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I've tick by tick data for Forex pairs Here is a sample of EURUSD/EURUSD-2012-06.csv EUR/USD,20120601 00:00:00.207,1.23618,1.2363 EUR/USD,20120601 00:00:00.209,1.23618,1.23631 EUR/USD,20120601 00:00:00.210,1.23618,1.23631 EUR/USD,20120601 00:00:00.211,1.23623,1.23631 EUR/USD,20120601 00:00:00.240,1.23623,1.23627 EUR/USD,20120601 00:00:00.423,1.23622,1.23627 EUR/USD,20120601 00:00:00.457,1.2362,1.23626 EUR/USD,20120601 00:00:01.537,1.2362,1.23625 EUR/USD,20120601 00:00:03.010,1.2362,1.23624 EUR/USD,20120601 00:00:03.012,1.2362,1.23625 Full tick data can be downloaded here http://dl.free.fr/k4vVF7aOD Columns are : Symbol,Datetime,Bid,Ask I would like to convert this tick by tick data to candlestick data (also called OHLC Open High Low Close) I will say that I want to get a M15 timeframe (15 minutes) as an example I would like to use Python and Pandas library to achieve this task. I've done a little part of the job... reading the tick by tick data file Here is the code #!/usr/bin/env python import pandas as pd import matplotlib.pyplot as plt import numpy as np from matplotlib.finance import candlestick from datetime import * def conv_str_to_datetime(x): return(datetime.strptime(x, '%Y%m%d %H:%M:%S.%f')) df = pd.read_csv('test_EURUSD/EURUSD-2012-07.csv', names=['Symbol', 'Date_Time', 'Bid', 'Ask'], converters={'Date_Time': conv_str_to_datetime}) PipPosition = 4 df['Spread'] = (df['Ask'] - df['Bid']) * 10**PipPosition print(df) print("="*10) print(df.ix[0]) but now I don't know how to start rest of the job... I want to get data like Symbol,Datetime_open_candle,open_price,high_price,low_price,close_price Price on candle will be based on Bid column. The first part of the problem is in my mind to get

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