair as alt
alt.Chart(shap).mark_bar().encode(
    x='Variable',
    y='Estimate'
)

AviSoori1x

shapvals = s.linearExplainer(
             table           = {"name" : 'hmeqTest','caslib':'public'},
             query           = {"name" : 'realtime','caslib':'public'},
             modelTable      = {"name" :"hmeqTestAstore",'caslib':'public'},
             modelTableType  = "ASTORE",
             predictedTarget = 'P_BAD1',
             seed            = 1234,
             preset          = "KERNELSHAP",
             inputs          = ['LOAN','MORTDUE','VALUE','YOJ','DEROG','DELINQ','CLAGE','NINQ','CLNO','DEBTINC','REASON', 'JOB','BAD'],
             nominals        = ['REASON', 'JOB','BAD']

AviSoori1x

samplepd['BAD'] = scores.I_BAD.to_list()
s.upload(samplepd,casout={'name' : 'realtime', 'caslib' : 'public','replace' : True})

AviSoori1x

def score(samplepd):
    s.upload(samplepd,casout={'name' : 'realtime', 'caslib' : 'public','replace' : True})
    s.aStore.score(rstore = {"caslib":"public","name":"hmeqTestAstore"},
                        table = {"caslib":'public',"name":'realtime'},
                        out = {"caslib":'public',"name":'realscore', 'replace':True})
    scoredData = s.CASTable(name='realscore',caslib='public')
    datasetDict = scoredData.to_dict()
    scores = pd.DataFrame(datasetDict, index=[0])
    return scores

AviSoori1x

s.aStore.score(rstore = {"caslib":"public","name":"hmeqTestAstore"},
                    table = {"caslib":'public',"name":'realtime'},
                    out = {"caslib":'public',"name":'realscore', 'replace':True})
scoredData = s.CASTable(name='realscore',caslib='public')
datasetDict = scoredData.to_dict()
scores = pd.DataFrame(datasetDict, index=[0])
scores

AviSoori1x

samplepd = dicttopd(datadict)
s.upload(samplepd,casout={'name' : 'realtime', 'caslib' : 'public','replace' : True})

AviSoori1x

def dicttopd(datadict):
    for key in datadict:
        datadict[key] = [datadict[key]]
    return pd.DataFrame.from_dict(datadict)

AviSoori1x

datadict = {'LOAN':140,'MORTDUE':3000, 'VALUE':40000, 'REASON':'HomeImp','JOB':'Other','YOJ':12,
           'DEROG':0.0,'DELINQ':0.0, 'CLAGE':89,'NINQ':1.0, 'CLNO':10.0, 'DEBTINC':0.05} 

AviSoori1x

s.table.promote(name="hmeqTest", caslib='public',target="hmeqTest",targetLib='public')
modelAstore = s.decisionTree.dtreeExportModel(modelTable = {"caslib":"public","name":"gradboosthmeqtest" }, 
                                        casOut = {"caslib":"public","name":'hmeqTestAstore','replace':True})

s.table.promote(name='hmeqTestAstore', caslib='public',target='hmeqTestAstore',targetLib='public')