如何解决Python - 从“for循环”中获取单个浮点类型输出并组合成一个列表
我当前的输出是在我的下一步中不可迭代的单个浮点数:sum() 和 statistics.mean()。我曾尝试嵌套列表理解,但当它不起作用时,我在嵌套循环中尝试了 next,但我得到了同样的错误 - TypeError: 'float' object is not iterable。并且通过使用 [ss],列出了每个输出,但不会合并到一个列表中。
感谢任何帮助。如果您需要澄清或有任何疑问,请随时提问。
import pandas as pd
import numpy as np
import math
import statistics
frame=[bdrc,bdmp,bdmv,bdsm] #These are sources selected and then concated for variable,popPrices.
result=pd.concat(frame)
popPrices=result["Price"]
#Grand Mean
xpop=popPrices.mean() #The mean
for popsq in popPrices: #An attempt to have each individual sample treated with the grand mean. - success.
ss=math.pow(popsq - xpop,2)
print(ss) #This will print floats individually,but need it in a list.
当前浮点输出:
244107.59945389628
54722.0922075194
6765577.961772737
643320.2371350557
...
...
通缉名单输出:
[244107.59945389628,54722.0922075194,6765577.961772737,643320.2371350557,...,...]
解决方法
使用列表理解
ss=[math.pow(popsq - xpop,2) for popsq in popPrices]
,
import pandas as pd
import numpy as np
import math
import statistics
frame=[bdrc,bdmp,bdmv,bdsm] #These are sources selected and then concated for variable,popPrices.
result=pd.concat(frame)
popPrices=result["Price"]
#Grand Mean
xpop=popPrices.mean() #The mean
newList = []
for popsq in popPrices: #An attempt to have each individual sample treated with the grand mean. - success.
ss=math.pow(popsq - xpop,2)
newList.append(ss)
,
您需要将这些项目添加到列表中;现在你只是将它们分配给一个变量。试试这个:
resultList = []
for popsq in popPrices:treated with the grand mean. - success.
resultList.append(math.pow(popsq - xpop,2))
print(resultList)
,
您可以创建一个空列表并附加您的结果
result=[]
for popsq in popPrices:
ss=math.pow(popsq - xpop,2)
result.append(ss)
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