.. _misc-rec_groupby_demo: misc example code: rec_groupby_demo.py ====================================== [`source code `_] :: from __future__ import print_function import numpy as np import matplotlib.mlab as mlab import matplotlib.cbook as cbook datafile = cbook.get_sample_data('aapl.csv', asfileobj=False) print('loading', datafile) r = mlab.csv2rec(datafile) r.sort() def daily_return(prices): 'an array of daily returns from price array' g = np.zeros_like(prices) g[1:] = (prices[1:]-prices[:-1])/prices[:-1] return g def volume_code(volume): 'code the continuous volume data categorically' ind = np.searchsorted([1e5,1e6, 5e6,10e6, 1e7], volume) return ind # a list of (dtype_name, summary_function, output_dtype_name). # rec_summarize will call on each function on the indicated recarray # attribute, and the result assigned to output name in the return # record array. summaryfuncs = ( ('date', lambda x: [thisdate.year for thisdate in x], 'years'), ('date', lambda x: [thisdate.month for thisdate in x], 'months'), ('date', lambda x: [thisdate.weekday() for thisdate in x], 'weekday'), ('adj_close', daily_return, 'dreturn'), ('volume', volume_code, 'volcode'), ) rsum = mlab.rec_summarize(r, summaryfuncs) # stats is a list of (dtype_name, function, output_dtype_name). # rec_groupby will summarize the attribute identified by the # dtype_name over the groups in the groupby list, and assign the # result to the output_dtype_name stats = ( ('dreturn', len, 'rcnt'), ('dreturn', np.mean, 'rmean'), ('dreturn', np.median, 'rmedian'), ('dreturn', np.std, 'rsigma'), ) # you can summarize over a single variable, like years or months print('summary by years') ry = mlab.rec_groupby(rsum, ('years',), stats) print(mlab. rec2txt(ry)) print('summary by months') rm = mlab.rec_groupby(rsum, ('months',), stats) print(mlab.rec2txt(rm)) # or over multiple variables like years and months print('summary by year and month') rym = mlab.rec_groupby(rsum, ('years','months'), stats) print(mlab.rec2txt(rym)) print('summary by volume') rv = mlab.rec_groupby(rsum, ('volcode',), stats) print(mlab.rec2txt(rv)) Keywords: python, matplotlib, pylab, example, codex (see :ref:`how-to-search-examples`)