Question

运行代码时，我遇到以下错误。错误-列标签“ Avg_Threat_Score”不是唯一的。

我正在创建数据透视表，并希望将值从高到低排序。

pt = df.pivot_table(index = 'User Name',values = ['Threat Score', 'Score'], 
        aggfunc = {
                   'Threat Score': np.mean,
                   'Score' :[np.mean, lambda x: len(x.dropna())]
                  }, 
        margins = False) 

new_col =['User Name Count', 'AVG_TH_Score', 'Avg_Threat_Score']
pt.columns = [new_col]
#befor this code is working, after that now working 
df = df.reindex(pt.sort_values
                    (by = 'Avg_Threat_Score',ascending=False).index)

需要对“ Avg_Threat_Score”列的值从高到低排序

Answer 1

您需要按列表而不是嵌套列表传递新的列名称，因为大熊猫会在一个级别上创建MultiIndex。

new_col =['User Name Count', 'AVG_TH_Score', 'Avg_Threat_Score']
pt.columns = [new_col]

就像：

pt.columns = [['User Name Count', 'AVG_TH_Score', 'Avg_Threat_Score']]

ValueError：列标签“ Avg_Threat_Score”不是唯一的。
对于多索引，标签必须是一个元组，其元素与每个级别相对应。

因此使用：

pt.columns = ['User Name Count', 'AVG_TH_Score', 'Avg_Threat_Score']

示例：

df = pd.DataFrame({
        'User Name':list('ababaa'),
         'Threat Score':[4,5,4,np.nan,5,4],
         'Score':[np.nan,8,9,4,2,np.nan],
         'D':[1,3,5,7,1,0]})

pt = (df.pivot_table(index = 'User Name',values = ['Threat Score', 'Score'], 
        aggfunc = {
                   'Threat Score': np.mean,
                   'Score' :[np.mean, lambda x: len(x.dropna())]
                  }, 
        margins = False))

pt.columns = ['User Name Count', 'AVG_TH_Score', 'Avg_Threat_Score']
print (pt)
           User Name Count  AVG_TH_Score  Avg_Threat_Score
User Name                                                 
a                      2.0           5.5              4.25
b                      2.0           6.0              5.00

然后按照从Avg_Threat_Score开始的顺序进行排序，请对列User Name使用有序的Categorical，这样最后sort_values就可以工作了：

names = pt.sort_values(by = 'Avg_Threat_Score',ascending=False).index
print (names)
#Index(['b', 'a'], dtype='object', name='User Name')

df['User Name'] = pd.CategoricalIndex(df['User Name'], categories=names, ordered=True)
df = df.sort_values('User Name')

print (df)
  User Name  Threat Score  Score  D
1         b           5.0    8.0  3
3         b           NaN    4.0  7
0         a           4.0    NaN  1
2         a           4.0    9.0  5
4         a           5.0    2.0  1
5         a           4.0    NaN  0

Answer 2

pt = df.pivot_table(index = 'User Name', values = ['Threat Score', 'Score','Source IP'] ,  
                    aggfunc = {"Source IP" : 'count',
                              'Threat Score':np.mean,
                               'Score': np.mean})

pt = pt.sort_values('Threat Score', ascending = False) 
new_cols = ['Avg_Score', 'Count', 'Avg_ThreatScore']
pt.columns = new_cols

如何解决“列标签'Avg_Threat_Score'不是唯一的”。起诉熊猫

2 个答案: