@M.ST. Lastly I wanted to tested an Open Range Breakout system for SPY, therefore I would like to check, when a high or low of the day occured for every 30 minutes. Analyzing this in Jupyter took me about 10 lines of code, the result is a graph, check the attachment. This is the Python / Jupyter code: Code: import pytz import matplotlib.pyplot as pyplot import numpy as np import pandas as pd # code below data = get_pricing( 'SPY' , start_date='2015-1-1', end_date = '2016-9-1', frequency='minute' ) df = data.resample('30min',"ohlc")["open_price"] df = df.dropna() df["high_rank"]=df.groupby([ df.index.dayofyear])[["high"]].rank(method="max",ascending=False ) df["low_rank"]=df.groupby([df.index.dayofyear])[["low"]].rank(method="min",ascending=True) l_or_h=df[((df.high_rank==1) |(df.low_rank==1) )].groupby( ["hour","minute"] ).agg("count")["high_rank"] l_or_h.plot(kind='bar')
Thanks but I know how to write a program. I just don't see how Python would be most productive. What you did there is pretty easy to achieve elsewhere too.
If you are a seasoned programmer you can do everything in your language, this type of guys are seldom changing to other system, I hear people talking all the time of the benefits of vi and emacs as an IDE )) But for the rest of us, the not professional programmers, not even nerds, Python is a mean to achieve many things, just seasoned programmers could do otherwise. And the benefits of Python over R oder Amitrader is, from my point of view the possibilities to glue so many different libraries together.
Nonsense, you have access to libraries in R and AmiBroker also. You don't know anything about those as you clearly prove by your absolute beginners talk.