python - 将导入的日期从.txt转换为日期格式python

Question

我在导入的 .txt 文件中转换日期时遇到问题，我想知道我做错了什么。

我通过以下方式导入数据：

df_TradingMonthlyDates = pd.read_csv(TradingMonthlyDates, dtype=str, sep=',') # header=True,

它看起来像下表（日期代表月份的开始/结束并有一个标题Date）：

           Date
0    2008-12-30
1    2008-12-31
2    2009-01-01
3    2009-01-02
4    2009-01-29
..          ...

557  2020-06-29
558  2020-06-30
559  2020-07-01
560  2020-07-02
561  2020-07-30
..          ...

624  2021-11-30
625  2021-12-01
626  2021-12-02
627  2021-12-30
628  2021-12-31

[629 rows x 1 columns]
<class 'pandas.core.frame.DataFrame'>

然后我计算今天的日期：

df_EndDate = datetime.now().date()

我正在尝试在此函数中应用上述数据以获取给定日期之前的最接近日期（在我的情况下，给定日期 = 今天的日期）：

# https://stackoverflow.com/questions/32237862/find-the-closest-date-to-a-given-date
def nearest(items, pivot):
    return min([i for i in items if i < pivot], key=lambda x: abs(x - pivot))

date_output = nearest(df_TradingMonthlyDates, df_EndDate)
# date_output should be = 2020-07-02 given today's date of 2020-07-12

我收到的错误消息df_TradingMonthlyDates是不是日期格式。因此，我尝试将数据框转换为日期时间格式，但无法使其正常工作。

我尝试将数据转换为日期格式：

# df_TradingMonthlyDates["Date"] = pd.to_datetime(df_TradingMonthlyDates["Date"], format="%Y-%m-%d")
# df_TradingMonthlyDates = datetime.strptime(df_TradingMonthlyDates, "%Y-%m-%d").date()
# df_TradingMonthlyDates['Date'] = df_TradingMonthlyDates['Date'].apply(lambda x: pd.to_datetime(x[0], format="%Y-%m-%d"))
# df_TradingMonthlyDates = df_TradingMonthlyDates.iloc[1:]
# print(df_TradingMonthlyDates)
# df_TradingMonthlyDates = datetime.strptime(str(df_TradingMonthlyDates), "%Y-%m-%d").date()
# for line in split_source[1:]: # skip the first line

代码：

import pandas as pd
from datetime import datetime
 
# Version 1

TradingMonthlyDates = "G:/MonthlyDates.txt"

# Import file where all the first/end month date exists
df_TradingMonthlyDates = pd.read_csv(TradingMonthlyDates, dtype=str, sep=',') # header=True,
print(df_TradingMonthlyDates)

# https://community.dataquest.io/t/datetime-and-conversion/213425
# df_TradingMonthlyDates["Date"] = pd.to_datetime(df_TradingMonthlyDates["Date"], format="%Y-%m-%d")
# df_TradingMonthlyDates = datetime.strptime(df_TradingMonthlyDates, "%Y-%m-%d").date()
# df_TradingMonthlyDates['Date'] = df_TradingMonthlyDates['Date'].apply(lambda x: pd.to_datetime(x[0], format="%Y-%m-%d"))
# df_TradingMonthlyDates = df_TradingMonthlyDates.iloc[1:]
# print(df_TradingMonthlyDates)
# df_TradingMonthlyDates = datetime.strptime(str(df_TradingMonthlyDates), "%Y-%m-%d").date()
# for line in split_source[1:]: # skip the first line # maybe header is the problem
print(type(df_TradingMonthlyDates))
df_TradingMonthlyDates = df_TradingMonthlyDates.datetime.strptime(df_TradingMonthlyDates, "%Y-%m-%d")
df_TradingMonthlyDates = df_TradingMonthlyDates.time()


print(df_TradingMonthlyDates)

df_EndDate = datetime.now().date()
print(type(df_EndDate))



# https://stackoverflow.com/questions/32237862/find-the-closest-date-to-a-given-date
def nearest(items, pivot):
    return min([i for i in items if i < pivot], key=lambda x: abs(x - pivot))

date_output = nearest(df_TradingMonthlyDates, df_EndDate)

---

错误消息因我尝试转换数据类型的方式而异，但我认为它们都注意到我的日期格式不成功：

df_TradingMonthlyDates = df_TradingMonthlyDates.datetime.strptime(df_TradingMonthlyDates, "%Y-%m-%d")

Traceback (most recent call last):
  File "g:/till2.py", line 25, in <module>
    df_TradingMonthlyDates = df_TradingMonthlyDates.datetime.strptime(df_TradingMonthlyDates, "%Y-%m-%d")
  File "C:\Users\ID\AppData\Roaming\Python\Python38\site-packages\pandas\core\generic.py", line 5274, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'DataFrame' object has no attribute 'datetime'

df_TradingMonthlyDates["Date"] = pd.to_datetime(df_TradingMonthlyDates["Date"], format="%Y-%m-%d")

Traceback (most recent call last):
  File "g:/till2.py", line 40, in <module>
    date_output = nearest(df_TradingMonthlyDates, df_EndDate)
  File "g:/till2.py", line 38, in nearest
    return min([i for i in items if i < pivot], key=lambda x: abs(x - pivot))
  File "g:/till2.py", line 38, in <listcomp>
    return min([i for i in items if i < pivot], key=lambda x: abs(x - pivot))
TypeError: '<' not supported between instances of 'str' and 'datetime.date'

标签： pythonpandasdatetimetype-conversion

Answer 1

编辑：添加了方法 3，这可能是最简单的.loc，然后.iloc

您可以采用稍微不同的方法（使用下面的方法 #1 或方法 #2），方法是取今天日期和数据之间差异的绝对最小值，但是您没有做的关键事情是pd.to_datetime()环绕datetime.date对象df_EndDate以便将其转换为 aDatetimeArray以便可以将其与您的Date列进行比较。它们都必须采用相同的格式DatetimeArray才能进行比较。

方法一：

import pandas as pd
import datetime as dt
df_TradingMonthlyDates = pd.DataFrame({'Date': {'0': '2008-12-30',
  '1': '2008-12-31',
  '2': '2009-01-01',
  '3': '2009-01-02',
  '4': '2009-01-29',
  '557': '2020-06-29',
  '558': '2020-06-30',
  '559': '2020-07-01',
  '560': '2020-07-02',
  '561': '2020-07-30',
  '624': '2021-11-30',
  '625': '2021-12-01',
  '626': '2021-12-02',
  '627': '2021-12-30',
  '628': '2021-12-31'}})

df_TradingMonthlyDates['Date'] = pd.to_datetime(df_TradingMonthlyDates['Date'])
df_TradingMonthlyDates['EndDate'] = pd.to_datetime(dt.datetime.now().date())
df_TradingMonthlyDates['diff'] = (df_TradingMonthlyDates['Date'] - df_TradingMonthlyDates['EndDate'])
a=min(abs(df_TradingMonthlyDates['diff']))
df_TradingMonthlyDates = df_TradingMonthlyDates.loc[(df_TradingMonthlyDates['diff'] == a)
                                                    | (df_TradingMonthlyDates['diff'] == -a)]
df_TradingMonthlyDates

输出 1：

    Date        EndDate     diff
560 2020-07-02  2020-07-11  -9 days

如果您不想要额外的列而只想要日期，则分配变量以创建系列而不是新列：

方法二：

d = pd.to_datetime(df_TradingMonthlyDates['Date'])
t = pd.to_datetime(dt.datetime.now().date())
e = (d-t)
a=min(abs(e))
df_TradingMonthlyDates = df_TradingMonthlyDates.loc[(e == a) | (e == -a)]
df_TradingMonthlyDates

输出 2：

    Date
560 2020-07-02

方法三：

df_TradingMonthlyDates['Date'] = pd.to_datetime(df_TradingMonthlyDates['Date'])
date_output = df_TradingMonthlyDates.sort_values('Date') \
              .loc[df_TradingMonthlyDates['Date'] <= 
pd.to_datetime(dt.datetime.now().date())] \
              .iloc[-1,:]
date_output

输出 3：

Date   2020-07-02
Name: 560, dtype: datetime64[ns]