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Merged
merged 11 commits into from
Aug 7, 2016
Merged

Build misc examples #6868

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a2b21a8
Run misc examples as part of docs build
jenshnielsen Jul 31, 2016
1535bb0
Don't try to run image_thumbnail example as part of docs build
jenshnielsen Jul 31, 2016
2df20fc
Multiprocess example depends on gtk so don't run it during docss build
jenshnielsen Jul 31, 2016
0c42d2f
rc_traits example depends on traits so don't run it during docss build
jenshnielsen Jul 31, 2016
b172ec6
Remove out of datelongshort example
jenshnielsen Jul 31, 2016
222ed14
np.dtype does not support unicode strings on python 2.7 so encode bef…
jenshnielsen Jul 31, 2016
cbec32b
interkeys should be called on the dict and not the keys
jenshnielsen Jul 31, 2016
0ba12c6
Revert "Remove out of datelongshort example"
jenshnielsen Jul 31, 2016
c9caa48
Make longshort python3 compatible
jenshnielsen Jul 31, 2016
90d6bac
dtype names must be strings and not unicode in python2
jenshnielsen Jul 31, 2016
b926d50
Feedback from review
jenshnielsen Aug 7, 2016
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Make longshort python3 compatible
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@jenshnielsen
jenshnielsen committed Jul 31, 2016
commit c9caa48a05cfce16fbd7114cd75eca536468c404
10 changes: 5 additions & 5 deletions examples/misc/longshort.py
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Expand Up @@ -3,18 +3,18 @@
csv file, computing the daily returns, appending the results to the
record arrays, joining on date
"""
import urllib
from six.moves import urllib
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab

# grab the price data off yahoo
u1 = urllib.urlretrieve('http://ichart.finance.yahoo.com/table.csv?s=AAPL&d=9&e=14&f=2008&g=d&a=8&b=7&c=1984&ignore=.csv')
u2 = urllib.urlretrieve('http://ichart.finance.yahoo.com/table.csv?s=GOOG&d=9&e=14&f=2008&g=d&a=8&b=7&c=1984&ignore=.csv')
u1 = urllib.request.urlretrieve('http://ichart.finance.yahoo.com/table.csv?s=AAPL&d=9&e=14&f=2008&g=d&a=8&b=7&c=1984&ignore=.csv')
u2 = urllib.request.urlretrieve('http://ichart.finance.yahoo.com/table.csv?s=GOOG&d=9&e=14&f=2008&g=d&a=8&b=7&c=1984&ignore=.csv')

# load the CSV files into record arrays
r1 = mlab.csv2rec(file(u1[0]))
r2 = mlab.csv2rec(file(u2[0]))
r1 = mlab.csv2rec(open(u1[0]))
r2 = mlab.csv2rec(open(u2[0]))

# compute the daily returns and add these columns to the arrays
gains1 = np.zeros_like(r1.adj_close)
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