我有以下各列的时间序列数据框。我试图弄清楚：
如果df ['PH'] == 1，那么我需要找到df ['pivot_low_1'] == 1的先前日期，并提取该日期的df ['low']值。因此，对于df ['PH'] == 1的2010-01-12，我需要在2010-01-07上标识先前的非零df ['pivot_low_1'] == 1并获取df ['low '] == 1127.00000。
low pivot_low_1 PH
date
2010-01-04 1114.00000 1 0
2010-01-05 1125.00000 0 0
2010-01-06 1127.25000 0 0
2010-01-07 1127.00000 1 0
2010-01-08 1131.00000 0 0
2010-01-11 1137.75000 0 0
2010-01-12 1127.75000 1 1
2010-01-13 1129.25000 0 0
2010-01-14 1138.25000 0 0
2010-01-15 1127.50000 1 0
2010-01-18 1129.50000 0 0
2010-01-19 1126.25000 0 0
2010-01-20 1125.25000 0 0
2010-01-21 1108.50000 0 0
2010-01-22 1086.25000 1 0
2010-01-25 1089.75000 0 0
2010-01-26 1081.00000 0 0
2010-01-27 1078.50000 0 0
2010-01-28 1074.25000 0 0
2010-01-29 1066.50000 1 1
2010-02-01 1068.00000 0 0
由于您想要同一数据框中的一列，但输出仅对应于某些行，因此我将每隔一列替换为nan值，
data = pd.read_csv('file.csv')
data.columns=['low', 'pivot_low_1', 'PH']
count = 0
l = list()
new=list()
for index, row in data.iterrows():
if row['pivot_low_1']==1:
l.append(count)
if (row['PH']==1) and (row['pivot_low_1']==1):
new.append(data.iloc[l[len(l)-2]].low)
elif (row['PH']==1):
new.append(data.iloc[l[len(l)-1]].low)
elif (row['PH']==0):
new.append(np.nan)
count+=1
data['new'] = new
data
输出如下图所示，https://imgur.com/a/IqowZHZ，希望对您有所帮助
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