python - Matplotlib and Numpy Math -

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i'm trying traction matplotlib , numpy not easy.

i'm doing mini project start dealing matplotlib , numpy i'm stuck...

here code:

# modules import datetime import numpy np import matplotlib.finance finance import matplotlib.mlab mlab import matplotlib.pyplot plot  # define quote startdate = datetime.date(2010,10,1) today = enddate = datetime.date.today() ticker = 'uso'  # catch csv fh = finance.fetch_historical_yahoo(ticker, startdate, enddate)  # csv reacarray r = mlab.csv2rec(fh); fh.close() # order desc r.sort()   ### methods begin def moving_average(x, n, type='simple'):     """     compute n period moving average.      type 'simple' | 'exponential'      """     x = np.asarray(x)     if type=='simple':         weights = np.ones(n)     else:         weights = np.exp(np.linspace(-1., 0., n))      weights /= weights.sum()       =  np.convolve(x, weights, mode='full')[:len(x)]     a[:n] = a[n]     return ### methods end   prices = r.adj_close dates = r.date ma20 = moving_average(prices, 20, type='simple') ma50 = moving_average(prices, 50, type='simple')  # when ma20 crosses ma50 equal = np.round(ma20,1)==np.round(ma50,1) dates_cross  = (dates[equal]) prices_cross = (prices[equal])  # when ma20 > ma50 ma20_greater_than_ma50 = np.round(ma20,1) > np.round(ma50,1) dates_ma20_greater_than_ma50  = (dates[ma20_greater_than_ma50]) prices_ma20_greater_than_ma50 = (prices[ma20_greater_than_ma50])  print dates_ma20_greater_than_ma50 print prices_ma20_greater_than_ma50

now need this:

store price of "price_cross" see if 1 day after "ma20_greater_than_ma50" statment true, if true store price "price of 1 day after" "next price_cross" - "price of 1 day after"  (price2 - price1) occurences

how can math , more important. how can traction matplotlib , numpy. books should buy?

give me clues.

best regards,

i agree josh, wanted add matplotlib gallery:

http://matplotlib.sourceforge.net/gallery.html

most of plots start off directly copying close want, , modifying fit needs. matplotlib gallery has many such examples.


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