datetime struggle with a pandas dataframe

huangapple
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英文:

datetime struggle with a pandas dataframe

问题

以下是您提供的代码的翻译部分：

  1. 我正在运行以下 **代码**：
  2. ```python
  3. filled_df = (ts.set_index(date_col)
  4.                  .groupby(grouping)
  5.                  .apply(lambda d: d.reindex(
  6.                      pd.date_range(
  7.                          mf_heuristic(d.index, champion_end), pd.to_datetime(
  8.                              dt.datetime.now()
  9.                          ),
  10.                          freq='MS')
  11.                  )
  12.     )
  13.         .drop(grouping, axis=1)
  14.         .reset_index(grouping)
  15.         .fillna(0)

使用以下预定义变量：

  1. date_col = 'timepoint'
  2. grouping = ['Level', 'Kontogruppe']
  3. champion_end = fc_date - pd.DateOffset(months=13)
  5. print(champion_end)
  6. 2021-03-01 00:00:00
  8. print(ts)
  9. Kontogruppe  Level   timepoint    data_value
  10. 0       A   ZBFO  2020-03-01      1
  11. 1       B   ZBFO  2020-07-01      1612.59
  12. 2       A   ZBFO  2020-08-01      1046.1
  14. print(ts.dtypes)
  15. Kontogruppe     object
  16. Level           object
  17. timepoint       object
  18. data_value         float64
  19. dtype: object
  1. def mf_heuristic(date, champion_end):
  2.         
  3.         if min(date) < champion_end:
  4.             start_date = min(date)
  5.         else:
  6.             
  7.             start_date = min(date)
  8.         return start_date

当我运行代码时，我收到以下 错误消息：

TypeError: Cannot compare Timestamp with datetime.date. Use ts == pd.Timestamp(date) or ts.date() == date instead.

针对具有 mf_heuristic 函数的行。

如果我尝试在之前加入以下代码：

  1. ts[date_col] = pd.Timestamp(ts[date_col])

我会收到以下错误消息：

TypeError: function missing required argument 'year' (pos 1)

  2. <details>
  3. <summary>英文:</summary>
  5. I am running the following **code**:

filled_df = (ts.set_index(date_col)
.groupby(grouping)
.apply(lambda d: d.reindex(
pd.date_range(
mf_heuristic(d.index, champion_end), pd.to_datetime(
dt.datetime.now()
),
freq='MS')
)
)
.drop(grouping, axis=1)
.reset_index(grouping)
.fillna(0)

  1. *with the predefinitions:*

date_col = 'timepoint'
grouping = ['Level', 'Kontogruppe']
champion_end = fc_date - pd.DateOffset(months=13)

print(champion_end)
2021-03-01 00:00:00

print(ts)
Kontogruppe Level timepoint data_value
0 A ZBFO 2020-03-01 1
1 B ZBFO 2020-07-01 1612.59
2 A ZBFO 2020-08-01 1046.1

print(ts.dtypes)
Kontogruppe object
Level object
timepoint object
data_value float64
dtype: object

def mf_heuristic(date, champion_end):

  1.     if min(date) &lt; champion_end:
  2.         start_date = min(date)
  3.     else:
  4.         
  5.         start_date = min(date)
  6.     return start_date
  2. When I run the code, I get the following **error massage**:
  4. &gt; TypeError: Cannot compare Timestamp with datetime.date. Use ts ==
  5. &gt; pd.Timestamp(date) or ts.date() == date instead.
  7. for the line with the mf_heuristic function.
  9. If I try to put before:

ts[date_col] = pd.Timestamp(ts[date_col])

  1. I get the error massage:
  3. &gt; TypeError: function missing required argument &#39;year&#39; (pos 1)
  8. </details>
  11. # 答案1
  12. **得分**: 2
  14. 尝试使用 `to_datetime`：
  15. ```python
  16. ts[date_col] = pd.to_datetime(ts[date_col])
英文:

Try using to_datetime:

  1. ts[date_col] = pd.to_datetime(ts[date_col])

huangapple
  • 本文由 发表于 2023年7月27日 21:06:38
  • 转载请务必保留本文链接：https://go.coder-hub.com/76780057.html
  • datetime
  • pandas
  • python
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