ValueError:太多的值无法打开Panda

Question

我有以下代码。然而，我在执行相同的操作时出现了错误。我想要这个函数来计算日程日期，并将其输出到一个新的数据帧。错误似乎在for循环中。我是新手，所以只是想弄清楚

import QuantLib as ql
import pandas as pd
import numpy as np
import datetime
from dateutil.parser import parse
data = pd.read_excel (r'C:UsersAvishenDesktopPythonBONDDATA.xlsx')
for ISIN,issuedate,maturitydate in data:
issueDate = ql.Date(issuedate, '%d-%m-%Y')
maturityDate = ql.Date(maturitydate, '%d-%m-%Y')
tenor = ql.Period(ql.Semiannual)
day_count = ql.Thirty360
calendar = ql.UnitedStates()
businessConvention = ql.Unadjusted
dateGeneration = ql.DateGeneration.Backward
monthEnd = False
# Dates in Bond Period
df['Test']= df['t'].apply(ISIN)
df['Test']= df['t1'].apply(ql.Schedule (issueDate, maturityDate, tenor, calendar, businessConvention,businessConvention , dateGeneration, monthEnd))
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-14-b6dc0a0bd926> in <module>
8 
9 
---> 10 for ISIN,issuedate,maturitydate in data:
11     issueDate = ql.Date(issuedate, '%d-%m-%Y')
12     maturityDate = ql.Date(maturitydate, '%d-%m-%Y')
ValueError: too many values to unpack (expected 3)

期望输出

t       t1
Test1   Date(22,10,2019)
Test1   Date(8,2,2020)
Test1   Date(8,8,2020)
Test1   Date(8,2,2021)
Test1   Date(8,8,2021)
Test1   Date(8,2,2022)
Test1   Date(8,8,2022)
Test1   Date(8,2,2023)
Test1   Date(8,8,2023)
Test2   Date(31,7,2020)
Test2   Date(21,9,2020)
Test2   Date(21,3,2021)
Test2   Date(21,9,2021)
Test2   Date(21,3,2022)
Test2   Date(21,9,2022)
Test2   Date(21,3,2023)
Test2   Date(21,9,2023)
Test2   Date(21,3,2024)
Test2   Date(21,9,2024)
Test2   Date(21,3,2025)

Answer 1

我认为您想要做的是逐行修改数据帧(如果有更多的数据帧，可能会有更好的解决方案(：

df['new_issueDate'] = df['issuedate'].apply(lambda row: ql.Date(row, '%d-%m-%Y')
df['new_maturityDate'] = df['maturityDate'].apply(lambda row: ql.Date(row, '%d-%m-%Y')

编辑：您只想遍历行：

t_list = []
t1_list = []
for _, row in data.iterrows():
issueDate = ql.Date(row['issuedate'], '%d-%m-%Y')
maturityDate = ql.Date(row['maturitydate'], '%d-%m-%Y')
tenor = ql.Period(ql.Semiannual)
day_count = ql.Thirty360
calendar = ql.UnitedStates()
businessConvention = ql.Unadjusted
dateGeneration = ql.DateGeneration.Backward
monthEnd = False
t_list.append(row['ISIN'])
t1_list.append(ql.Schedule(issueDate, maturityDate, tenor, calendar, businessConvention, businessConvention, dateGeneration, monthEnd))
new_df = pd.DataFrame({'t':t_list, 't1':t1_list})

还有其他方法可以逐行附加到数据帧，但这种方法也很好。