问题描述
我知道有一个简单的实现可以做到这一点,但我不记得语法了.有一个简单的 pandas 时间序列,我想按月汇总数据.具体来说,我想添加数月和数年的数据以获取一些摘要.可以用切片来写,但我记得看到过自动执行它的语法.
I know there is a simple implementation to do this but I cannot remember the syntax. Have a simple pandas time series and I want to summarize the data by month. Specifically I want to add data over months and years to get some summary of it. Can write it with slicing, but I remember seeing syntax that does it automatically.
import pandas as pd df = Series(randn(100), index=pd.date_range('2012-01-01', periods=100))
一等奖是一等奖.
部分答案:
ds.resample('M', how=sum) # for calendar monthly ds.resample('A', how=sum) # for calendar yearly
知道如何优雅地按年总和进行多索引吗?
Any idea how to elegantly get to multindexed by year sums?
推荐答案
In [1]: import pandas as pd from numpy.random import randn In [2]: df = Series(randn(500), index=pd.date_range('2012-01-01', periods=500)) In [3]: s2 = df.groupby([lambda x: x.year, lambda x: x.month]).sum() In [4]: s2 Out[4]: 2012 1 3.853775 2 4.259941 3 4.629546 4 -10.812505 5 -16.383818 6 -5.255475 7 5.901344 8 13.375258 9 1.758670 10 6.570200 11 6.299812 12 7.237049 2013 1 -1.331835 2 3.399223 3 2.011031 4 7.905396 5 1.127362 dtype: float64