本文介绍了Python pandas .日期对象按单独的列拆分.的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我用Python(熊猫)写的日期写为"1/31/2010".要应用线性回归，我想拥有3个单独的变量:天数，月数，年数.
I have dates in Python (pandas) written as "1/31/2010". To apply linear regression I want to have 3 separate variables: number of day, number of month, number of year.
将熊猫中带有日期的列拆分为3列的方式是什么?另一个问题是将相同但分组的天数分为3组:1-10、11-20、21-31.
What will be the way to split a column with date in pandas into 3 columns?Another question is to have the same but group days into 3 groups: 1-10, 11-20, 21-31.
推荐答案
df['date'] = pd.to_datetime(df['date'])
#Create 3 additional columns
df['day'] = df['date'].dt.day
df['month'] = df['date'].dt.month
df['year'] = df['date'].dt.year
理想情况下，您无需创建3个额外的列即可执行此操作，只需将 Series 传递给函数即可.
Ideally, you can do this without having to create 3 additional columns, you can just pass the Series to your function.
In [2]: pd.to_datetime('01/31/2010').day
Out[2]: 31
In [3]: pd.to_datetime('01/31/2010').month
Out[3]: 1
In [4]: pd.to_datetime('01/31/2010').year
Out[4]: 2010
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