在 Pandas 中将整数系列转换为 timedelta
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Convert integer series to timedelta in pandas
提问by abdouglass
I have a data frame in pandas which includes number of days since an event occurred. I want to create a new column that calculates the date of the event by subtracting the number of days from the current date. Every time I attempt to apply pd.offsets.Dayor pd.TimedeltaI get an error stating that Series are an unsupported type. This also occurs when I use apply. When I use mapI receive a runtime error saying "maximum recursion depth exceeded while calling a Python object".
我在Pandas中有一个数据框，其中包括事件发生后的天数。我想创建一个新列，通过从当前日期中减去天数来计算事件的日期。每次我尝试申请pd.offsets.Day或pd.Timedelta收到错误消息，指出 Series 是不受支持的类型。当我使用apply. 当我使用时，map我收到一个运行时错误，提示“调用 Python 对象时超出了最大递归深度”。
For example, assume my data frame looked like this:
例如，假设我的数据框如下所示：
index days_since_event
0 5
1 7
2 3
3 6
4 0
I want to create a new column with the date of the event, so my expected outcome (using today's date of 12/29/2015)
我想用事件的日期创建一个新列，所以我的预期结果（使用今天的日期 12/29/2015）
index days_since_event event_date
0 5 2015-12-24
1 7 2015-12-22
2 3 2015-12-26
3 6 2015-12-23
4 0 2015-12-29
I have attempted multiple ways to do this, but have received errors for each.
我尝试了多种方法来做到这一点，但每种方法都收到了错误。
One method I tried was:
我尝试过的一种方法是：
now = pd.datetime.date(pd.datetime.now())
df['event_date'] = now - df.days_since_event.apply(pd.offsets.Day)
With this I received an error saying that Series are an unsupported type.
有了这个，我收到一个错误，说 Series 是不受支持的类型。
I tried the above with .mapinstead of .apply, and received the error that "maximum recursion depth exceeded while calling a Python object".
我尝试了上面的.map而不是.apply，并收到了“调用 Python 对象时超出了最大递归深度”的错误。
I also attempted to convert the days into timedelta, such as:
我还尝试将天数转换为 timedelta，例如：
df.days_since_event = (dt.timedelta(days = df.days_since_event)).apply
This also received an error referencing the series being an unsupported type.
这也收到了一个错误，指出该系列是不受支持的类型。
回答by joris
First, to convert the column with integers to a timedelta, you can use to_timedelta:
首先，要将带有整数的列转换为 timedelta，您可以使用to_timedelta：
In [60]: pd.to_timedelta(df['days_since_event'], unit='D')
Out[60]:
0 5 days
1 7 days
2 3 days
3 6 days
4 0 days
Name: days_since_event, dtype: timedelta64[ns]
Then you can create a new column with the current date and substract those timedelta's:
然后，您可以使用当前日期创建一个新列并减去这些 timedelta：
In [62]: df['event_date'] = pd.Timestamp('2015-12-29')
In [63]: df['event_date'] = df['event_date'] - pd.to_timedelta(df['days_since_event'], unit='D')
In [64]: df['event_date']
Out[64]:
0 2015-12-24
1 2015-12-22
2 2015-12-26
3 2015-12-23
4 2015-12-29
dtype: datetime64[ns]
