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我有一个scipy distance_matrix作为dataframe.

如何从数据框中提取每行的最小值（不包括 0.00）以及该值的关联（行、列）标签？

例如：

第一min行的将是[0.012885,'king','boy']

第二min行的将是[2.826742,'wise','bananas']

代码DataFrame：

import scipy
...
 df = pd.DataFrame(scipy.spatial.distance_matrix(w2v_df[['x1', 'x2']], 
                                                          w2v_df[['x1', 'x2']]),
                           index=w2v_df['word'],
                           columns=w2v_df['word'])
print(df)
print(df.size)

输出：

<class 'pandas.core.frame.DataFrame'>
word            king       wise      queen  ...       kind        man        boy
word                                        ...                                 
king        0.000000   7.917140  10.963772  ...   5.811759   3.180582   0.012885
wise        7.917140   0.000000   6.642557  ...  10.990575   9.957878   7.908536
queen      10.963772   6.642557   0.000000  ...  10.347096  11.126121  10.951130
trees       9.954951   3.937842   2.917539  ...  10.940161  10.948519   9.943392
lab         7.437203  11.811392  10.148030  ...   1.716404   4.612150   7.429358
prince      3.180829   9.958469  11.126762  ...   2.897802   0.000654   3.177194
monkeys    10.007491   3.958035   2.926149  ...  10.995299  11.004550   9.995942
girl        5.820748   5.026462   5.153798  ...   6.336225   6.244742   5.808014
woman      10.663214   8.143587   2.350959  ...   8.843283  10.155728  10.650332
princess    5.204497   5.744348   5.894201  ...   5.439997   5.356606   5.191617
cat         3.033364   5.678351  10.397241  ...   8.359144   6.077646   3.031699
dinosaurs   5.745362   6.422390   5.683175  ...   5.075057   5.442950   5.732531
person      9.421978  10.901532   7.192433  ...   5.081030   7.477618   9.410744
bananas     5.238502   2.826742   8.147972  ...   9.239873   7.668165   5.231329
partner     7.752175  10.135952   7.572307  ...   3.468261   5.742199   7.741316
rat         8.830544   8.633246   4.739600  ...   6.113317   7.734904   8.818027
kind        5.811759  10.990575  10.347096  ...   0.000000   2.897668   5.804801
man         3.180582   9.957878  11.126121  ...   2.897668   0.000000   3.176944
boy         0.012885   7.908536  10.951130  ...   5.804801   3.176944   0.000000

[19 rows x 19 columns]

我已经尝试了以下（仍然需要附加关联的值）：

df1 = df[all_results != 0]
df1.idxmin()
print(df1.idxmin())

出去：

word
trees          monkeys
rat              trees
person         partner
monkeys          trees
king               boy
girl             queen
princess         woman
dinosaurs         wise
lab               kind
man             prince
boy               king
woman            queen
prince             man
wise         dinosaurs
partner         person
queen            woman
bananas         person
cat           princess
kind               lab
4

1 回答 1

1

请注意，距离矩阵是对称的。所以你可以只dataframe.sort_value(by='king')为每一行使用一个例子。并采取.iloc[:,1]。或者您可以只使用 min 函数并将其存储在列表中。

我这样做了，并且对看起来像你的小数据框很有用。

     df = df.replace(0,99999) /// # OR df.replace(0,999,inplace = True)
     #get the min for per example the king
     min_king = df.king.min()
     [min_king,'king', df[df['king']==min_king].index.values[0]]

然后对块进行循环以获取所有索引

于 2019-10-04T10:02:55.997 回答