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<p>我碰巧陷入了一个有点复杂的境地(至少对我来说)。在</p>
<p>我有一个列表,它包含一个元组,它包含一个字典的多个<code>combinations</code>和一个值,如下所示:</p>
<pre><code>[({'a':'1,2,3','b':'2','c':'3'},0.25),({'a':'3,4,5','b':'4','c':'6'},0.50),({'a':'10,4,3','b':'6','c':'4'},0.25)
</code></pre>
<p>我只需要得到某些键的值才能进行我想要的计算。假设我想要得到每个字典的<code>'a'</code>与元组中另一个字典的关联:</p>
^{pr2}$
<p>我知道这段代码对你们中的许多人来说可能太过分了,但我对python(以及一般的编码)还不太熟悉,对元组和字典的迭代了解不多。在</p>
<h2>更新</h2>
<p>输入示例:</p>
<pre><code>[({'url': 'https://ca.finance.yahoo.com/q/hp?s=QEC.TO&a=02&b=2&c=2005&d=02&e=2&f=2015&g=m&z=66&y=66', 'varreturns': '0.847771901', 'sdreturns': '0.920745296', 'name': 'Questerre Energy Corp (QEC.TO)', 'avgreturns': '1.292727273'}, 0.25), ({'url': 'https://ca.finance.yahoo.com/q/hp?s=RBA.TO&a=02&b=2&c=2005&d=02&e=2&f=2015&g=m&z=66&y=66', 'varreturns': '16.6860534', 'sdreturns': '4.084856595', 'name': 'Ritchie Bros Auctioneers Inc (RBA.TO)', 'avgreturns': '20.71140496'}, 0.5), ({'url': 'https://ca.finance.yahoo.com/q/hp?s=RDK.TO&a=02&b=2&c=2005&d=02&e=2&f=2015&g=m&z=66&y=66', 'varreturns': '0.038118899', 'sdreturns': '0.195240618', 'name': 'Redhawk Resources Inc (RDK.TO)', 'avgreturns': '0.400330579'}, 0.25)]
</code></pre>
<p>每个元组都是不同的股票,通过itertools分配了不同的权重</p>
<p>代码给出:</p>
<pre><code>import itertools
import csv
names = []
stocks = []
with open('AbCtest.csv', 'rU') as csvfile:
reader = csv.DictReader(csvfile)
document = reader
for row in reader:
stock = row
stocks.<a href="https://www.cnpython.com/list/append" class="inner-link">append</a>(row)
name = row['name']
names.append(name)
weights_list = [(0.95, 0.025, 0.025),
(0.90, 0.05, 0.05),
(0.85, 0.075, 0.075),
(0.80, 0.1, 0.1),
(0.75, 0.125, 0.125),
(0.70, 0.15, 0.15),
(0.65, 0.175, 0.175),
(0.60, 0.20, 0.20),
(0.55, 0.225, 0.225),
(0.50, 0.25, 0.25)]
def portfolios(document, weights_list):
for stock_triplet in itertools.combinations(document, 3):
for weights in weights_list:
unique_weight_orders = set(itertools.permutations(weights))
for weight_order in unique_weight_orders:
yield zip(stock_triplet, weight_order)
for port in portfolios(stocks,weights_list):
print port
</code></pre>
<p>有希望的产出示例:</p>
<pre><code>10.778966942999999
</code></pre>
<p>出具人:</p>
<pre><code>('avgreturns' * weight) + ('avgreturns' * weight) + ('avgreturns' * weight)
#or, from taking the values given in "example of input"
(0.400330579*0.25)+(20.71140496*0.5)+(1.292727273*0.25)
</code></pre>
<p><strong>至于相关部分:</strong></p>
<p>我知道这将更加困难,并且可能需要再次使用<code>itertools</code>。在</p>
<p>假设我们将“example input”中的每个元组命名为“a”、“b”和“c”。我们如何找到“a”和“b”,“b”和“c”,以及“a”和“c”之间的相关性?在</p>
<p>对于“示例输入”中所有可能的“avgreturns”组合:</p>
<pre><code>corr_ab = numpy.correlate('avgreturns','avgreturns')
corr_ac = numpy.correlate('avgreturns','avgreturns')
corr_cb = numpy.correlate('avgreturns','avgreturns')
</code></pre>
<p>感谢你的帮助!在</p>
<p>干杯!在</p>