我在数据框中有两列已转换为日期时间。我正在尝试减去这些数字,并找出年份之间的差异。这是我正在使用的代码:
from dateutil.relativedelta import relativedelta
difference_in_years = relativedelta(x['start'], x['end']).year
但是,我收到以下错误消息:
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
出了什么问题?
答案 0 :(得分:2)
将属性.years
与apply
和axis=1
一起用于按行处理:
df = pd.DataFrame({'start':['2015-10-02','2014-11-05'],
'end':['2018-01-02','2018-10-05']})
df['start'] = pd.to_datetime(df['start'])
df['end'] = pd.to_datetime(df['end'])
from dateutil.relativedelta import relativedelta
df['y'] = df.apply(lambda x: relativedelta(x['end'], x['start']).years, axis=1)
或使用list comprehension
:
df['y'] = [relativedelta(i, j).years for i, j in zip(df['end'], df['start'])]
print (df)
start end y
0 2015-10-02 2018-01-02 2
1 2014-11-05 2018-10-05 3
编辑:
df = pd.DataFrame({'start':['2015-10-02','2014-11-05'],
'end':['2018-01-02',np.nan]})
df['start'] = pd.to_datetime(df['start'])
df['end'] = pd.to_datetime(df['end'])
from dateutil.relativedelta import relativedelta
m = df[['start','end']].notnull().all(axis=1)
df.loc[m, 'y'] = df[m].apply(lambda x: relativedelta(x['end'], x['start']).years, axis=1)
print (df)
start end y
0 2015-10-02 2018-01-02 2.0
1 2014-11-05 NaT NaN
答案 1 :(得分:1)
检查此答案calculate the difference between two datetime.date() dates in years and months
from dateutil import relativedelta as rdelta
from datetime import date
d1 = date(2001,5,1)
d2 = date(2012,1,1)
rd = rdelta.relativedelta(d2,d1)
rd
relativedelta(years=+10, months=+8)
答案 2 :(得分:0)
您可以通过
(df['end'] - df['start'])/pd.Timedelta(1, 'Y')
并根据需要四舍五入结果。
在大熊猫v0.23.4
中,以后可以做
(df['end'] - df['start'])//pd.Timedelta(1, 'Y')
立即获得全年差异。
答案 3 :(得分:0)
您可以将timedelta
系列除以年份单位,并在必要时四舍五入:
# data from jezrael
df['years'] = (df['end'] - df['start']) / np.timedelta64(1, 'Y')
df['years_floor'] = df['years'].round()
print(df)
start end years years_floor
0 2015-10-02 2018-01-02 2.253297 2.0
1 2014-11-05 NaT NaN NaN