熊猫to_records()时间戳至今

Question

我有以下数据帧对象

              total
scanned_date       
2021-11-01        0
2021-11-02        0
2021-11-03        0
2021-11-04        0
2021-11-05        0

其中scanned_date是Timestamp对象。我想将数据转换为一个元组列表，如

[
  (2021-11-01, 0),
  (2021-11-02, 0),
  (2021-11-03, 0),
  ...
]

但当使用时

list(df.to_records())

它正在添加时区，而我只想要日期字符串。

[('2021-11-01T00:00:00.000000000', 0), ('2021-11-02T00:00:00.000000000', 0), ('2021-11-03T00:00:00.000000000', 0)]

如何从T00:00:00.00000000 to_records() 输出中删除时区字符串？

Answer 1

尝试转换strftime

df.index = df.index.strftime('%Y-%m-%d')
list(df.to_records())
Out[212]: 
[('2021-11-01', 0),
 ('2021-11-02', 0),
 ('2021-11-03', 0),
 ('2021-11-04', 0),
 ('2021-11-05', 0)]

Answer 2

我试着用numpy做日期转换，但选择了熊猫。在numpy中使用64位整数。我使用map函数和lambda将dataframe记录转换为日期和值元组。

txt="""scanned_date,total       
2021-11-01,0
2021-11-02,0
2021-11-03,0
2021-11-04,0
2021-11-05,0
"""

#https://www.py4u.net/discuss/17020

df = pd.read_csv(io.StringIO(txt),sep=',',parse_dates=['scanned_date'])
print(list(map(lambda tuple_obj: 
               (
                   pd.to_datetime(tuple_obj[1],'%M/%d/%Y')
                  #str(tuple_obj[1].astype("datetime64[M]").astype(int)% 12 + 1)
                  # + "-" + str(tuple_obj[1].astype(object).day)
                  # + "-" + str(tuple_obj[1].astype("datetime64[Y]"))
                 ,
                tuple_obj[2]),
               df.to_records())))

产出：

[(Timestamp('2021-11-01 00:00:00'), 0), (Timestamp('2021-11-02 00:00:00'), 0), (Timestamp('2021-11-03 00:00:00'), 0), (Timestamp('2021-11-04 00:00:00'), 0), (Timestamp('2021-11-05 00:00:00'), 0)]