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c:\Users\Administrator\Desktop\python\最终完整版第三版(台账) copy 2.py:257: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '交强险' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.
last1_data.loc[(last1_data['产品名称'] == '机动车辆保险') & (last1_data['经纪费比例'] == 0.04),'统计产品名称'] = '交强险' #如果产品名称为机动车险保险并且比例是0.04,那么统计名称为较强
险
c:\Users\Administrator\Desktop\python\最终完整版第三版(台账) copy 2.py:260: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '意外伤害保险' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.
last1_data.loc[last1_data['产品名称'] == '意外伤害保险', '险别小类名称'] = '意外伤害保险'
Traceback (most recent call last):
File "c:\Users\Administrator\Desktop\python\最终完整版第三版(台账) copy 2.py", line 272, in <module>
last1_data['出单时间'] = pd.to_datetime(last1_data['出单时间'], format='%Y/%m/%d')
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\tools\datetimes.py", line 1067, in to_datetime
values = convert_listlike(arg._values, format)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\tools\datetimes.py", line 433, in _convert_listlike_datetimes
return _array_strptime_with_fallback(arg, name, utc, format, exact, errors)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\tools\datetimes.py", line 467, in _array_strptime_with_fallback
result, tz_out = array_strptime(arg, fmt, exact=exact, errors=errors, utc=utc)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "strptime.pyx", line 501, in pandas._libs.tslibs.strptime.array_strptime
File "strptime.pyx", line 451, in pandas._libs.tslibs.strptime.array_strptime
File "strptime.pyx", line 583, in pandas._libs.tslibs.strptime._parse_with_format
ValueError: time data "2024-08-08" doesn't match format "%Y/%m/%d", at position 0. You might want to try:
- passing `format` if your strings have a consistent format;
- passing `format='ISO8601'` if your strings are all ISO8601 but not necessarily in exactly the same format;
- passing `format='mixed'`, and the format will be inferred for each element individually. You might want to use `dayfirst` alongside this.
根据你提供的错误信息,主要有两个问题:
1. **FutureWarning**
你在用 pandas 修改数据时,设置的数据类型与原数据类型不兼容。具体来说,你想将一个字符串(比如 '交强险')赋值给一个原本是 `float64` 类型的列。这在未来版本的 pandas 中会抛出错误。
解决方法:在赋值之前明确地转换数据类型。例如:
last1_data['统计产品名称'] = last1_data['统计产品名称'].astype(str)
last1_data.loc[(last1_data == '机动车辆保险') & (last1_data == 0.04), '统计产品名称'] = '交强险'
2. **ValueError**
你在用 `pd.to_datetime` 函数转换日期格式时,格式不匹配。错误消息表明日期字符串 "2024-08-08" 不匹配你指定的格式 "%Y/%m/%d"。
解决方法:检查你的数据,确保日期格式一致,或者使用适合的数据格式。例如:
last1_data = pd.to_datetime(last1_data, format='%Y-%m-%d')
如果数据格式多样,建议使用 `errors='coerce'` 参数处理错误数据:
last1_data = pd.to_datetime(last1_data, errors='coerce')
具体代码需要根据你的数据结构稍作调整,不过这样应该可以解决大部分问题。
以上回复来自 FishC AI 小助理,如未能正确解答您的问题,请继续追问。
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