TypeError：“datetime.date”对象的描述符“strftime”不适用于“str”对象--尽管已存在类型为datetime的列开发者社区

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|     Column          |     Data Type    |
|---------------------|------------------|
|    flowId           |         object   |
|    flowName         |         object   |
|    executionId      |         object   |
|    startedAt        |         datetime64[ns, tzlocal()]       |
|    lastUpdatedAt    |         datetime64[ns, tzlocal()]       |
|    dataPullStartTime|         datetime64[ns, tzlocal()]       |
|    dataPullEndTime  |         datetime64[ns, tzlocal()]       |
|    bytesProcessed   |         float64       |
|    bytesWritten     |         float64       |
|    recordsProcessed |         float64       |

test_df[['startedAt','lastUpdatedAt', 'dataPullStartTime', 'dataPullEndTime']] = 
test_df[['startedAt','lastUpdatedAt', 
'dataPullStartTime','dataPullEndTime']].apply(datetime.strftime('%Y-%m-%d 
%H:%M:%S.%f'), axis=1)

TypeError: descriptor 'strftime' for 'datetime.date' objects doesn't apply to a 'str' object

cols = ['startedAt','lastUpdatedAt', 'dataPullStartTime', 'dataPullEndTime']
df[cols] = df[cols].apply(lambda c: c.dt.strftime('%Y-%m-%d %H:%M:%S.%f'))

cols = ['startedAt','lastUpdatedAt', 'dataPullStartTime', 'dataPullEndTime']
df.update(df[cols].apply(lambda c: c.dt.strftime('%Y-%m-%d %H:%M:%S.%f')))

df = pd.DataFrame({'col1': ['2000-01-01'], 'col2': ['2022-01-01']})
df['col1'] = pd.to_datetime(df['col1'])
df['col2'] = pd.to_datetime(df['col2'])
print(df)
        col1       col2
0 2000-01-01 2022-01-01
cols = ['col1', 'col2']

问 TypeError：“datetime.date”对象的描述符“strftime”不适用于“str”对象--尽管已存在类型为datetime的列 EN

回答 4

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