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在 ddply summarize 期间从 df 中选择一个值

[英]selecting a value from df during ddply summarise

 原文  2020-10-25 00:52:39  1   2    r/ plyr

问题描述

I want to use ddply and summarise to get the monthly medians for several years of data.我想使用ddply和summarise来获取几年数据的月中值。 I can do this successfully.我可以成功地做到这一点。 However, I would also like to have a column with the value for one year of the data.但是，我还希望有一列包含一年数据的值。 I know other ways to add this, but would like to do it within the ddply line.我知道添加它的其他方法，但想在ddply行中进行。 Data is at the bottom.数据在底部。

The first row of the result would look like this if median for all years is 16 and the value for 2018 is 30:如果所有年份的中位数为 16 且 2018 年的值为 30，则结果的第一行将如下所示：

Month Median 2018
 
Apr   16.0   30

Here is what I have tried: This works as expected:这是我尝试过的：这按预期工作：

Summary<-ddply(df, ~Month, summarise, Median = median(Value))
Summary

When I try to add the single year value I can't seem to think of a way to do it:当我尝试添加单个年份值时，我似乎想不出办法：

Summary<-ddply(df, ~Month, summarise, Median = median(Value), SingleYearValue = which(df[,"Year"]==2018));Summary

df<-structure(list(Month = c("Apr", "Apr", "Apr", "Apr", "Apr", "Apr", 
                             "Apr", "Apr", "Apr", "Apr", "Apr", "Apr", "Apr", "Apr", "Apr", 
                             "Apr", "Apr", "Apr", "Apr", "Apr", "Apr", "Apr", "Apr", "Apr", 
                             "Apr", "Apr", "Apr", "Apr", "Apr", "Apr", "Apr", "Aug", "Aug", 
                             "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", 
                             "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", 
                             "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", "Aug", 
                             "Aug", "Aug", "Aug", "Dec", "Dec", "Dec", "Dec", "Dec", "Dec", 
                             "Dec", "Dec", "Dec", "Dec", "Dec", "Dec", "Dec", "Feb", "Feb", 
                             "Feb", "Feb", "Feb", "Feb", "Feb", "Feb", "Feb", "Feb", "Feb", 
                             "Feb", "Feb", "Jan", "Jan", "Jan", "Jan", "Jan", "Jan", "Jan", 
                             "Jan", "Jan", "Jan", "Jan", "Jan", "Jan", "Jul", "Jul", "Jul", 
                             "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", 
                             "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", 
                             "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", "Jul", 
                             "Jul", "Jul", "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", 
                             "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", 
                             "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", 
                             "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", "Jun", "Mar", "Mar", 
                             "Mar", "Mar", "Mar", "Mar", "Mar", "Mar", "Mar", "Mar", "Mar", 
                             "Mar", "Mar", "Mar", "Mar", "Mar", "Mar", "May", "May", "May", 
                             "May", "May", "May", "May", "May", "May", "May", "May", "May", 
                             "May", "May", "May", "May", "May", "May", "May", "May", "May", 
                             "May", "May", "May", "May", "May", "May", "May", "May", "May", 
                             "May", "Nov", "Nov", "Nov", "Nov", "Nov", "Nov", "Nov", "Nov", 
                             "Nov", "Nov", "Nov", "Nov", "Nov", "Nov", "Nov", "Nov", "Nov", 
                             "Nov", "Oct", "Oct", "Oct", "Oct", "Oct", "Oct", "Oct", "Oct", 
                             "Oct", "Oct", "Oct", "Oct", "Oct", "Oct", "Oct", "Oct", "Oct", 
                             "Oct", "Oct", "Oct", "Oct", "Oct", "Oct", "Oct", "Oct", "Oct", 
                             "Oct", "Oct", "Oct", "Oct", "Oct", "Sep", "Sep", "Sep", "Sep", 
                             "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", 
                             "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", 
                             "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", "Sep", 
                             "Sep"), Year = c("1960", "1961", "1962", "1963", "1964", "1965", 
                                              "1966", "1967", "1968", "1969", "1970", "1971", "1972", "2002", 
                                              "2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010", 
                                              "2011", "2012", "2013", "2014", "2015", "2016", "2017", "2018", 
                                              "2019", "1960", "1961", "1962", "1963", "1964", "1965", "1966", 
                                              "1967", "1968", "1969", "1970", "1971", "1972", "2001", "2002", 
                                              "2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010", 
                                              "2011", "2012", "2013", "2014", "2015", "2016", "2017", "2018", 
                                              "2019", "1959", "1960", "1961", "1962", "1963", "1964", "1965", 
                                              "1966", "1967", "1968", "1969", "1970", "1971", "1960", "1961", 
                                              "1962", "1963", "1964", "1965", "1966", "1967", "1968", "1969", 
                                              "1970", "1971", "1972", "1960", "1961", "1962", "1963", "1964", 
                                              "1965", "1966", "1967", "1968", "1969", "1970", "1971", "1972", 
                                              "1960", "1961", "1962", "1963", "1964", "1965", "1966", "1967", 
                                              "1968", "1969", "1970", "1971", "1972", "2001", "2002", "2003", 
                                              "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", 
                                              "2012", "2013", "2014", "2015", "2016", "2017", "2018", "2019", 
                                              "1960", "1961", "1962", "1963", "1964", "1965", "1966", "1967", 
                                              "1968", "1969", "1970", "1971", "1972", "2001", "2002", "2003", 
                                              "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", 
                                              "2012", "2013", "2014", "2015", "2016", "2017", "2018", "2019", 
                                              "1960", "1961", "1962", "1963", "1964", "1965", "1966", "1967", 
                                              "1968", "1969", "1970", "1971", "1972", "2016", "2017", "2018", 
                                              "2019", "1960", "1961", "1962", "1963", "1964", "1965", "1966", 
                                              "1967", "1968", "1969", "1970", "1971", "1972", "2002", "2003", 
                                              "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", 
                                              "2012", "2013", "2014", "2015", "2016", "2017", "2018", "2019", 
                                              "1959", "1960", "1961", "1962", "1963", "1964", "1965", "1966", 
                                              "1967", "1968", "1969", "1970", "1971", "2005", "2015", "2016", 
                                              "2017", "2018", "1959", "1960", "1961", "1962", "1963", "1964", 
                                              "1965", "1966", "1967", "1968", "1969", "1970", "1971", "2001", 
                                              "2002", "2003", "2004", "2005", "2006", "2007", "2008", "2010", 
                                              "2011", "2012", "2013", "2014", "2015", "2016", "2017", "2018", 
                                              "2019", "1960", "1961", "1962", "1963", "1964", "1965", "1966", 
                                              "1967", "1968", "1969", "1970", "1971", "1972", "2001", "2002", 
                                              "2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010", 
                                              "2011", "2012", "2013", "2014", "2015", "2016", "2017", "2018", 
                                              "2019"), Value = 1:295), row.names = c(NA, -295L), class = "data.frame")

2 个解决方案

解决方案1
 2  2020-10-25 01:37:13

You can subset a particular years value and then merge :您可以对特定年份值进行subset ，然后merge ：

year = 2018
data <- subset(df, Year == year, select = -Year)
names(data)[names(data) == 'Value'] <- year
merge(Summary, data, by = 'Month', all.x = TRUE)

#   Month Median 2018
#1    Apr   16.0   30
#2    Aug   47.5   62
#3    Dec   70.0   NA
#4    Feb   83.0   NA
#5    Jan   96.0   NA
#6    Jul  118.5  133
#7    Jun  150.5  165
#8    Mar  175.0  182
#9    May  199.0  213
#10   Nov  223.5  232
#11   Oct  248.0  262
#12   Sep  279.5  294

解决方案2
 1 已采纳  2020-10-25 22:16:48

If we want to do this all in plyr , use the plyr::join如果我们想在plyr中完成这一切，请使用plyr::join

plyr::join(Summary, subset(df, Year == 2018, select = -Year))
#    Month Median Value
#1    Apr   16.0    30
#2    Aug   47.5    62
#3    Dec   70.0    NA
#4    Feb   83.0    NA
#5    Jan   96.0    NA
#6    Jul  118.5   133
#7    Jun  150.5   165
#8    Mar  175.0   182
#9    May  199.0   213
#10   Nov  223.5   232
#11   Oct  248.0   262
#12   Sep  279.5   294

Or if we want to do this within ddply或者如果我们想在ddply中执行此操作

plyr::ddply(df, ~ Month, summarise, Median = median(Value),
        `2018` = Value[Year == 2018][1])
#   Month Median 2018
#1    Apr   16.0   30
#2    Aug   47.5   62
#3    Dec   70.0   NA
#4    Feb   83.0   NA
#5    Jan   96.0   NA
#6    Jul  118.5  133
#7    Jun  150.5  165
#8    Mar  175.0  182
#9    May  199.0  213
#10   Nov  223.5  232
#11   Oct  248.0  262
#12   Sep  279.5  294

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