python – 遍历行以查看哪个值首先出现

2023年12月31日 163次阅读

使用Pandas时,我可以使用.shift()检查先前和后续行以查看是否满足某些条件.

如果我需要查看是否满足条件,在我与之比较的行之后可能是100行或更多,该怎么办？我知道在数据帧中循环不是最有效的,但有人可以请帮助以下示例.

当df [‘reversal’]列有一个信号时 – 根据下面的例子在14:00显示6.0 – 我想知道在14:00的行之后首先看到以下哪一个：

> df.price,其值为df.reversal 1(我们可以看到这是在20:00被命中为6 1 = 7)
> df.price,其值为df.reversal – df.reversal(在此示例中没有命中,因为价格未达到6 – 6 = 0)

《python – 遍历行以查看哪个值首先出现》

这是所需的输出,蓝色的单元格显示了我想要看到的内容.新列应显示目标被击中的时间(根据此示例)或目标未命中(如果此示例中的价格达到0).

《python – 遍历行以查看哪个值首先出现》

请参阅下面的df.to_dict()以重现：

{'move_start': {datetime.time(9, 0): nan,
  datetime.time(10, 0): nan,
  datetime.time(11, 0): nan,
  datetime.time(12, 0): nan,
  datetime.time(13, 0): nan,
  datetime.time(14, 0): datetime.time(9, 0),
  datetime.time(15, 0): nan,
  datetime.time(16, 0): nan,
  datetime.time(17, 0): nan,
  datetime.time(18, 0): nan,
  datetime.time(19, 0): nan,
  datetime.time(20, 0): nan},
 'price': {datetime.time(9, 0): 1,
  datetime.time(10, 0): 2,
  datetime.time(11, 0): 3,
  datetime.time(12, 0): 4,
  datetime.time(13, 0): 5,
  datetime.time(14, 0): 6,
  datetime.time(15, 0): 5,
  datetime.time(16, 0): 4,
  datetime.time(17, 0): 3,
  datetime.time(18, 0): 2,
  datetime.time(19, 0): 4,
  datetime.time(20, 0): 7},
 'reversal': {datetime.time(9, 0): nan,
  datetime.time(10, 0): nan,
  datetime.time(11, 0): nan,
  datetime.time(12, 0): nan,
  datetime.time(13, 0): nan,
  datetime.time(14, 0): 6.0,
  datetime.time(15, 0): nan,
  datetime.time(16, 0): nan,
  datetime.time(17, 0): nan,
  datetime.time(18, 0): nan,
  datetime.time(19, 0): nan,
  datetime.time(20, 0): nan}}

最佳答案 认为……让它变得更好,更干净

import datetime,numpy as np,pandas as pd
nan = np.nan

a = pd.DataFrame({'move_start': {datetime.time(9, 0): nan,   datetime.time(10, 0): nan,   datetime.time(11, 0): nan,   datetime.time(12, 0): nan,   datetime.time(13, 0): nan,   datetime.time(14, 0): datetime.time(9, 0),   datetime.time(15, 0): nan,   datetime.time(16, 0): nan,   datetime.time(17, 0): nan,   datetime.time(18, 0): nan,   datetime.time(19, 0): nan,   datetime.time(20, 0): nan},  'price': {datetime.time(9, 0): 1,   datetime.time(10, 0): 0,   datetime.time(11, 0): 3,   datetime.time(12, 0): 4,   datetime.time(13, 0): 7,   datetime.time(14, 0): 6,   datetime.time(15, 0): 5,   datetime.time(16, 0): 4,   datetime.time(17, 0): 0,   datetime.time(18, 0): 2,   datetime.time(19, 0): 4,   datetime.time(20, 0): 7},  'reversal': {datetime.time(9, 0): nan,   datetime.time(10, 0): nan,   datetime.time(11, 0): nan,   datetime.time(12, 0): nan,   datetime.time(13, 0): nan,
  datetime.time(14, 0): 6.0,   datetime.time(15, 0): nan,   datetime.time(16, 0): nan,   datetime.time(17, 0): nan,   datetime.time(18, 0): nan,   datetime.time(19, 0): nan,   datetime.time(20, 0): nan}})


a['target_hit']=nan;
a['target_miss']=nan;
a['reversal1']=a['reversal']+1;
a['reversal2']=a['reversal']-a['reversal'];
a.sort_index(1,inplace=True);

hit = a.ix[:,:-2].dropna()

takeBoth = False
targetIsHit,targetIsMiss = False,False

if takeBoth:

    targetHit = a[(hit['reversal1'].values==a['price'].values) & (hit['reversal1'].index.values<a['price'].index.values)];
    targetMiss = a[(hit['reversal2'].values==a['price'].values) & (hit['reversal2'].index.values<a['price'].index.values)];

    targetIsHit,targetIsMiss = not targetHit.empty, not targetMiss.empty

else:

    targetHit = a[(hit['reversal1'].values==a['price'].values) & (hit['reversal1'].index.values<a['price'].index.values)];
    targetIsHit = not targetHit.empty
    if not targetIsHit:
         targetMiss = a[(hit['reversal2'].values==a['price'].values) & (hit['reversal2'].index.values<a['price'].index.values)]; 
         targetIsMiss = not targetMiss.empty

if targetIsHit:a.loc[hit.index.values,"target_hit"] = targetHit.index.values;
if targetIsMiss:a.loc[hit.index.values,"target_miss"] = targetMiss.index.values;

print '#'*50
print a
'''
##################################################
         move_start  price  reversal  reversal1  reversal2 target_hit  \
09:00:00        NaN      1       NaN        NaN        NaN        NaN   
10:00:00        NaN      0       NaN        NaN        NaN        NaN   
11:00:00        NaN      3       NaN        NaN        NaN        NaN   
12:00:00        NaN      4       NaN        NaN        NaN        NaN   
13:00:00        NaN      7       NaN        NaN        NaN        NaN   
14:00:00   09:00:00      6       6.0        7.0        0.0   20:00:00   
15:00:00        NaN      5       NaN        NaN        NaN        NaN   
16:00:00        NaN      4       NaN        NaN        NaN        NaN   
17:00:00        NaN      0       NaN        NaN        NaN        NaN   
18:00:00        NaN      2       NaN        NaN        NaN        NaN   
19:00:00        NaN      4       NaN        NaN        NaN        NaN   
20:00:00        NaN      7       NaN        NaN        NaN        NaN   

          target_miss  
09:00:00          NaN  
10:00:00          NaN  
11:00:00          NaN  
12:00:00          NaN  
13:00:00          NaN  
14:00:00          NaN  
15:00:00          NaN  
16:00:00          NaN  
17:00:00          NaN  
18:00:00          NaN  
19:00:00          NaN  
20:00:00          NaN
'''

PS：作为典型的pythonist我很懒,喜欢处理包含大多数典型问题的普通输入/输出,所以你从开始做出令人讨厌的df,不仅仅是写它XD …关于阅读文本…人们倾向于写,写和写.通常是它的简单问题,但是hella wroten,所以我不理解yota xD.然后就像“WTF他想要在这里吗？！”.

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