Resampling Live Websocket Ticks to Candles using Pandas in python The 2019 Stack Overflow Developer Survey Results Are In Announcing the arrival of Valued Associate #679: Cesar Manara Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern) The Ask Question Wizard is Live! Data science time! April 2019 and salary with experienceAdding new column to existing DataFrame in Python pandaspandas resample documentationPython Pandas Error tokenizing dataCombine two columns of text in dataframe in pandas/pythonResampling OHLC tick data and filling gaps in PandasHow to avoid Python/Pandas creating an index in a saved csv?pandas resample .csv tick data to OHLCTrouble resampling data in PandasResample python list with pandasaggregate tick data to open high low close non time related

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Resampling Live Websocket Ticks to Candles using Pandas in python



The 2019 Stack Overflow Developer Survey Results Are In
Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)
The Ask Question Wizard is Live!
Data science time! April 2019 and salary with experienceAdding new column to existing DataFrame in Python pandaspandas resample documentationPython Pandas Error tokenizing dataCombine two columns of text in dataframe in pandas/pythonResampling OHLC tick data and filling gaps in PandasHow to avoid Python/Pandas creating an index in a saved csv?pandas resample .csv tick data to OHLCTrouble resampling data in PandasResample python list with pandasaggregate tick data to open high low close non time related



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0















I am trying to resample live ticks from KiteTicker websocket into OHLC candles using pandas and this is the code I have written, which works fine with single instrument (The commented trd_portfolio on line 9) but doesn't work with multiple instruments (Line 8) as it mixes up data of different instruments.



Is there any way to relate the final candles df to instrument tokens? or make this work with multiple intruments?



I would like to run my algo on multiple instruments at once, please suggest if there is a better way around it.



from kiteconnect import KiteTicker;
from kiteconnect import KiteConnect;
import logging
import time,os,datetime,math;
import winsound
import pandas as pd

trd_portfolio = 954883:"USDINR19MARFUT",4632577:"JUBLFOOD"
# trd_portfolio = 954883:"USDINR19MARFUT"

trd_tkn1 = [];

for x in trd_portfolio:
trd_tkn1.append(x)


c_id = '****************'
ak = '************'
asecret = '*************************'

kite = KiteConnect(api_key=ak)
print('[*] Generate access Token : ',kite.login_url())
request_tkn = input('[*] Enter Your Request Token Here : ')[-32:];
data = kite.generate_session(request_tkn, api_secret=asecret)
kite.set_access_token(data['access_token'])
kws = KiteTicker(ak, data['access_token'])

#columns in data frame
df_cols = ["Timestamp", "Token", "LTP"]

data_frame = pd.DataFrame(data=[],columns=df_cols, index=[])

def on_ticks(ws, ticks):

global data_frame, df_cols

data = dict()

for company_data in ticks:
token = company_data["instrument_token"]
ltp = company_data["last_price"]
timestamp = company_data['timestamp']

data[timestamp] = [timestamp, token, ltp]

tick_df = pd.DataFrame(data.values(), columns=df_cols, index=data.keys()) #
data_frame = data_frame.append(tick_df)

ggframe=data_frame.set_index(['Timestamp'],['Token'])
print ggframe
gticks=ggframe.ix[:,['LTP']]
candles=gticks['LTP'].resample('1min').ohlc().dropna()
print candles

def on_connect(kws , response):
print('Connected')
kws.subscribe(trd_tkn1)
kws.set_mode(kws.MODE_FULL, trd_tkn1)

def on_close(ws, code, reason):
print('Connection Error')


kws.on_ticks = on_ticks
kws.on_connect = on_connect
kws.on_close = on_close

kws.connect()









share|improve this question




























    0















    I am trying to resample live ticks from KiteTicker websocket into OHLC candles using pandas and this is the code I have written, which works fine with single instrument (The commented trd_portfolio on line 9) but doesn't work with multiple instruments (Line 8) as it mixes up data of different instruments.



    Is there any way to relate the final candles df to instrument tokens? or make this work with multiple intruments?



    I would like to run my algo on multiple instruments at once, please suggest if there is a better way around it.



    from kiteconnect import KiteTicker;
    from kiteconnect import KiteConnect;
    import logging
    import time,os,datetime,math;
    import winsound
    import pandas as pd

    trd_portfolio = 954883:"USDINR19MARFUT",4632577:"JUBLFOOD"
    # trd_portfolio = 954883:"USDINR19MARFUT"

    trd_tkn1 = [];

    for x in trd_portfolio:
    trd_tkn1.append(x)


    c_id = '****************'
    ak = '************'
    asecret = '*************************'

    kite = KiteConnect(api_key=ak)
    print('[*] Generate access Token : ',kite.login_url())
    request_tkn = input('[*] Enter Your Request Token Here : ')[-32:];
    data = kite.generate_session(request_tkn, api_secret=asecret)
    kite.set_access_token(data['access_token'])
    kws = KiteTicker(ak, data['access_token'])

    #columns in data frame
    df_cols = ["Timestamp", "Token", "LTP"]

    data_frame = pd.DataFrame(data=[],columns=df_cols, index=[])

    def on_ticks(ws, ticks):

    global data_frame, df_cols

    data = dict()

    for company_data in ticks:
    token = company_data["instrument_token"]
    ltp = company_data["last_price"]
    timestamp = company_data['timestamp']

    data[timestamp] = [timestamp, token, ltp]

    tick_df = pd.DataFrame(data.values(), columns=df_cols, index=data.keys()) #
    data_frame = data_frame.append(tick_df)

    ggframe=data_frame.set_index(['Timestamp'],['Token'])
    print ggframe
    gticks=ggframe.ix[:,['LTP']]
    candles=gticks['LTP'].resample('1min').ohlc().dropna()
    print candles

    def on_connect(kws , response):
    print('Connected')
    kws.subscribe(trd_tkn1)
    kws.set_mode(kws.MODE_FULL, trd_tkn1)

    def on_close(ws, code, reason):
    print('Connection Error')


    kws.on_ticks = on_ticks
    kws.on_connect = on_connect
    kws.on_close = on_close

    kws.connect()









    share|improve this question
























      0












      0








      0








      I am trying to resample live ticks from KiteTicker websocket into OHLC candles using pandas and this is the code I have written, which works fine with single instrument (The commented trd_portfolio on line 9) but doesn't work with multiple instruments (Line 8) as it mixes up data of different instruments.



      Is there any way to relate the final candles df to instrument tokens? or make this work with multiple intruments?



      I would like to run my algo on multiple instruments at once, please suggest if there is a better way around it.



      from kiteconnect import KiteTicker;
      from kiteconnect import KiteConnect;
      import logging
      import time,os,datetime,math;
      import winsound
      import pandas as pd

      trd_portfolio = 954883:"USDINR19MARFUT",4632577:"JUBLFOOD"
      # trd_portfolio = 954883:"USDINR19MARFUT"

      trd_tkn1 = [];

      for x in trd_portfolio:
      trd_tkn1.append(x)


      c_id = '****************'
      ak = '************'
      asecret = '*************************'

      kite = KiteConnect(api_key=ak)
      print('[*] Generate access Token : ',kite.login_url())
      request_tkn = input('[*] Enter Your Request Token Here : ')[-32:];
      data = kite.generate_session(request_tkn, api_secret=asecret)
      kite.set_access_token(data['access_token'])
      kws = KiteTicker(ak, data['access_token'])

      #columns in data frame
      df_cols = ["Timestamp", "Token", "LTP"]

      data_frame = pd.DataFrame(data=[],columns=df_cols, index=[])

      def on_ticks(ws, ticks):

      global data_frame, df_cols

      data = dict()

      for company_data in ticks:
      token = company_data["instrument_token"]
      ltp = company_data["last_price"]
      timestamp = company_data['timestamp']

      data[timestamp] = [timestamp, token, ltp]

      tick_df = pd.DataFrame(data.values(), columns=df_cols, index=data.keys()) #
      data_frame = data_frame.append(tick_df)

      ggframe=data_frame.set_index(['Timestamp'],['Token'])
      print ggframe
      gticks=ggframe.ix[:,['LTP']]
      candles=gticks['LTP'].resample('1min').ohlc().dropna()
      print candles

      def on_connect(kws , response):
      print('Connected')
      kws.subscribe(trd_tkn1)
      kws.set_mode(kws.MODE_FULL, trd_tkn1)

      def on_close(ws, code, reason):
      print('Connection Error')


      kws.on_ticks = on_ticks
      kws.on_connect = on_connect
      kws.on_close = on_close

      kws.connect()









      share|improve this question














      I am trying to resample live ticks from KiteTicker websocket into OHLC candles using pandas and this is the code I have written, which works fine with single instrument (The commented trd_portfolio on line 9) but doesn't work with multiple instruments (Line 8) as it mixes up data of different instruments.



      Is there any way to relate the final candles df to instrument tokens? or make this work with multiple intruments?



      I would like to run my algo on multiple instruments at once, please suggest if there is a better way around it.



      from kiteconnect import KiteTicker;
      from kiteconnect import KiteConnect;
      import logging
      import time,os,datetime,math;
      import winsound
      import pandas as pd

      trd_portfolio = 954883:"USDINR19MARFUT",4632577:"JUBLFOOD"
      # trd_portfolio = 954883:"USDINR19MARFUT"

      trd_tkn1 = [];

      for x in trd_portfolio:
      trd_tkn1.append(x)


      c_id = '****************'
      ak = '************'
      asecret = '*************************'

      kite = KiteConnect(api_key=ak)
      print('[*] Generate access Token : ',kite.login_url())
      request_tkn = input('[*] Enter Your Request Token Here : ')[-32:];
      data = kite.generate_session(request_tkn, api_secret=asecret)
      kite.set_access_token(data['access_token'])
      kws = KiteTicker(ak, data['access_token'])

      #columns in data frame
      df_cols = ["Timestamp", "Token", "LTP"]

      data_frame = pd.DataFrame(data=[],columns=df_cols, index=[])

      def on_ticks(ws, ticks):

      global data_frame, df_cols

      data = dict()

      for company_data in ticks:
      token = company_data["instrument_token"]
      ltp = company_data["last_price"]
      timestamp = company_data['timestamp']

      data[timestamp] = [timestamp, token, ltp]

      tick_df = pd.DataFrame(data.values(), columns=df_cols, index=data.keys()) #
      data_frame = data_frame.append(tick_df)

      ggframe=data_frame.set_index(['Timestamp'],['Token'])
      print ggframe
      gticks=ggframe.ix[:,['LTP']]
      candles=gticks['LTP'].resample('1min').ohlc().dropna()
      print candles

      def on_connect(kws , response):
      print('Connected')
      kws.subscribe(trd_tkn1)
      kws.set_mode(kws.MODE_FULL, trd_tkn1)

      def on_close(ws, code, reason):
      print('Connection Error')


      kws.on_ticks = on_ticks
      kws.on_connect = on_connect
      kws.on_close = on_close

      kws.connect()






      python pandas resampling






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      share|improve this question










      asked Mar 22 at 5:39









      Parva PatelParva Patel

      193




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