ValueError:日期超出月份范围
问题描述：
我想将字符串从数据帧转换为日期时间.
I want to convert a string from a dataframe to datetime.
dfx = df.ix[:,'a']
dfx = pd.to_datetime(dfx)
但是会出现以下错误:
ValueError:日期超出月份范围
ValueError: day is out of range for month
任何人都可以帮忙吗?
Can anyone help?
答
Maybe help add parameter dayfirst=True to to_datetime, if format of datetime is 30-01-2016:
dfx = df.ix[:,'a']
dfx = pd.to_datetime(dfx, dayfirst=True)
更通用的方法是将参数 format 与errors='coerce'一起使用，以将值替换为其他format至
More universal is use parameter format with errors='coerce' for replacing values with other format to NaN:
dfx = '30-01-2016'
dfx = pd.to_datetime(dfx, format='%d-%m-%Y', errors='coerce')
print (dfx)
2016-01-30 00:00:00
示例:
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]
如果格式是标准格式(例如01-30-2016或01-30-2016)，则仅添加errors='coerce':
If format is standard (e.g. 01-30-2016 or 01-30-2016), add only 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]