在 Python/Pandas 中使用近似值查找一年后的日期

Question

我有一个 df pandas，列中只有一个“价格”和索引日期。我想在里面找到一个名为“Aprox”的新列

 aprox. = price of today - price of one year ago (or closest date from a year ago) - 
price in one year (again take aprox if exact one year price don't exist)
 for example   
 aprox. 2019-04-30 = 8 -4 -10 = -6 = aprox. 2019-04-30
                                            - aprox. 2018-01-31 - aprox.2020-07-30  

说实话，我有点挣扎......

ex. [in]:      Price
2018-01-31       4  
2019-04-30       8 
2020-07-30       10   
2020-10-31       9  
2021-01-31       14   
2021-04-30       150
2021-07-30       20
2022-10-31       14

   [out]:      Price    aprox.
2018-01-31       4  
2019-04-30       8       -6  ((8-4-10) = -6) since there is no 2018-04-30 
2020-07-30       10      -12 (10-14-8)
2020-10-31       9       ...
2021-01-31       14      ...
2021-04-30       150
2021-07-30       20
2022-10-31       14

我对此非常苦恼......甚至更多的是大约。

非常感谢！！

Answer 1

我不太清楚你想要做什么，但也许这就是你想要的：

import pandas

def last_year(x):
    """
    Return date from a year ago.
    """
    return x - pandas.DateOffset(years=1)

# Simulate the data you provided in example
dt_str = ['2018-01-31', '2019-04-30', '2020-07-30', '2020-10-31',
          '2021-01-31', '2021-04-30', '2021-07-30', '2022-10-31']
dates = [pandas.Timestamp(x) for x in dt_str]
df = pandas.DataFrame([4, 8, 10, 9, 14, 150, 20, 14], columns=['Price'], index=dates)

# This is the code that does the work
for dt, value in df['Price'].iteritems():
    df.loc[dt, 'approx'] = value - df['Price'].asof(last_year(dt))

这给了我以下结果：

In [147]: df
Out[147]:
              Price  approx
2018-01-31      4     NaN
2019-04-30      8     4.0
2020-07-30     10     2.0
2020-10-31      9     1.0
2021-01-31     14     6.0
2021-04-30    150   142.0
2021-07-30     20    10.0
2022-10-31     14    -6.0

底线是，对于这种类型的操作，您不能只使用apply 操作，因为您需要索引和值。