在数据帧上应用if条件

Question

我想循环我的数据帧并选择每个月

然后我想看看一个指标是高还是低，如果是这样，只选择某些变量

我的代码如下所示：

#Sorting date range and taking top 10 values and append these to account
start_date = date(2003, 1, 1)
end_date = date(2019, 12, 1)
highest = []
lowest = []


while start_date <= end_date:
   
    end_of_month = start_date + relativedelta(months=1, days=-1) #Calculate end of month
    port = preds_vix.loc[start_date:end_of_month] #Select date range
    
    #Apply if condition to filter for high and low Signals

    if preds_vix['Signal_1'] == 'High':
        port = port[vix_high] #Select factors that perform well/badly during high vix
        
        for i in list(vix_high_short):
            port_l = port.sort_values(i)
            low = port_l.nlargest(1,['bh1m_prediction'])
        
        for i in list(vix_high_long):
            port_h = port.sort_values(i)
            high = port_h.nlargest(1,['bh1m_prediction'])
    
    
    
    elif preds_vix['Signal_1'] == 'Low':
        port = port[vix_low] #Select factors that perform well/badly during high vix
        
        for i in list(vix_low_short):
            port_l = port.sort_values(i)
            low = port_l.nlargest(1,['bh1m_prediction'])
        
        for i in list(vix_low_long):
            port_h = port.sort_values(i)
            high = port_h.nlargest(1,['bh1m_prediction'])
      
    
    
    else:
        port = port.sort_values(by = 'bh1m_prediction') #sort data conditional on target value
        top = port.nlargest(5,['preds']) #take 10 highest values
        low = port.nsmallest(5, ['preds']) #take 10 lowest values
    
    
    
    ret_h = np.mean(top['bh1m_prediction']) #calculate mean return of each month of long stocks
    ret_l = np.mean(low['bh1m_prediction']) #calculate mean return of each month of short stocks
    
    
    highest.append(ret_h) #append all values to a list
    lowest.append(ret_l)
    
    start_date = start_date + relativedelta(months=+1) #move one month forward and repeat the process

但是，我总是收到一条错误消息：

ValueError                                Traceback (most recent call last)
<ipython-input-91-4bb929bb98fb> in <module>
     12 
     13 
---> 14     if preds_vix['Signal_1'] == 'High':
     15         port = port[vix_high] #Select factors that perform well/badly during high vix
     16 

~\anaconda3\lib\site-packages\pandas\core\generic.py in __nonzero__(self)
   1477     def __nonzero__(self):
   1478         raise ValueError(
-> 1479             f"The truth value of a {type(self).__name__} is ambiguous. "
   1480             "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
   1481         )

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

是否可以在数据帧上应用if条件来选择以我的信号_1为条件的值

Answer 1

因此，如果您从错误中看到，问题的关键在于您试图验证整个列是否为true/false。这是不可能的。我们要做的是逐个检查每一行，看看它们是高还是低。我所做的是创建另一列来跟踪信号_1是高还是低，然后逐行进行

#Sorting date range and taking top 10 values and append these to account
start_date = date(2003, 1, 1)
end_date = date(2019, 12, 1)
highest = []
lowest = []
preds_vix['is_signal_high'] = preds_vix['Signal_1'] == 'High'
preds_vix['is_signal_low'] = preds_vix['Signal_1'] == 'Low'


for counter in range(0, len(preds_vix['Signal_1'])):
    while start_date <= end_date:
       
        end_of_month = start_date + relativedelta(months=1, days=-1) #Calculate end of month
        port = preds_vix.loc[start_date:end_of_month] #Select date range
        
        #Apply if condition to filter for high and low Signals
    
        if preds_vix['is_signal_high'][counter]:
            port = port[vix_high] #Select factors that perform well/badly during high vix
            
            for i in list(vix_high_short):
                port_l = port.sort_values(i)
                low = port_l.nlargest(1,['bh1m_prediction'])
            
            for i in list(vix_high_long):
                port_h = port.sort_values(i)
                high = port_h.nlargest(1,['bh1m_prediction'])
        
        
        
        elif preds_vix['is_signal_low'][counter]:
            port = port[vix_low] #Select factors that perform well/badly during high vix
            
            for i in list(vix_low_short):
                port_l = port.sort_values(i)
                low = port_l.nlargest(1,['bh1m_prediction'])
            
            for i in list(vix_low_long):
                port_h = port.sort_values(i)
                high = port_h.nlargest(1,['bh1m_prediction'])
          
        
        
        else:
            port = port.sort_values(by = 'bh1m_prediction') #sort data conditional on target value
            top = port.nlargest(5,['preds']) #take 10 highest values
            low = port.nsmallest(5, ['preds']) #take 10 lowest values
        
        
        
        ret_h = np.mean(top['bh1m_prediction']) #calculate mean return of each month of long stocks
        ret_l = np.mean(low['bh1m_prediction']) #calculate mean return of each month of short stocks
        
        
        highest.append(ret_h) #append all values to a list
        lowest.append(ret_l)
        
        start_date = start_date + relativedelta(months=+1) #move one month forward and repeat the process