flask_update_1

import pandas as pk
import numpy as np
from flask import Flask, jsonify
from flask import render_template

app = Flask(__name__)


df = pk.read_excel(
    '/home/pavan/PAVANKUMAR/MachineLearning/CaseStudy/MLCP_VIsualize/DayFile_EntriesCount.xlsx', sheetname=0)


WeekList = []
WeekSum = []

ValueList = []
IndexList = []

e = [0, 1, 2, 3, 4, 5, 6]

Last = df['U.Date'][0]
#print Last
startIndex = 0

df['x'] = map(lambda x: str(x), df['x'])

def WeakString(t):
    weekStr = []
    string = "Week"
    map(lambda z: weekStr.append(string + `z`), range(t))
    return weekStr

llr = [0,0,0,0,0,0,0]



def fun(k):

    #print (yy)
    llr[k] = yy.pop()
    return llr




ppp = []

for r in range(0, 5):



    WeekDate = Last + np.timedelta64(1, 'W')
    WeekIndex = df[df['U.Date'] == WeekDate].index.tolist()
    nextIndex = WeekIndex[0]
    df_2 = df[startIndex:nextIndex].sort_values(by=['DayNo'])
    Last = WeekDate
    startIndex = nextIndex

    ww = df_2[['DayNo', 'y']]
    ee = ww['DayNo'].tolist()
    yy = ww['y'].tolist()
    rr = ee[::-1]
    # print len(ww.index.tolist())
    IndexList.append((ww.index.tolist()))

    x = map(fun, rr)

    #print np.vstack(x[0])

    ValueList.append(np.array(x[0]))


    cc = df_2[['x', 'y']]
    # ddr = cc.reset_index(level=None, drop=True, inplace=False, col_level=0, col_fill='').to_json(orient='records')
    ddr = cc.to_json(orient='records')
    WeekList.append(ddr)
    WeekSum.append(cc['y'].sum())


fg = pk.DataFrame({"x": WeakString(len(WeekSum)), "y": WeekSum})
LG = fg.to_json(orient='records')

print np.column_stack(ValueList)



#print (IndexList)

print (IndexList[:])





@app.route("/getdata", methods=['POST'])
def chart():


    print WeekList
    print LG

    return jsonify(WL=WeekList, WS=LG)


@app.route("/")
def hello():
    return render_template('more.html')


if __name__ == "__main__":
    app.run()