按特定值排序

Question

我有一个包含文本及其 TFIDF 分数的列表：

[['penguji', 117    0.594552 Name: rank, dtype: float64], 
 ['saat', 126    0.263102 Name: rank, dtype: float64], 
 ['melakukan', 92    0.223703 Name: rank, dtype: float64], 
 ['ini', 60    0.772189 Name: rank, dtype: float64], 
 ['kebenaran', 73    0.318094 Name: rank, dtype: float64], 
 ['selain', 136    0.234254 Name: rank, dtype: float64], 
 ['khusus', 76    0.553491 Name: rank, dtype: float64], 
 ['dan', 31    0.782068 Name: rank, dtype: float64],...]

然后我想对分数进行排序，所以我这样编码：

TFIDF_Score.sort()
print('Sorted list:', TFIDF_Score)

结果是排序的文本，而实际上，预期输出是排序的分数，如下所示：

[['dan', 31    0.782068 Name: rank, dtype: float64],
 ['ini', 60    0.772189 Name: rank, dtype: float64], 
 ['penguji', 117    0.594552 Name: rank, dtype: float64],
 ['khusus', 76    0.553491 Name: rank, dtype: float64], 
 ['kebenaran', 73    0.318094 Name: rank, dtype: float64], 
 ['saat', 126    0.263102 Name: rank, dtype: float64],
 ['selain', 136    0.234254 Name: rank, dtype: float64], 
 ['melakukan', 92    0.223703 Name: rank, dtype: float64],...]

如何处理循环？还是谢谢

Answer 1

尝试使用 sorted:

print(sorted(TFIDF_Score, key=lambda x: -x[2]))

Answer 2

假设第二个元素是 pandas.Series，使用 sorted 和 key:

import pandas as pd

l = [['aaa', pd.Series([0.2])],
     ['bbb', pd.Series([0.1])]]

sorted(l, key=lambda x: x[1].values, reverse=True)

输出：

[['aaa', 0    0.2  dtype: float64], 
 ['bbb', 0    0.1  dtype: float64]]

按特定值排序

Get sorted in specific value

python

sorting

loops

list

tf-idf