Python系列在数据帧错误方面不明确
这是数据帧,我用它做逻辑运算,抛出如下错误。我如何克服这个问题Python系列在数据帧错误方面不明确,python,pandas,dataframe,Python,Pandas,Dataframe,这是数据帧,我用它做逻辑运算,抛出如下错误。我如何克服这个问题 Traceback (most recent call last): in <module> if( eoddf['High'][Open] > linebreakvalue): File "", line , in __nonzero__ .format(self.__class__.__name__)) ValueError: The truth value of a Series
Traceback (most recent call last):
in <module>
if( eoddf['High'][Open] > linebreakvalue):
File "", line , in __nonzero__
.format(self.__class__.__name__))
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
代码:
用于范围内打开(1,len(eoddf)):
如果(eoddf['High'][Open]>linebreakvalue):
eoddf['LBHigh']{Open]=eoddf['High'][Open]
eoddf['LBLow'][Open]=eoddf['Low'][Open]
linebreakvalue=eoddf['LBHigh'][打开]
如果(eoddf['Low'][Open]
我正试图根据需要将此MQ4代码写入Python。代码参考如下:
我还想运行这个循环,直到Open列的最后一个条目。这里是否可以使用更好的for循环或其他方法
基本上,我正在尝试将这段代码转换为Python
OLDSwing=Swing;
VALUE1=High[Highest(NULL,0,MODE_HIGH,Lines_Break,shift+1)];
VALUE2= Low[Lowest(NULL,0,MODE_LOW,Lines_Break,shift+1)];
if (OLDSwing==1 && Low[shift]<VALUE2) Swing=-1;
if (OLDSwing==-1 && High[shift]>VALUE1 ) Swing=1;
if (Swing==1)
{ HighBuffer[shift]=High[shift]; LowBuffer[shift]=Low[shift]; }
if (Swing==-1)
{ LowBuffer[shift]=High[shift]; HighBuffer[shift]=Low[shift]; }
OLDSwing=Swing;
值1=高[最高值(零,0,模式高,线断,移位+1)];
值2=低[最低(零,0,模式低,行断,移位+1)];
如果(OLDSwing==1&&Low[shift]值1)Swing=1;
如果(摆动==1)
{HighBuffer[shift]=High[shift];LowBuffer[shift]=Low[shift];}
如果(摆动==-1)
{LowBuffer[shift]=高[shift];高缓冲[shift]=低[shift];}
这方面的规则是:
- 如果价格超过前一行的高价,将绘制一条新的绿线
- 如果价格低于前一行的低价,则会画一条新的红线
- 如果价格不高于或低于前一条线,则不提取任何内容
- 如果涨势足以形成三条连续的绿线,那么只有当价格跌破最后三条绿线的最低点时,才会画出一条新的红线
- 如果抛售足以形成三条连续的红线,那么只有当价格上涨超过最后三条红线的最高点时,才会画出一条新的绿线
linebreakvalue = 320
m1 = eoddf['High'] > linebreakvalue
m2 = eoddf['Low'] > linebreakvalue
eoddf['LBHigh']= np.where(m1, eoddf['High'], eoddf['Low'])
eoddf['LBLow'] = np.where(m2, eoddf['Low'], eoddf['High'])
但如果真的需要循环:
for i, x in eoddf.iterrows():
if(eoddf.loc[i, 'High'] > linebreakvalue):
eoddf.loc[i, 'LBHigh']=eoddf.loc[i,'High']
eoddf.loc[i,'LBLow'] =eoddf.loc[i,'Low']
if(eoddf.loc[i,'Low'] < linebreakvalue):
eoddf.loc[i,'LBHigh']=eoddf.loc[i,'Low']
eoddf.loc[i,'LBLow'] =eoddf.loc[i,'High']
eoddf.iterrows()中的i,x的
如果(eoddf.loc[i,‘高’]>linebreakvalue):
eoddf.loc[i,'LBHigh']=eoddf.loc[i,'High']
eoddf.loc[i,'LBLow']=eoddf.loc[i,'Low']
如果(eoddf.loc[i,'Low']
这就是你想要的:
eoddf['LBHigh'] = df.apply(lambda x: x['High'] if x['High'] > linebreakvalue else x['Low'], axis=1)
eoddf['LBLow'] = df.apply(lambda x: x['Low'] if x['Low'] < linebreakvalue else x['High'], axis=1)
eoddf['LBHigh']=df.apply(λx:x['High']如果x['High']>linebreakvalue否则x['Low'],轴=1)
eoddf['LBLow']=df.apply(λx:x['Low'],如果x['Low']
更改<我检查了它,它工作得很好-可能问题是我的解决方案和您的for循环相同,而您的原始代码不同:(我尝试重写循环以矢量化操作。由于格式错误,能否将注释中不起作用的代码添加到答案中?此外,如果循环不起作用,是否可以从示例数据中添加预期输出?输出类似下面的蓝色和红色线,以使用低价和高价形成的蜡烛,如图所示此链接。具有此输出的数据帧准备就绪后,我将使用plotly制作图表。相同的错误回溯(上次调用):结果[i]=func(v)文件“C:\python3\Lib\site packages\nsepy\testplot.py”,第413行,在eoddf['LBHigh']=df.apply中(lambda x:x['High']如果x['High']>linebreakvalue else x['Low'],axis=1)文件“C:\python3\lib\site packages\pandas\core\generic.py”,第953行,非零格式(self.\uuuuuu class.\uuuuuuu name.\uuuuuuuuuuu))ValueError:(“序列的真值不明确。请使用a.empty、a.bool()、a.item()、a.any()或a.all(),”出现在索引2017-10-03中”)此解决方案未使用for
循环,因此您可能希望删除该部分。
print (eoddf)
Symbol Series Prev Close Open High Low Last Close \
2015-01-01 SBIN EQ 311.85 312.45 315.00 310.70 314.00 314.00
2015-01-02 SBIN EQ 314.00 314.35 318.30 314.35 315.60 315.25
2015-01-05 SBIN EQ 315.25 316.25 316.80 312.10 312.80 312.75
2015-01-06 SBIN EQ 312.75 310.00 311.10 298.70 299.90 299.90
2015-01-07 SBIN EQ 299.90 300.00 302.55 295.15 301.40 300.15
2015-01-08 SBIN EQ 300.15 305.00 306.50 302.35 305.25 304.85
2015-01-09 SBIN EQ 304.85 306.70 307.85 302.00 303.00 303.20
2015-01-12 SBIN EQ 303.20 304.15 307.80 301.10 306.90 307.10
2015-01-13 SBIN EQ 307.10 308.15 310.75 304.15 305.25 305.10
2015-01-14 SBIN EQ 305.10 304.00 307.00 302.25 305.00 304.70
2015-01-15 SBIN EQ 304.70 319.90 323.70 314.00 318.40 320.30
2015-01-16 SBIN EQ 320.30 320.00 320.30 313.10 315.25 315.45
2015-01-19 SBIN EQ 315.45 316.55 317.95 312.50 313.20 313.15
2015-01-20 SBIN EQ 313.15 314.00 319.80 314.00 318.00 318.15
2015-01-21 SBIN EQ 318.15 319.90 327.60 319.00 326.00 326.20
2015-01-22 SBIN EQ 326.20 326.90 327.60 321.80 325.20 324.65
2015-01-23 SBIN EQ 324.65 328.25 332.55 324.65 327.05 327.45
2015-01-27 SBIN EQ 327.45 329.40 332.15 322.60 331.45 330.05
2015-01-28 SBIN EQ 330.05 330.40 336.00 328.20 333.40 334.60
LBHigh LBLow
2015-01-01 310.70 315.00
2015-01-02 314.35 318.30
2015-01-05 312.10 316.80
2015-01-06 298.70 311.10
2015-01-07 295.15 302.55
2015-01-08 302.35 306.50
2015-01-09 302.00 307.85
2015-01-12 301.10 307.80
2015-01-13 304.15 310.75
2015-01-14 302.25 307.00
2015-01-15 323.70 323.70
2015-01-16 320.30 320.30
2015-01-19 312.50 317.95
2015-01-20 314.00 319.80
2015-01-21 327.60 327.60
2015-01-22 327.60 321.80
2015-01-23 332.55 324.65
2015-01-27 332.15 322.60
2015-01-28 336.00 328.20
for i, x in eoddf.iterrows():
if(eoddf.loc[i, 'High'] > linebreakvalue):
eoddf.loc[i, 'LBHigh']=eoddf.loc[i,'High']
eoddf.loc[i,'LBLow'] =eoddf.loc[i,'Low']
if(eoddf.loc[i,'Low'] < linebreakvalue):
eoddf.loc[i,'LBHigh']=eoddf.loc[i,'Low']
eoddf.loc[i,'LBLow'] =eoddf.loc[i,'High']
eoddf['LBHigh'] = df.apply(lambda x: x['High'] if x['High'] > linebreakvalue else x['Low'], axis=1)
eoddf['LBLow'] = df.apply(lambda x: x['Low'] if x['Low'] < linebreakvalue else x['High'], axis=1)