小编Arm*_*man的帖子

获取2D numpy数组中大于阈值的元素索引

我有一个2D numpy数组:

x = [[  1.92043482e-04   0.00000000e+00   0.00000000e+00   0.00000000e+00
    0.00000000e+00   0.00000000e+00   2.41005634e-03   0.00000000e+00
    7.19330120e-04   0.00000000e+00   0.00000000e+00   1.42886875e-04
    0.00000000e+00   0.00000000e+00   0.00000000e+00   0.00000000e+00
    0.00000000e+00   9.79279411e-05   7.88888657e-04   0.00000000e+00
    0.00000000e+00   1.40425916e-01   0.00000000e+00   1.13955893e-02
    7.36868947e-03   3.67091988e-04   0.00000000e+00   0.00000000e+00
    0.00000000e+00   0.00000000e+00   1.72037105e-03   1.72377961e-03
    0.00000000e+00   0.00000000e+00   1.19532061e-01   0.00000000e+00
    0.00000000e+00   0.00000000e+00   0.00000000e+00   3.37249481e-04
    0.00000000e+00   0.00000000e+00   0.00000000e+00   0.00000000e+00
    0.00000000e+00   0.00000000e+00   1.75111492e-03   0.00000000e+00
    0.00000000e+00   1.12639313e-02]
 [  0.00000000e+00   0.00000000e+00   1.10271735e-04   5.98736562e-04
    6.77961628e-04   7.49569659e-04   0.00000000e+00   0.00000000e+00
    2.91697850e-03   0.00000000e+00   0.00000000e+00   0.00000000e+00
    0.00000000e+00   0.00000000e+00   3.30257021e-04   2.46629275e-04
    0.00000000e+00   1.87586441e-02   6.49103144e-04   0.00000000e+00
    1.19046355e-04   0.00000000e+00   0.00000000e+00   2.69499898e-03 …
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python numpy

10
推荐指数
1
解决办法
2万
查看次数

自动标记LDA生成的主题

我正在尝试对客户反馈进行分类,并且我在python中运行了LDA并获得了10个主题的以下输出:

(0, u'0.559*"delivery" + 0.124*"area" + 0.018*"mile" + 0.016*"option" + 0.012*"partner" + 0.011*"traffic" + 0.011*"hub" + 0.011*"thanks" + 0.010*"city" + 0.009*"way"')
(1, u'0.397*"package" + 0.073*"address" + 0.055*"time" + 0.047*"customer" + 0.045*"apartment" + 0.037*"delivery" + 0.031*"number" + 0.026*"item" + 0.021*"support" + 0.018*"door"')
(2, u'0.190*"time" + 0.127*"order" + 0.113*"minute" + 0.075*"pickup" + 0.074*"restaurant" + 0.031*"food" + 0.027*"support" + 0.027*"delivery" + 0.026*"pick" + 0.018*"min"')
(3, u'0.072*"code" + 0.067*"gps" + 0.053*"map" + 0.050*"street" + 0.047*"building" + 0.043*"address" + 0.042*"navigation" + 0.039*"access" + 0.035*"point" + …
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python nlp labeling lda topic-modeling

6
推荐指数
1
解决办法
813
查看次数

如何在excel中的所有单元格中查找和替换部分公式

是一种在 Excel 公式中使用查找和替换的方法。就像我在某些单元格中有这样的公式:

GETPIVOTDATA("Sales", $A$4, "Region", "South")
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我想更换SalesNew_Sales

有可能这样做吗?

excel replace formula

3
推荐指数
2
解决办法
4万
查看次数

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python ×2

excel ×1

formula ×1

labeling ×1

lda ×1

nlp ×1

numpy ×1

replace ×1

topic-modeling ×1