在 Pandas 中将整数系列转换为 timedelta [英] Convert integer series to timedelta in pandas

问题描述

我在 Pandas 中有一个数据框，其中包含事件发生后的天数.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.每次我尝试应用 pd.offsets.Day 或 pd.Timedelta 时，我都会收到一个错误，指出 Series 是不受支持的类型.当我使用 apply 时也会发生这种情况.当我使用 map 时，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".

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.Day or pd.Timedelta I get an error stating that Series are an unsupported type. This also occurs when I use apply. When I use map I receive a runtime error saying "maximum recursion depth exceeded while calling a Python object".

例如，假设我的数据框如下所示:

For example, assume my data frame looked like this:

index    days_since_event
0        5
1        7
2        3
3        6
4        0

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)

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)

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

我尝试了多种方法来执行此操作，但每种方法都收到了错误.

I have attempted multiple ways to do this, but have received errors for each.

我尝试过的一种方法是:

One method I tried was:

now = pd.datetime.date(pd.datetime.now())
df['event_date'] = now - df.days_since_event.apply(pd.offsets.Day)

因此，我收到一条错误消息，指出系列是不受支持的类型.

With this I received an error saying that Series are an unsupported type.

我使用 .map 而不是 .apply 尝试了上述操作，并收到了 调用 Python 对象时超出最大递归深度"的错误em>.

I tried the above with .map instead of .apply, and received the error that "maximum recursion depth exceeded while calling a Python object".

我也尝试将天数转换为时间增量，例如:

I also attempted to convert the days into timedelta, such as:

df.days_since_event = (dt.timedelta(days = df.days_since_event)).apply

这也收到了一个错误，指出该系列是不受支持的类型.

This also received an error referencing the series being an unsupported type.

推荐答案

首先，要将带有整数的列转换为 timedelta，可以使用 to_timedelta:

First, to convert the column with integers to a timedelta, you can use 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]

然后您可以使用当前日期创建一个新列并减去这些时间增量:

Then you can create a new column with the current date and substract those timedelta's:

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]

这篇关于在 Pandas 中将整数系列转换为 timedelta的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！