ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all() with .loc

Question

给出以下 pandas DataFrame -

json_path	Reporting Group	Entity/Grouping	Entity ID	Adjusted Value (Today, No Div, USD)	Adjusted TWR (Current Quarter, No Div, USD)	Adjusted TWR (YTD, No Div, USD)	Annualized Adjusted TWR (Since Inception, No Div, USD)	Adjusted Value (No Div, USD)
data.attributes.total.children.[0].children.[0].children.[0]	Barrack Family	William and Rupert Trust	9957007	-1.44				-1.44
data.attributes.total.children.[0].children.[0].children.[0].children.[0]	Barrack Family	Cash	-	-1.44				-1.44
data.attributes.total.children.[0].children.[0].children.[1]	Barrack Family	Gratia Holdings No. 2 LLC	8413655	55491732.66	-0.971018847	-0.971018847	11.52490309	55491732.66
data.attributes.total.children.[0].children.[0].children.[1].children.[0]	Barrack Family	Investment Grade Fixed Income	-	18469768.6				18469768.6
data.attributes.total.children.[0].children.[0].children.[1].children.[1]	Barrack Family	High Yield Fixed Income	-	3668982.44	-0.205356545	-0.205356545	4.441190127	3668982.44

我正在尝试筛选 != Cash（'Entity/Grouping' 列）并且在 'Adjusted TWR (Current Quarter, No Div, USD)' 列、'Adjusted TWR (YTD, No Div, USD)' 列或 'Annualized Adjusted TWR (Since Inception, No Div, USD)' column.

代码： 我试图通过以下代码实现这一点 -

perf_asset_class_df = df[df['json_path'].str.contains(r'(?:\.children\.\[\d+\]){4}')]
perf_asset_class_df.loc[(perf_asset_class_df['Entity/Grouping']!= 'Cash') & 
                        (perf_asset_class_df['Adjusted TWR (Current Quarter, No Div, USD)'] == '') or
                        (perf_asset_class_df['Adjusted TWR (YTD, No Div, USD)'] == '') or
                        (perf_asset_class_df['Annualized Adjusted TWR (Since Inception, No Div, USD)'] == '')]
return perf_asset_class_df

问题： 我收到以下错误，表明 perf_asset_class_df.loc[(perf_asset_class_df['Entity/Grouping']!= 'Cash')...

存在问题

ValueError                                Traceback (most recent call last)
C:\Users\WILLIA~1.FOR\AppData\Local\Temp/ipykernel_18756/2689024934.py in <module>
     48     writer.save()
     49 
---> 50 xlsx_writer()

C:\Users\WILLIA~1.FOR\AppData\Local\Temp/ipykernel_18756/2689024934.py in xlsx_writer()
      1 # Function that writes Exceptions Report and API Response as a consolidated .xlsx file.
      2 def xlsx_writer():
----> 3     reporting_group_df, unknown_df, perf_asset_class_df, perf_entity_df, perf_entity_group_df = twr_exceptions_logic()
      4 
      5 #   Creating and defining filename for exceptions report

C:\Users\WILLIA~1.FOR\AppData\Local\Temp/ipykernel_18756/1522996685.py in twr_exceptions_logic()
      4 #   [LOGIC] FOR PERF. BY ASSET CLASS (EX. ILLIQUID) - STANDARD REPORT PG.4
      5     perf_asset_class_df = df[df['json_path'].str.contains(r'(?:\.children\.\[\d+\]){4}')]
----> 6     perf_asset_class_df.loc[(perf_asset_class_df['Entity/Grouping']!= 'Cash') & 
      7                             (perf_asset_class_df['Adjusted TWR (Current Quarter, No Div, USD)'] == '') or
      8                             (perf_asset_class_df['Adjusted TWR (YTD, No Div, USD)'] == '') or

~\.conda\envs\JPDevelopment\lib\site-packages\pandas\core\generic.py in __nonzero__(self)
   1533     @final
   1534     def __nonzero__(self):
-> 1535         raise ValueError(
   1536             f"The truth value of a {type(self).__name__} is ambiguous. "
   1537             "Use a.empty, a.bool(), a.item(), a.any() or a.all()."

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

我犯了一些业余错误，这很糟糕运行，想知道是否有人可以给我提示我哪里出错了？

Answer 1

使用 |，而不是 or 来组合布尔系列。

在您的情况下，您可以简化使用与所有目标列的切片上的空字符串进行比较和 any:

m1 = perf_asset_class_df.loc[(perf_asset_class_df['Entity/Grouping']!= 'Cash')
m2 = (perf_asset_class_df[['Adjusted TWR (Current Quarter, No Div, USD)', 
                           'Adjusted TWR (YTD, No Div, USD)',
                           'Annualized Adjusted TWR (Since Inception, No Div, USD)']]
                           .eq('').any(1)
                           )

perf_asset_class_df.loc[m1&m2]

注意。为清楚起见，此处使用命名掩码

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all() with .loc

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all() with .loc

python

pandas

pandas-loc