Question

我正在尝试将数据按年份分组，并根据其所属年份对支出进行汇总。

以下是示例数据：

date:            spend_amt:

2/1/2014          10000

2/5/2014           98

1/2/2015          5834.2

7/8/2017          561236

9/3/2017          568

28/1/2016         989895.3

我当前的代码

def yearlySpending(self):

    dfspendingYearly = pd.DataFrame()
    dfspendingYearly = self.dfGov.groupby(["date"])['spend_amt'].agg('sum')
    dfspendingYearly.groupby(dfspendingYearly["date"].dt.year)['spend_amt'].agg(['sum'])

我遇到一个错误，'KeyError：'date'

所需的输出

date:       spend_amt:
2014        10098
2015        5834.2
2016        989895.3
2017        561804

Answer 1

将datestamp列转换为日期时间，并按年份对数据框进行分组

可能重复 grouping by year

df["date:"] = pd.to_datetime(df['date:'])
df.groupby(df['date:'].dt.year).sum().reset_index()

出局：

    date:   spend_amt:
0   2014    10098.0
1   2015    5834.2
2   2016    989895.3
3   2017    561804.0

Answer 2

您的错误意味着没有列# attach packages to the search path, installing them from CRAN or GitHub if needed librarian::shelf(plyr, tidyverse, knitr, ggplot2, scales, sqldf) # List of all loaded packages # (.packages()) librarian:::check_attached() # unload librarian::unshelf(plyr, tidyverse, knitr, ggplot2, scales, reshape2, also_depends = TRUE) # print(.Last.value)，我猜有date叫做index：

date

如何将日期列分组为年份并根据年份对支出列求和？

2 个答案: