列的信号条件

Signal conditional for column

从 yahoo finance 读取 nvidia 的 ohlcv, 我正在为信号 buy/dontbuy 创建一个列,当我尝试定义哪些通过 avg>volume 测试时,所有内容要么全部 'buy' 出现,要么不购买。

df=pd.read_csv('NVDA.csv',dtype={'label':str})
df['Price%delta']=((df['Close']/df['Open'])*100)                       

df['Avg_volume']=df['Volume'].rolling(7).mean()

df['Signal']=0

for index, row in df.iterrows():
    if row['Volume'] > row['Avg_volume']:
    df['Signal']='Buy'
    else:
        df['Signal']='Dont Buy'

您没有指定要分配 'Buy''Don't buy' 的任何索引。使用 loc 代替:

for index, row in df.iterrows(): 
    if row['Volume'] > row['Avg_volume']:
        df.loc[index, 'Signal']='Buy'
    else:
        df.loc[index, 'Signal']='Dont Buy'

您根本不需要 for 循环:

mask = df["Volume"] > df["Avg_volume"] 

df.loc[mask, "Signal"] = "Buy"
df.loc[~mask, "Signal"] = 'Don't buy'

使用np.where()的向量化解决方案:

df['Signal'] = np.where(df['Volume'] > df['Avg_volume'], 'Buy', 'Dont Buy')