类型错误：“bool”对象不可下标 Python 3

我收到以下错误：

TypeError                                 Traceback (most recent call last)
C:\Users\levanim\Desktop\Levani Predictive\cosinesimilarity1.py in <module>()
     39 
     40 for i in meowmix_nearest_neighbors.index:
---> 41     top_ten = pd.DataFrame(similarity_matrix.ix[i,]).sort([i], 
ascending=False[1:6]).index.values
     42     meowmix_nearest_neighbors.ix[i,:] = top_ten
     43 
TypeError: 'bool' object is not subscriptable 

对于以下代码。我是 Python 新手，不太清楚如何更改语法（如果它是 python 3 语法问题）。有人遇到这种情况吗？我认为这与 ascending=False[1:6] 部分有关，并且花了一些时间将我的头撞在墙上。希望这是一个简单的修复，但还不够了解

import numpy as np
import pandas as pd
from scipy.spatial.distance import cosine


enrollments = pd.read_csv(r'C:\Users\levanim\Desktop\Levani 
Predictive\smallsample.csv')

meowmix = enrollments.fillna(0)

meowmix.ix[0:5,0:5]

def getCosine(x,y) :
    cosine = np.sum(x*y) / (np.sqrt(np.sum(x*x)) * np.sqrt(np.sum(y*y)))
    return cosine

print("done creating cosine function")

similarity_matrix = pd.DataFrame(index=meowmix.columns, 
columns=meowmix.columns)
similarity_matrix = similarity_matrix.fillna(np.nan)

similarity_matrix.ix[0:5,0:5]
print("done creating a matrix placeholder")


for i in similarity_matrix.columns:
    for j in similarity_matrix.columns:
        similarity_matrix.ix[i,j] = getCosine(meowmix[i].values, 
meowmix[j].values)

print("done looping through each column and filling in placeholder with 
cosine similarities")


meowmix_nearest_neighbors = pd.DataFrame(index=meowmix.columns,
                                        columns=['top_'+str(i+1) for i in 
range(5)])

meowmix_nearest_neighbors = meowmix_nearest_neighbors.fillna(np.nan)

print("done creating a nearest neighbor placeholder for each item")


for i in meowmix_nearest_neighbors.index:
    top_ten = pd.DataFrame(similarity_matrix.ix[i,]).sort([i], 
ascending=False[1:6]).index.values
    meowmix_nearest_neighbors.ix[i,:] = top_ten

print("done creating the top 5 neighbors for each item")

meowmix_nearest_neighbors.head()

代替

    top_ten = pd.DataFrame(similarity_matrix.ix[i,]).sort([i], 
ascending=False[1:6]).index.values

use

    top_ten = pd.DataFrame(similarity_matrix.ix[i,]).sort([i], 
ascending=False), [1:6]).index.values

（即插入),就在之后False.)

False是的值sort()方法参数，含义为“不按升序排列”，i。 e.要求下降一。所以你需要终止sort()方法参数列表与)然后划定界限第一个参数 of the DataFrame构造函数来自2nd one with , .

[1:6] is the 第二个参数DataFrame 构造函数的（用于结果帧的索引）