Python ValueError：日期超出月份的范围
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ValueError: day is out of range for month
提问by Niladri Gomes
I want to convert a string from a dataframe to datetime.
我想将字符串从数据帧转换为日期时间。
dfx = df.ix[:,'a']
dfx = pd.to_datetime(dfx)
But it gives the following error:
但它给出了以下错误：
ValueError: day is out of range for month
ValueError：日期超出月份的范围
Can anyone help?
任何人都可以帮忙吗？
回答by jezrael
Maybe help add parameter dayfirst=Trueto to_datetime, if format of datetime is 30-01-2016:
也许帮助添加参数dayfirst=True到to_datetime，如果日期时间格式为30-01-2016：
dfx = df.ix[:,'a']
dfx = pd.to_datetime(dfx, dayfirst=True)
More universal is use parameter formatwith errors='coerce'for replacing values with other formatto NaN:
更通用的是使用参数formatwitherrors='coerce'用其他formatto替换值NaN：
dfx = '30-01-2016'
dfx = pd.to_datetime(dfx, format='%d-%m-%Y', errors='coerce')
print (dfx)
2016-01-30 00:00:00
Sample:
样本：
dfx = pd.Series(['30-01-2016', '15-09-2015', '40-09-2016'])
print (dfx)
0 30-01-2016
1 15-09-2015
2 40-09-2016
dtype: object
dfx = pd.to_datetime(dfx, format='%d-%m-%Y', errors='coerce')
print (dfx)
0 2016-01-30
1 2015-09-15
2 NaT
dtype: datetime64[ns]
If format is standard (e.g. 01-30-2016or 01-30-2016), add only errors='coerce':
如果格式是标准的（例如01-30-2016或01-30-2016），只添加errors='coerce'：
dfx = pd.Series(['01-30-2016', '09-15-2015', '09-40-2016'])
print (dfx)
0 01-30-2016
1 09-15-2015
2 09-40-2016
dtype: object
dfx = pd.to_datetime(dfx, errors='coerce')
print (dfx)
0 2016-01-30
1 2015-09-15
2 NaT
dtype: datetime64[ns]
