如何将列表中的指定值除以循环下的整个列表？

Question

我有一个循环打印出一个“源”。 在该源下是一个特定值，需要除以另一个值数组。 此值与源相关

代码：

for matchlow in lowest:
lowestform = (dfprice[dfprice.Price.isin(matchlow)])
print (lowestform)
for matchloww in arraylowest:
    for matchhighh in arrayhighest:
        print (matchloww / matchhighh)

输出：

Source
[0.58309556]
[0.6017244]
[0.61525167]
[0.67711764]
[0.68032508]
[0.72635714]
[0.74874422]
[0.76183104]
[0.76589366]
[0.60918449]
[0.62864682]
[0.64277933]
[0.70741331]
[0.71076426]
[0.7588559]
[0.78224462]
[0.79591697]
[0.80016135]
[0.62298038]
[0.64288347]
[0.65733604]
[0.72343375]
[0.72686058]
[0.77604133]
[0.79995973]
[0.81394171]
[0.81828221]
[0.62421753]
[0.64416014]
[0.65864141]
[0.72487037]
[0.72830402]
[0.77758243]
[0.80154832]
[0.81555807]
[0.81990719]
[0.62480561]
[0.64476701]
[0.65926191]
[0.72555328]
[0.72899016]
[0.77831499]
[0.80230347]
[0.81632641]
[0.82067963]
[0.6249058]
[0.6448704]
[0.65936763]
[0.72566963]
[0.72910705]
[0.7784398]
[0.80243212]
[0.81645732]
[0.82081123]
[0.62604711]
[0.64604817]
[0.66057188]
[0.72699497]
[0.73043867]
[0.77986152]
[0.80389766]
[0.81794847]
[0.82231034]
[0.62615601]
[0.64616055]
[0.66068679]
[0.72712143]
[0.73056573]
[0.77999718]
[0.8040375]
[0.81809076]
[0.82245338]
[0.627428]
[0.64747319]
[0.66202893]
[0.72859853]
[0.73204983]
[0.78158169]
[0.80567085]
[0.81975265]
[0.82412414]
Source2
[0.58309556]
[0.6017244]
[0.61525167]
[0.67711764]
[0.68032508]
[0.72635714]
[0.74874422]
[0.76183104]
[0.76589366]
[0.60918449]
[0.62864682]
[0.64277933]
[0.70741331]
[0.71076426]
[0.7588559]
[0.78224462]
[0.79591697]
[0.80016135]
[0.62298038]
[0.64288347]
[0.65733604]
[0.72343375]
[0.72686058]
[0.77604133]
[0.79995973]
[0.81394171]
[0.81828221]
[0.62421753]
[0.64416014]
[0.65864141]
[0.72487037]
[0.72830402]
[0.77758243]
[0.80154832]
[0.81555807]
[0.81990719]
[0.62480561]
[0.64476701]
[0.65926191]
[0.72555328]
[0.72899016]
[0.77831499]
[0.80230347]
[0.81632641]
[0.82067963]
[0.6249058]
[0.6448704]
[0.65936763]
[0.72566963]
[0.72910705]
[0.7784398]
[0.80243212]
[0.81645732]
[0.82081123]
[0.62604711]
[0.64604817]
[0.66057188]
[0.72699497]
[0.73043867]
[0.77986152]
[0.80389766]
[0.81794847]
[0.82231034]
[0.62615601]
[0.64616055]
[0.66068679]
[0.72712143]
[0.73056573]
[0.77999718]
[0.8040375]
[0.81809076]
[0.82245338]
[0.627428]
[0.64747319]
[0.66202893]
[0.72859853]
[0.73204983]
[0.78158169]
[0.80567085]
[0.81975265]
[0.82412414]
 Source3
[0.58309556]
[0.6017244]
[0.61525167]
[0.67711764]
[0.68032508]
[0.72635714]
[0.74874422]
[0.76183104]
[0.76589366]
[0.60918449]
[0.62864682]
[0.64277933]
[0.70741331]
[0.71076426]
[0.7588559]
[0.78224462]
[0.79591697]
[0.80016135]
[0.62298038]
[0.64288347]
[0.65733604]
[0.72343375]
[0.72686058]
[0.77604133]
[0.79995973]
[0.81394171]
[0.81828221]
[0.62421753]
[0.64416014]
[0.65864141]
[0.72487037]
[0.72830402]
[0.77758243]
[0.80154832]
[0.81555807]
[0.81990719]
[0.62480561]
[0.64476701]
[0.65926191]
[0.72555328]
[0.72899016]
[0.77831499]
[0.80230347]
[0.81632641]
[0.82067963]
[0.6249058]
[0.6448704]
[0.65936763]
[0.72566963]
[0.72910705]
[0.7784398]
[0.80243212]
[0.81645732]
[0.82081123]
[0.62604711]
[0.64604817]
[0.66057188]
[0.72699497]
[0.73043867]
[0.77986152]
[0.80389766]
[0.81794847]
[0.82231034]
[0.62615601]
[0.64616055]
[0.66068679]
[0.72712143]
[0.73056573]
[0.77999718]
[0.8040375]
[0.81809076]
[0.82245338]
[0.627428]
[0.64747319]
[0.66202893]
[0.72859853]
[0.73204983]
[0.78158169]
[0.80567085]
[0.81975265]
[0.82412414]
Source5
[0.58309556]
[0.6017244]
[0.61525167]
[0.67711764]
[0.68032508]
[0.72635714]
[0.74874422]
[0.76183104]
[0.76589366]
[0.60918449]
[0.62864682]
[0.64277933]
[0.70741331]
[0.71076426]
[0.7588559]
[0.78224462]
[0.79591697]
[0.80016135]
[0.62298038]
[0.64288347]
[0.65733604]
[0.72343375]
[0.72686058]
[0.77604133]
[0.79995973]
[0.81394171]
[0.81828221]
[0.62421753]
[0.64416014]
[0.65864141]
[0.72487037]
[0.72830402]
[0.77758243]
[0.80154832]
[0.81555807]
[0.81990719]
[0.62480561]
[0.64476701]
[0.65926191]
[0.72555328]
[0.72899016]
[0.77831499]
[0.80230347]
[0.81632641]
[0.82067963]
[0.6249058]
[0.6448704]
[0.65936763]
[0.72566963]
[0.72910705]
[0.7784398]
[0.80243212]
[0.81645732]
[0.82081123]
[0.62604711]
[0.64604817]
[0.66057188]
[0.72699497]
[0.73043867]
[0.77986152]
[0.80389766]
[0.81794847]
[0.82231034]
[0.62615601]
[0.64616055]
[0.66068679]
[0.72712143]
[0.73056573]
[0.77999718]
[0.8040375]
[0.81809076]
[0.82245338]
[0.627428]
[0.64747319]
[0.66202893]
[0.72859853]
[0.73204983]
[0.78158169]
[0.80567085]
[0.81975265]
[0.82412414]

它会一直传到源代码9

期望输出：

 Source
    [0.58309556]
    [0.6017244]
    [0.61525167]
    [0.67711764]
    [0.68032508]
    [0.72635714]
    [0.74874422]
    [0.76183104]
    [0.76589366]
Source2
    [0.60918449]
    [0.62864682]
    [0.64277933]
    [0.70741331]
    [0.71076426]
    [0.7588559]
    [0.78224462]
    [0.79591697]
    [0.80016135]
Source3
    [0.62298038]
    [0.64288347]
    [0.65733604]
    [0.72343375]
    [0.72686058]
    [0.77604133]
    [0.79995973]
    [0.81394171]
    [0.81828221]

我想这一个去所有的方式通过9也，但在它的不同数字在第一个名单。 我该怎么做呢？提前谢谢

Answer 1

您可以使用np.divide.outer一次性获得整个比率表

table = np.divide.outer(arraylowest, arrayhighest)
for i, row in enumerate(table):
    print(f"Source{i+1}", row)

这对数组和列表都有效

如果只需要特定行：

arraylowest[i] / arrayhighest

这只适用于阵列