python - Pandas :根据两个不同的列条件选择值价格

Question

我的数据框是这样的:

 price      direction   event           High_cross  movement
-------------------------------------------------------------
 0.00225246 down        0               False       False 
 0.00225506 up          crossing up     False       False   
 0.00225347 up          0               False       False   
 0.00225345 up          0               False       False   
 0.00225613 up          0               True        movement 
 0.00225506 up          0               True        True    
 0.00225345 up          0               False       movement
 0.00225235 down        0               False       False   
 0.00224500 down        crossing down   False       False   
 0.00225266 down        0               False       False
 0.00225246 up          crossing up     False       False
 0.00225506 up          0               False       False
 0.00225506 down        crossing down   False       False

这是一个相对复杂的请求。当 event 列中有 crossing up 时，选择列的 High_cross 值为 True 的价格，然后movement 值 movement 并将其与 crossing down 之前的价格行进行比较。如果第一个价格小于第二个价格，则在新列中使用 True 语句通知它。我不知道如何开始!有什么帮助吗？如果您需要说明，请告诉我...谢谢

小修正，如果一个crossing up和一个crossing down之间没有movement，计算不应该完成!谢谢

在上面的示例中它将是:选择行

price       direction   event   High_cross  movement
----------------------------------------------------
0.00225613  up          0       True        movement 

因为 High_cross 列是 True 并且 movement 具有值 movement，从这一行取价格 0.00225613 并将其与 crossing down 事件正上方一行的价格进行比较，因此 0.00225235

它应该像这样存储结果:

 price      direction   event           High_cross  movement  triggered
----------------------------------------------------------------------
 0.00225246 down        0               False       False 
 0.00225506 up          crossing up     False       False   
 0.00225347 up          0               False       False   
 0.00225345 up          0               False       False   
 0.00225613 up          0               True        movement 
 0.00225506 up          0               True        True    
 0.00225345 up          0               False       movement
 0.00225235 down        0               False       False   
 0.00224500 down        crossing down   False       False     True
 0.00225266 down        0               False       False
 0.00225246 up          crossing up     False       False
 0.00225506 up          0               False       False
 0.00225506 down        crossing down   False       False

Answer 1

更新

通过问题更新改进

import pandas as pd

pd.set_option('precision', 8) # To see all decimals

df = pd.DataFrame({
    "price":[0.00225246,0.00225506,0.00225347,0.00225345,0.00225613,0.00225506,0.00225345,0.00225235,0.00224500,0.00225266,0.00225246,0.00225506,0.00225506],
    "direction":["down","up","up","up","up","up","up","down","down","down","up","up","down"],
    "event": [0,"crossing up",0,0,0,0,0,0,"crossing down",0,"crossing up",0,"crossing down"],
    "High_cross": [False,False,False,False,True,True,False,False,False,False,False,False,False],
    "movement": [False,False,False,False,"movement",True,"movement",False,False,False,False,False,False]
})

# Add result column
df['triggered'] = "No"

pre_row = []
match_price = None
match_price_2 = None
matched = False
start_search = False
for index,row in df.iterrows():
    if index == 0:
        pre_row = row
        continue
    if row["event"] == 'crossing up':
        start_search = True
    if start_search and row["High_cross"] == True and row["movement"] == 'movement':
        match_price = row["price"]
        matched = True
    if matched and row["event"] == 'crossing down':
        match_price_2 = pre_row["price"]
        #Only update when condition it's true
        if (match_price < match_price_2) == False: 
            df.at[index, 'triggered'] = result
        matched = False
        start_search = False
    pre_row = row

print(df)

输出

          price direction          event  High_cross  movement  triggered
 ------------------------------------------------------------------------
 0   0.00225246      down              0       False     False        No
 1   0.00225506        up    crossing up       False     False        No
 2   0.00225347        up              0       False     False        No
 3   0.00225345        up              0       False     False        No
 4   0.00225613        up              0        True  movement        No
 5   0.00225506        up              0        True      True        No
 6   0.00225345        up              0       False  movement        No
 7   0.00225235      down              0       False     False        No
 8   0.00224500      down  crossing down       False     False       Yes
 9   0.00225266      down              0       False     False        No
 10  0.00225246        up    crossing up       False     False        No
 11  0.00225506        up              0       False     False        No
 12  0.00225506      down  crossing down       False     False        No