我想在嵌套循环中计算以下函数并保持这种方式：
Calc_Value = value_a(2D) - (values_b(0D) + values_b(1D))/10000
导致值：
1.1274875
定义为：
value_a(2D) corresponds to type **a**, year **2D** and value **1.1275**
value_b(0D) corresponds to type **b**, year **0D** and value **0**
value_b(1D) corresponds to type **b**, year **1D** and value **0.125**
不知怎的，我不确定如何定义下面的函数来使用值b正确的两个值如上所示???
有一种方法可以直接使用pandas（Pandas Version），但想使用我的嵌套方式。
更新：
我改变了我的功能并获得了适当的值，但仍然存在我多次而不是一次计算值的问题。我得到每个值b的值a，直到计算出正确的值，这是最后一个值。我只想保留最后一个值。
1.1275 1.1275 1.1275 1.1275 1.1275 1.1275 1.1275 1.1275 1.1275 1.1275 1.1275 1.1275 1.1275 1.1275 1.1275 1.1275 1.1274875 --> **Only this value should be shown**
代码如下所示：
import pandas as pd
def CalcValue(year, a, b):
normalization = 0.0
value_0D = 0.0
value_1D = 0.0
Calc = 0.0
normalization = 10000.0
if year == "0D":
value_0D = b
elif year == "1D":
value_1D = b
Calc = a-(value_0D+value_1D)/normalization
return Calc
data = pd.read_csv('C:/Users/mcm/Desktop/Book1.csv').fillna('')
pd_date = pd.DatetimeIndex(data['date'].values)
data['date'] = pd_date
index_data = data.set_index('date')
for current_date in index_data.index.unique():
print('calculating date: ' + str(current_date))
for index, row in index_data.iterrows():
if index == current_date:
for index2, row2 in index_data.iterrows():
if index2 == current_date:
if row['type'] in {'a', 'b'} and row2['type'] in {'a', 'b'}:
if row['type'] != row2['type'] and row['type'] != 'a' and row2['type'] != 'b':
test = CalcValue(row['year'], row2['value'],row['value'])
print(test)
数据如下所示：
date type year value
2015-02-09 a 2D 1.1275
2015-02-09 b 10M 58.125
2015-02-09 b 11M 68.375
2015-02-09 b 1M 3.345
2015-02-09 b 1W 0.89
2015-02-09 b 1Y 79.375
2015-02-09 b 2M 7.535
2015-02-09 b 2W 1.8
2015-02-09 b 3M 11.61
2015-02-09 b 3W 2.48
2015-02-09 b 4M 16.2
2015-02-09 b 5M 21.65
2015-02-09 b 6M 27.1
2015-02-09 b 7M 33.625
2015-02-09 b 8M 41.375
2015-02-09 b 9M 49.5
2015-02-09 b 0D 0
2015-02-09 b 1D 0.125
2015-02-09 c 2Y -28.5
2015-02-09 c 3Y -28.75
2015-02-09 c 4Y -28
2015-02-09 c 5Y -27.5
2015-02-09 c 6Y -27
2015-02-09 c 7Y -26.75
2015-02-09 c 8Y -26.25
2015-02-09 c 9Y -25.5
2015-02-09 c 10Y -25
2015-02-10 a 2D 1.1297
2015-02-10 b 10M 60.5
2015-02-10 b 11M 70.375
2015-02-10 b 1M 3.32
2015-02-10 b 1W 0.84
2015-02-10 b 1Y 81.625
2015-02-10 b 2M 7.54
2015-02-10 b 2W 1.74
2015-02-10 b 3M 11.745
2015-02-10 b 3W 2.45
2015-02-10 b 4M 16.4
2015-02-10 b 5M 22.05
2015-02-10 b 6M 28.1
2015-02-10 b 7M 35.375
2015-02-10 b 8M 42.625
2015-02-10 b 9M 51
2015-02-10 b 0D 0.105
2015-02-10 b 1D 0.11
2015-02-10 c 2Y -29.5
2015-02-10 c 3Y -29.75
2015-02-10 c 4Y -29.5
2015-02-10 c 5Y -29
2015-02-10 c 6Y -28.5
2015-02-10 c 7Y -28
2015-02-10 c 8Y -27.5
2015-02-10 c 9Y -26.75
2015-02-10 c 10Y -26.25
答案 0 :(得分：0)
这将是最小的：
for i in range(20):
print(i)
#print(i)
这包括一个条件：
for i in range(20):
if True:
test = i
print(test)
#print(test)
您的问题只是从循环中获取最后一个计算值 - 您已经实现了这一点，但是您正在打印循环中的每个计算值，即每个满足条件的迭代。快速解决方案是在循环后打印（在上面的print（）上交换注释）。
一旦找到了您想要的东西，通常会停止循环。否则，您将使用另一个变量来存储结果：
keepitthatway = None
for i in range(42):
if i==7:
keepitthatway = i
# keep on iterating if necessary or
#break
print(i)
print(keepitthatway)
有很多Python编程教程，例如https://wiki.python.org/moin/ForLoop。看看; - ）
关于Minimal, Complete, and Verifiable example，这也会奏效。虽然不是最小的，但它类似于您的代码结构：
for current_date in range(2):
print('calculating something...')
for index, row in enumerate(range(20)):
if index == current_date:
for index2, row2 in enumerate(range(20)):
if True:
if True:
if True:
test = index
print(test)
#print(test)
仅限制数据集本来就是一项改进：
import pandas as pd
# pretend to be the csv file
import io
csv = io.StringIO("""date\ttype\tyear\tvalue
2015-02-09\ta\t2D\t1.1275
2015-02-09\tb\t10M\t58.125
2015-02-09\tc\t2Y\t-28.5
2015-02-10\ta\t2D\t1.1297
2015-02-10\tb\t10M\t60.5
2015-02-10\tc\t2Y\t-29.5
2015-02-10\tc\t10Y\t-26.25
""")
def CalcValue(year, a, b):
normalization = 0.0
value_0D = 0.0
value_1D = 0.0
Calc = 0.0
normalization = 10000.0
if year == "0D":
value_0D = b
elif year == "1D":
value_1D = b
Calc = a-(value_0D+value_1D)/normalization
return Calc
data = pd.read_csv(csv, sep="\t").fillna('')
#print(data)
#import sys;sys.exit()
pd_date = pd.DatetimeIndex(data['date'].values)
data['date'] = pd_date
index_data = data.set_index('date')
for current_date in index_data.index.unique():
print('calculating date: ' + str(current_date))
for index, row in index_data.iterrows():
if index == current_date:
for index2, row2 in index_data.iterrows():
if index2 == current_date:
if row['type'] in {'a', 'b'} and row2['type'] in {'a', 'b'}:
if row['type'] != row2['type'] and row['type'] != 'a' and row2['type'] != 'b':
test = CalcValue(row['year'], row2['value'],row['value'])
print(test)
打印
calculating date: 2015-02-09 00:00:00
1.1275
calculating date: 2015-02-10 00:00:00
1.1297
（当然这些值与您问题中的值不同，因为数据集已被修改）