[英]Finding maxima and minima at certain points Pandas Python
鉴于以下情况:
toy = pd.DataFrame({
'price': [100, 103, 107, 105, 99, 96, 98, 103],
'barrier': [102, 102, 102,102,102,102, 102, 102],
'date': ['2020-02-28', '2020-03-01', '2020-03-02','2020-03-03', '2020-03-04', '2020-
03-05', '2020-03-06', '2020-03-07']})
toy['date'] = pd.to_datetime(toy['date']) #just make datetime obj
toy['rets'] = np.log(toy['price']/toy['price'].shift(1))
toy['ret_cum'] = toy['rets'].cumsum()
toy['loop'] = [0, 103, 0, 0, 99, 0, 0, 103] #some signal
toy['inten'] = 0.0 #initialize
当循环为 99(即 0.067 ..)时,我希望toy['inten']
为max(toy['ret_cum'].iloc[1,4])
,然后min(toy['ret_cum'].iloc[5,7])
(即 -0.0408),当循环为 103 时,依此类推。
更一般地说, np.where(toy['loop'] != 0)
产生 (1,4,7)...我想检查在 1 到 4 间隔内达到的最大水平,然后是 5 到 7等等
好的,这可能有效。 它在 min 和 max 之间交替,因为没有提供其背后的特定标准。
start = -1
stop = -1
count = 0
for i in toy.index:
if stop > max(toy.index):
break
if toy.loc[i, "loop"] != 0:
if count == 0:
start = i
else:
stop = i
if count % 2 == 0:
toy.loc[i, "inten"] = toy.loc[start:stop, "ret_cum"].min()
else:
toy.loc[i, "inten"] = toy.loc[start:stop, "ret_cum"].max()
start = stop + 1
count += 1
Output -
price barrier date rets ret_cum loop inten
0 100 102 2020-02-28 NaN NaN 0 0.000000
1 103 102 2020-03-01 0.029559 0.029559 103 0.000000
2 107 102 2020-03-02 0.038100 0.067659 0 0.000000
3 105 102 2020-03-03 -0.018868 0.048790 0 0.000000
4 99 102 2020-03-04 -0.058841 -0.010050 99 0.067659
5 96 102 2020-03-05 -0.030772 -0.040822 0 0.000000
6 98 102 2020-03-06 0.020619 -0.020203 0 0.000000
7 103 102 2020-03-07 0.049762 0.029559 103 -0.040822
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.