如何计算个人超过某个值的年数并显示所述年份

Question

我有以下数据集：

##      ID cumulative          sector        meters                           DOB
## 1 20100   41.75948             H38          6400                    1979-08-24
## 2 20101   35.16874             B01          1600                    1980-05-05
## 3 20102   20.60899             H04          1600                    1979-03-17
## 4 20103   38.72266 c("B09", "B37") c(3200, 8000) c("1981-11-30", "1981-11-30")
## 5 20104   38.72266 c("B09", "B37") c(3200, 8000) c("1978-09-01", "1978-09-01")
## 6 20105  116.88668 c("B09", "B09") c(3200, 3200) c("1980-12-03", "1980-12-03")
##             Oct                      Res_FROM                        Res_TO
## 1             W                    1979-08-15                    1991-05-15
## 2            NW                    1980-05-15                    1991-04-15
## 3            SW                    1972-06-15                    1979-08-15
## 4  c("NE", "N") c("1982-01-15", "1984-01-15") c("1984-01-15", "1986-04-15")
## 5  c("NE", "N") c("1982-01-15", "1984-01-15") c("1984-01-15", "1986-04-15")
## 6 c("NE", "NE") c("1980-12-15", "1983-08-15") c("1983-08-15", "1991-03-15")
##                        Exp_FROM                        Exp_TO
## 1                    1979-08-24                    1988-12-31
## 2                    1980-05-15                    1988-12-31
## 3                    1979-03-17                    1979-08-15
## 4 c("1982-01-15", "1984-01-15") c("1984-01-15", "1986-04-15")
## 5 c("1982-01-15", "1984-01-15") c("1984-01-15", "1986-04-15")
## 6 c("1980-12-15", "1983-08-15") c("1983-08-15", "1988-12-31")
##                  Exps_Grp Yr1952 Yr1953 Yr1954 Yr1955 Yr1956 Yr1957 Yr1958
## 1                 fr51>88     NA     NA     NA     NA     NA     NA     NA
## 2                 fr51>88     NA     NA     NA     NA     NA     NA     NA
## 3                 between     NA     NA     NA     NA     NA     NA     NA
## 4 c("between", "between")     NA     NA     NA     NA     NA     NA     NA
## 5 c("between", "between")     NA     NA     NA     NA     NA     NA     NA
## 6 c("between", "fr51>88")     NA     NA     NA     NA     NA     NA     NA
##   Yr1959 Yr1960 Yr1961 Yr1962 Yr1963 Yr1964 Yr1965 Yr1966 Yr1967 Yr1968 Yr1969
## 1     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA
## 2     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA
## 3     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA
## 4     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA
## 5     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA
## 6     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA     NA
##   Yr1970 Yr1971 Yr1972 Yr1973 Yr1974 Yr1975 Yr1976 Yr1977 Yr1978    Yr1979
## 1     NA     NA     NA     NA     NA     NA     NA     NA     NA  5.950991
## 2     NA     NA     NA     NA     NA     NA     NA     NA     NA        NA
## 3     NA     NA     NA     NA     NA     NA     NA     NA     NA 20.608986
## 4     NA     NA     NA     NA     NA     NA     NA     NA     NA        NA
## 5     NA     NA     NA     NA     NA     NA     NA     NA     NA        NA
## 6     NA     NA     NA     NA     NA     NA     NA     NA     NA        NA
##     Yr1980    Yr1981    Yr1982    Yr1983    Yr1984    Yr1985     Yr1986
## 1 4.340588  4.340588  4.340588  4.340588  4.340588  4.340588  4.3405881
## 2 2.927725  4.447229  4.447229  4.447229  4.447229  4.447229  4.4472289
## 3       NA        NA        NA        NA        NA        NA         NA
## 4       NA        NA 15.365412 16.018407  3.594414  3.052618  0.6918076
## 5       NA        NA 15.365412 16.018407  3.594414  3.052618  0.6918076
## 6 0.758267 16.018407 16.018407 16.018407 16.018407 16.018407 16.0184067
##      Yr1987   Yr1988   Yrs_Exp arth_mean    median cumulative.1 Age
## 1  4.340588 1.083782 9.3616438  4.175948  4.340588     41.75948   9
## 2  4.447229 1.110409 8.6356164  3.907637  4.447229     35.16874   8
## 3        NA       NA 0.4136986 20.608986 20.608986     20.60899   9
## 4        NA       NA 4.2493151  7.744532  3.594414     38.72266   7
## 5        NA       NA 4.2493151  7.744532  3.594414     38.72266  10
## 6 16.018407 3.999565 8.0493151 12.987409 16.018407    116.88668   8

根据这些信息，我想完成几件事：

我想计算每个人（每个 ID 是一个人）的平均值（即 arth_mean 列）大于 4 的年数。将此添加为列对我的数据集来说是理想的。
从第 2 点开始，我希望每一年每个人超过 4 的 arth_mean 都为每个人列出，也在我的数据集的新列中。因此，例如，我可能有一列为每个 ID 列出了 1954、1966、1967 等。

我对 R 比较陌生，因此非常感谢任何帮助或建议。我不知道如何获得我想要的输出。我在下面添加了可重现的数据。

## structure(list(ID = 20100:20109, cumulative = c(41.75947792, 
## 35.16873597, 20.60898553, 38.72265958, 38.72265958, 116.8866785, 
## 271.4880918, 134.9473309, 35.91709062, 26.06165412), sector = c("H38", 
## "B01", "H04", "c(\"B09\", \"B37\")", "c(\"B09\", \"B37\")", "c(\"B09\", \"B09\")", 
## "c(\"B09\", \"B09\")", "H02", "B13", "H38"), meters = c("6400", 
## "1600", "1600", "c(3200, 8000)", "c(3200, 8000)", "c(3200, 3200)", 
## "c(3200, 3200)", "1600", "4800", "6400"), DOB = c("1979-08-24", 
## "1980-05-05", "1979-03-17", "c(\"1981-11-30\", \"1981-11-30\")", 
## "c(\"1978-09-01\", \"1978-09-01\")", "c(\"1980-12-03\", \"1980-12-03\")", 
## "c(\"1978-04-25\", \"1978-04-25\")", "1979-06-22", "1978-10-09", 
## "1982-04-26"), Oct = c("W", "NW", "SW", "c(\"NE\", \"N\")", "c(\"NE\", \"N\")", 
## "c(\"NE\", \"NE\")", "c(\"NE\", \"NE\")", "SE", "N", "W"), Res_FROM = c("1979-08-15", 
## "1980-05-15", "1972-06-15", "c(\"1982-01-15\", \"1984-01-15\")", 
## "c(\"1982-01-15\", \"1984-01-15\")", "c(\"1980-12-15\", \"1983-08-15\")", 
## "c(\"1978-04-15\", \"1983-08-15\")", "1979-06-15", "1978-10-15", 
## "1982-04-15"), Res_TO = c("1991-05-15", "1991-04-15", "1979-08-15", 
## "c(\"1984-01-15\", \"1986-04-15\")", "c(\"1984-01-15\", \"1986-04-15\")", 
## "c(\"1983-08-15\", \"1991-03-15\")", "c(\"1983-08-15\", \"2000-01-15\")", 
## "1991-04-15", "1983-03-15", "1991-04-15"), Exp_FROM = c("1979-08-24", 
## "1980-05-15", "1979-03-17", "c(\"1982-01-15\", \"1984-01-15\")", 
## "c(\"1982-01-15\", \"1984-01-15\")", "c(\"1980-12-15\", \"1983-08-15\")", 
## "c(\"1978-04-25\", \"1983-08-15\")", "1979-06-22", "1978-10-15", 
## "1982-04-26"), Exp_TO = c("1988-12-31", "1988-12-31", "1979-08-15", 
## "c(\"1984-01-15\", \"1986-04-15\")", "c(\"1984-01-15\", \"1986-04-15\")", 
## "c(\"1983-08-15\", \"1988-12-31\")", "c(\"1983-08-15\", \"1988-12-31\")", 
## "1988-12-31", "1983-03-15", "1988-12-31"), Exps_Grp = c("fr51>88", 
## "fr51>88", "between", "c(\"between\", \"between\")", "c(\"between\", \"between\")", 
## "c(\"between\", \"fr51>88\")", "c(\"between\", \"fr51>88\")", 
## "fr51>88", "between", "fr51>88"), Yr1952 = c(NA, NA, NA, NA, 
## NA, NA, NA, NA, NA, NA), Yr1953 = c(NA, NA, NA, NA, NA, NA, NA, 
## NA, NA, NA), Yr1954 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## ), Yr1955 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Yr1956 = c(NA, 
## NA, NA, NA, NA, NA, NA, NA, NA, NA), Yr1957 = c(NA, NA, NA, NA, 
## NA, NA, NA, NA, NA, NA), Yr1958 = c(NA, NA, NA, NA, NA, NA, NA, 
## NA, NA, NA), Yr1959 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## ), Yr1960 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Yr1961 = c(NA, 
## NA, NA, NA, NA, NA, NA, NA, NA, NA), Yr1962 = c(NA, NA, NA, NA, 
## NA, NA, NA, NA, NA, NA), Yr1963 = c(NA, NA, NA, NA, NA, NA, NA, 
## NA, NA, NA), Yr1964 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## ), Yr1965 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Yr1966 = c(NA, 
## NA, NA, NA, NA, NA, NA, NA, NA, NA), Yr1967 = c(NA, NA, NA, NA, 
## NA, NA, NA, NA, NA, NA), Yr1968 = c(NA, NA, NA, NA, NA, NA, NA, 
## NA, NA, NA), Yr1969 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## ), Yr1970 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Yr1971 = c(NA, 
## NA, NA, NA, NA, NA, NA, NA, NA, NA), Yr1972 = c(NA, NA, NA, NA, 
## NA, NA, NA, NA, NA, NA), Yr1973 = c(NA, NA, NA, NA, NA, NA, NA, 
## NA, NA, NA), Yr1974 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## ), Yr1975 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Yr1976 = c(NA, 
## NA, NA, NA, NA, NA, NA, NA, NA, NA), Yr1977 = c(NA, NA, NA, NA, 
## NA, NA, NA, NA, NA, NA), Yr1978 = c(NA, NA, NA, NA, NA, NA, 79.39642441, 
## NA, 5.655852488, NA), Yr1979 = c(5.950991161, NA, 20.60898553, 
## NA, NA, NA, 59.94484924, 28.50091596, 16.41746701, NA), Yr1980 = c(4.340588078, 
## 2.927724588, NA, NA, NA, 0.758267013, 16.01840668, 12.90308755, 
## 4.387060214, NA), Yr1981 = c(4.340588078, 4.447228937, NA, NA, 
## NA, 16.01840668, 16.01840668, 12.90308755, 4.387060214, NA), 
##     Yr1982 = c(4.340588078, 4.447228937, NA, 15.36541238, 15.36541238, 
##     16.01840668, 16.01840668, 12.90308755, 4.387060214, 3.274931595
##     ), Yr1983 = c(4.340588078, 4.447228937, NA, 16.01840668, 
##     16.01840668, 16.01840668, 16.01840668, 12.90308755, 0.682590481, 
##     4.340588078), Yr1984 = c(4.340588078, 4.447228937, NA, 3.594414445, 
##     3.594414445, 16.01840668, 16.01840668, 12.90308755, NA, 4.340588078
##     ), Yr1985 = c(4.340588078, 4.447228937, NA, 3.052618478, 
##     3.052618478, 16.01840668, 16.01840668, 12.90308755, NA, 4.340588078
##     ), Yr1986 = c(4.340588078, 4.447228937, NA, 0.691807598, 
##     0.691807598, 16.01840668, 16.01840668, 12.90308755, NA, 4.340588078
##     ), Yr1987 = c(4.340588078, 4.447228937, NA, NA, NA, 16.01840668, 
##     16.01840668, 12.90308755, NA, 4.340588078), Yr1988 = c(1.083782142, 
##     1.110408824, NA, NA, NA, 3.999564755, 3.999564755, 3.221714571, 
##     NA, 1.083782142), Yrs_Exp = c(9.361643836, 8.635616438, 0.41369863, 
##     4.249315068, 4.249315068, 8.049315068, 10.69315068, 9.534246575, 
##     4.416438356, 6.687671233), arth_mean = c(4.175947792, 3.907637331, 
##     20.60898553, 7.744531916, 7.744531916, 12.98740872, 24.68073562, 
##     13.49473309, 5.98618177, 3.723093446), median = c(4.340588078, 
##     4.447228937, 20.60898553, 3.594414445, 3.594414445, 16.01840668, 
##     16.01840668, 12.90308755, 4.387060214, 4.340588078), cumulative.1 = c(41.75947792, 
##     35.16873597, 20.60898553, 38.72265958, 38.72265958, 116.8866785, 
##     271.4880918, 134.9473309, 35.91709062, 26.06165412), Age = c(9L, 
##     8L, 9L, 7L, 10L, 8L, 10L, 9L, 10L, 6L)), class = "data.frame", row.names = c(NA, 
## -10L))

Answer 1

如果你上面的10行数据集是dat，那么你可以将数据集融化成一个长格式（年列），限制在那些年列中的值超过4的行，计算行为 num_yr_above，并将年份值连接为 years_above.

然后加入 dat

library(data.table)
setDT(dat)

dat[melt(dat,id="ID",
         measure=patterns("Yr\d"))[value>4, .(
           num_yr_above=.N,
           years_above = list(gsub("Yr","",variable))),
           by=ID],
    on=.(ID)]

输出：（包括所有列，但这里我只显示添加到数据集中的新附加列）

       ID num_yr_above                       years_above
 1: 20106           10 1978,1979,1980,1981,1982,1983,...
 2: 20108            5          1978,1979,1980,1981,1982
 3: 20100            9 1979,1980,1981,1982,1983,1984,...
 4: 20102            1                              1979
 5: 20107            9 1979,1980,1981,1982,1983,1984,...
 6: 20101            7 1981,1982,1983,1984,1985,1986,...
 7: 20105            7 1981,1982,1983,1984,1985,1986,...
 8: 20103            2                         1982,1983
 9: 20104            2                         1982,1983
10: 20109            5          1983,1984,1985,1986,1987

如何计算个人超过某个值的年数并显示所述年份

How to calculate number of years individuals exceeded a value and display said years

r

dataframe

data.table