将年，月，日列与大 pandas 合并为单个日期列 [英] Combining year, month, day columns into a single date column with pandas

问题描述

合并数据时，我总是遇到错误:

I keep running into an error when combining my data:

record_id   month   day year   sex
1              7    17  1977    M
2              7    15  1979    M
3              7    26  1978    F
4              7    16  1973    M

我尝试了将月份，日期和年份合并为一列的不同方法:

I tried different methods of combining the month, date and year into one column:

1. surveys_df['date'] = surveys_df['month'].astype(str) + surveys_df['day'] + surveys_df['year']
2. surveys_df['Date'] = pd.to_datetime(surveys_df[['month', 'day', 'year']])

3. r= pd.to_datetime(surveys_df[['year', 'month', 'day']])

4. surveys_df['date'] = pd.to_datetime(surveys_df[['day','month','year']])

我得到的错误:

ValueError:无法组合日期时间:day超出了范围 天

ValueError: cannot assemble the datetimes: day is out of range for day

我知道我可以通过使用 error ='coerce'来强制执行此操作，但是我想避免使用该方法.

I know I can force it by using error= 'coerce' but I will like to refrain from using that method.

推荐答案

pd.to_datetime(df[['year', 'month', 'day']])

0   1977-07-17
1   1979-07-15
2   1978-07-26
3   1973-07-16
dtype: datetime64[ns]

如果您要NaTify无效的组合，然后添加errors='coerce'参数.

If there are invalid combinations you want to NaTify, then add the errors='coerce' argument.

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