Python 在 DataFrame pandas 中添加日期之间的天数列
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Add column with number of days between dates in DataFrame pandas
提问by Jase Villam
I want to subtract dates in 'A' from dates in 'B' and add a new column with the difference.
我想从“B”中的日期中减去“A”中的日期并添加一个具有差异的新列。
df
A B
one 2014-01-01 2014-02-28
two 2014-02-03 2014-03-01
I've tried the following, but get an error when I try to include this in a for loop...
我尝试了以下操作，但是当我尝试将其包含在 for 循环中时出现错误...
import datetime
date1=df['A'][0]
date2=df['B'][0]
mdate1 = datetime.datetime.strptime(date1, "%Y-%m-%d").date()
rdate1 = datetime.datetime.strptime(date2, "%Y-%m-%d").date()
delta = (mdate1 - rdate1).days
print delta
What should I do?
我该怎么办？
采纳答案by Andy Hayden
Assuming these were datetime columns (if they're not apply to_datetime) you can just subtract them:
假设这些是日期时间列（如果它们不适用to_datetime），您可以减去它们：
df['A'] = pd.to_datetime(df['A'])
df['B'] = pd.to_datetime(df['B'])
In [11]: df.dtypes # if already datetime64 you don't need to use to_datetime
Out[11]:
A datetime64[ns]
B datetime64[ns]
dtype: object
In [12]: df['A'] - df['B']
Out[12]:
one -58 days
two -26 days
dtype: timedelta64[ns]
In [13]: df['C'] = df['A'] - df['B']
In [14]: df
Out[14]:
A B C
one 2014-01-01 2014-02-28 -58 days
two 2014-02-03 2014-03-01 -26 days
Note: ensure you're using a new of pandas (e.g. 0.13.1), this may not work in older versions.
注意：确保您使用的是新的 Pandas（例如 0.13.1），这可能不适用于旧版本。
回答by A.Kot
A list comprehension is your best bet for the most Pythonic (and fastest) way to do this:
列表理解是最Pythonic（和最快）的方式来做到这一点的最佳选择：
[int(i.days) for i in (df.B - df.A)]
- i will return the timedelta(e.g. '-58 days')
- i.days will return this value as a long integer value(e.g. -58L)
- int(i.days) will give you the -58 you seek.
- 我将返回时间增量（例如“-58 天”）
- i.days 将此值作为长整数值返回（例如 -58L）
- int(i.days) 会给你你想要的 -58。
If your columns aren't in datetime format. The shorter syntax would be: df.A = pd.to_datetime(df.A)
如果您的列不是日期时间格式。较短的语法是：df.A = pd.to_datetime(df.A)
回答by Tom
How about this:
这个怎么样：
times['days_since'] = max(list(df.index.values))
times['days_since'] = times['days_since'] - times['months']
times
回答by Ricky McMaster
To remove the 'days' text element, you can also make use of the dt() accessor for series: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.dt.html
要删除“天”文本元素，您还可以使用系列的 dt() 访问器：https: //pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.dt.html
So,
所以，
df[['A','B']] = df[['A','B']].apply(pd.to_datetime) #if conversion required
df['C'] = (df['B'] - df['A']).dt.days
which returns:
返回：
A B C
one 2014-01-01 2014-02-28 58
two 2014-02-03 2014-03-01 26
