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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