大熊貓在數據框中的列表理解

Question

如果滿足某些條件，我想在當前存儲在第（row + 1）行中的第二天的開放價格中提取價格並將其存儲在新列中。

df['b']='' 

df['shift']='' 

df['shift']=df['open'].shift(-1) 

df['b']=df[x for x in df['shift'] if df["MA10"]>df["MA100"]] 

Answer 1

有幾種方法。使用apply：

>>> df = pd.read_csv("bondstack.csv") 
>>> df["shift"] = df["open"].shift(-1) 
>>> df["b"] = df.apply(lambda row: row["shift"] if row["MA10"] > row["MA100"] else np.nan, axis=1) 

產生

>>> df[["MA10", "MA100", "shift", "b"]][:10] 
     MA10  MA100  shift   b 
0 16.915625 17.405625 16.734375  NaN 
1 16.871875 17.358750 17.171875  NaN 
2 16.893750 17.317187 17.359375  NaN 
3 16.950000 17.279062 17.359375  NaN 
4 17.137500 17.254062 18.640625  NaN 
5 17.365625 17.229063 18.921875 18.921875 
6 17.550000 17.200312 18.296875 18.296875 
7 17.681250 17.177500 18.640625 18.640625 
8 17.812500 17.159375 18.609375 18.609375 
9 17.943750 17.142813 18.234375 18.234375 

對於更量化的方法，你可以使用

>>> df = pd.read_csv("bondstack.csv") 
>>> df["b"] = np.nan 
>>> df["b"][df["MA10"] > df["MA100"]] = df["open"].shift(-1) 

或我的首選方法：

>>> df = pd.read_csv("bondstack.csv") 
>>> df["b"] = df["open"].shift(-1).where(df["MA10"] > df["MA100"]) 

Answer 2

修改DSM的方法3，說明在np.where明確真/假值：

#numpy.where(condition, x, y) 
df["b"] = np.where(df["MA10"] > df["MA100"], df["open"].shift(-1), np.nan) 

使用明確列表理解：

#[xv if c else yv for (c,xv,yv) in zip(condition,x,y)]  #np.where documentation 
df['b'] = [ xv if c else np.nan for (c,xv) in zip(df["MA10"]> df["MA100"], df["open"].shift(-1))]