如果满足两个条件,则平均两行

Question

我有一个名为的数据框df,看起来像这样;

id face value
1   r   15
1   r   11
1   t   16
1   t   17
2   r   13
2   r   25
2   t   12
2   t   18
3   r   30
3   r   20
3   t   19
3   t   10

因此,如果满足两个条件,我需要平均每一行.条件是; 如果id和face是相同的,那么平均value.

例如,if id=1,face=r然后是平均值15+11并将计算值13放在新列中.我必须为整个数据帧(2000行,500行不同id)执行此操作.

PS; 对于每一个face我必须有不同的列.我的意思是,例如,如果id=1并face=r把平均value在一个名为新列newr,如果id=2和face=r投入平均value在一个名为新列newr也是如此.那么,如果id=1和face=t投入平均value在一个名为新列newt.输出将是这样的;

id face newr newt
1   r    13
1   t        16.5
2   r   19
2   t        15

这是我的 str(df1)

Classes ‘data.table’ and 'data.frame':  340 obs. of  26 variables:
 $ id         : int  5 5 5 5 5 5 5 5 7 7 ...
 $ nirid      : chr  "bx5xtx1" "ax5xrx2" "bx5xrx2" "bx5xtx2" ...
 $ group      : Factor w/ 3 levels "a","b","r": 2 1 2 2 2 1 1 1 1 1 ...
 $ section    : Factor w/ 3 levels "","r","t": 3 2 2 3 2 3 2 3 2 3 ...
 $ face       : Factor w/ 3 levels "","1","2": 2 3 3 3 2 2 2 3 2 3 ...
 $ sample     : chr  "B3C-3D" "B3C-3D" "B3C-3D" "B3C-3D" ...
 $ treatment  : chr  "control" "control" "control" "control" ...
 $ width      : num  1 1 1 1 1 ...
 $ thick      : num  1.02 1.02 1.02 1.02 1.02 ...
 $ length     : num  16 16 16 16 16 ...
 $ testweight : num  126 126 126 126 126 ...
 $ maxload    : num  418 418 418 418 418 418 418 418 436 436 ...
 $ loadppl    : num  251 251 251 251 251 251 251 251 258 258 ...
 $ ppldistance: num  0.139 0.139 0.139 0.139 0.139 ...
 $ scmor      : num  0.399 0.399 0.399 0.399 0.399 ...
 $ scmoe      : num  5.53e-05 5.53e-05 5.53e-05 5.53e-05 5.53e-05 ...
 $ failure    : int  2 2 2 2 2 2 2 2 2 2 ...
 $ mcweight   : num  107 107 107 107 107 ...
 $ odweight   : num  94.1 94.1 94.1 94.1 94.1 94.1 94.1 94.1 90.3 90.3 ...
 $ mc         : num  13.3 13.3 13.3 13.3 13.3 ...
 $ sgsc       : num  0.415 0.415 0.415 0.415 0.415 ...
 $ scmorpsi   : num  58 58 58 58 58 ...
 $ scmoepsi   : num  8.03 8.03 8.03 8.03 8.03 ...
 $ rows       : chr  "9" "10" "11" "12" ...
 $ value        :Class 'AsIs'  num [1:238000] 0.0147 -0.0169 -0.0152 0.0135 -0.0107 ...
 $ sg42       :Class 'AsIs'  num [1:235280] 1.86e-04 9.39e-05 8.94e-05 1.83e-04 8.86e-05 ...
 - attr(*, ".internal.selfref")=<externalptr> 

更新

这是使用实际数据集的一小部分 dput(droplevels(head(data, 20)))

structure(list(id = c(5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 
7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L), nirid = c("bx5xtx1", 
"ax5xrx2", "bx5xrx2", "bx5xtx2", "bx5xrx1", "ax5xtx1", "ax5xrx1", 
"ax5xtx2", "ax7xrx1", "ax7xtx2", "ax7xrx2", "ax7xtx1", "ax8xrx2", 
"ax8xtx1", "ax8xrx1", "ax8xtx2", "ax9xtx2", "bx9xtx2", "ax9xrx2", 
"ax9xtx1"), group = c("b", "a", "b", "b", "b", "a", "a", "a", 
"a", "a", "a", "a", "a", "a", "a", "a", "a", "b", "a", "a"), 
    section = c("t", "r", "r", "t", "r", "t", "r", "t", "r", 
    "t", "r", "t", "r", "t", "r", "t", "t", "t", "r", "t"), face = c(1L, 
    2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 
    2L, 2L, 2L, 1L), sample = c("B3C-3D", "B3C-3D", "B3C-3D", 
    "B3C-3D", "B3C-3D", "B3C-3D", "B3C-3D", "B3C-3D", "B3C-1E", 
    "B3C-1E", "B3C-1E", "B3C-1E", "B1C-2D", "B1C-2D", "B1C-2D", 
    "B1C-2D", "A3C-2C", "A3C-2C", "A3C-2C", "A3C-2C"), treatment = c("control", 
    "control", "control", "control", "control", "control", "control", 
    "control", "control", "control", "control", "control", "control", 
    "control", "control", "control", "control", "control", "control", 
    "control"), width = c("1.003", "1.003", "1.003", "1.003", 
    "1.003", "1.003", "1.003", "1.003", "1.021", "1.021", "1.021", 
    "1.021", "1.02", "1.02", "1.02", "1.02", "1.033", "1.033", 
    "1.033", "1.033"), thick = c("1.02", "1.02", "1.02", "1.02", 
    "1.02", "1.02", "1.02", "1.02", "1.043", "1.043", "1.043", 
    "1.043", "1.025", "1.025", "1.025", "1.025", "1.029", "1.029", 
    "1.029", "1.029"), length = c("16", "16", "16", "16", "16", 
    "16", "16", "16", "15.98", "15.98", "15.98", "15.98", "16.016", 
    "16.016", "16.016", "16.016", "16.005", "16.005", "16.005", 
    "16.005"), testweight = c("126", "126", "126", "126", "126", 
    "126", "126", "126", "121.4", "121.4", "121.4", "121.4", 
    "144.1", "144.1", "144.1", "144.1", "119.6", "119.6", "119.6", 
    "119.6"), maxload = c(418L, 418L, 418L, 418L, 418L, 418L, 
    418L, 418L, 436L, 436L, 436L, 436L, 631L, 631L, 631L, 631L, 
    486L, 486L, 486L, 486L), loadppl = c("251", "251", "251", 
    "251", "251", "251", "251", "251", "258", "258", "258", "258", 
    "296", "296", "296", "296", "255", "255", "255", "255"), 
    ppldistance = c("0.1388", "0.1388", "0.1388", "0.1388", "0.1388", 
    "0.1388", "0.1388", "0.1388", "0.155", "0.155", "0.155", 
    "0.155", "0.1412", "0.1412", "0.1412", "0.1412", "0.1488", 
    "0.1488", "0.1488", "0.1488"), scmor = c("0.399330740757585", 
    "0.399330740757585", "0.399330740757585", "0.399330740757585", 
    "0.399330740757585", "0.399330740757585", "0.399330740757585", 
    "0.399330740757585", "0.391336060622532", "0.391336060622532", 
    "0.391336060622532", "0.391336060622532", "0.587001478757759", 
    "0.587001478757759", "0.587001478757759", "0.587001478757759", 
    "0.442958394865818", "0.442958394865818", "0.442958394865818", 
    "0.442958394865818"), scmoe = c("5.5328050375923e-05", "5.5328050375923e-05", 
    "5.5328050375923e-05", "5.5328050375923e-05", "5.5328050375923e-05", 
    "5.5328050375923e-05", "5.5328050375923e-05", "5.5328050375923e-05", 
    "4.6792031310635e-05", "4.6792031310635e-05", "4.6792031310635e-05", 
    "4.6792031310635e-05", "6.2150955161815e-05", "6.2150955161815e-05", 
    "6.2150955161815e-05", "6.2150955161815e-05", "4.9585347590597e-05", 
    "4.9585347590597e-05", "4.9585347590597e-05", "4.9585347590597e-05"
    ), failure = c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L), mcweight = c("106.6", 
    "106.6", "106.6", "106.6", "106.6", "106.6", "106.6", "106.6", 
    "102.1", "102.1", "102.1", "102.1", "121.9", "121.9", "121.9", 
    "121.9", "100.7", "100.7", "100.7", "100.7"), odweight = c("94.1", 
    "94.1", "94.1", "94.1", "94.1", "94.1", "94.1", "94.1", "90.3", 
    "90.3", "90.3", "90.3", "107.1", "107.1", "107.1", "107.1", 
    "88.3", "88.3", "88.3", "88.3"), mc = c("13.2837407013815", 
    "13.2837407013815", "13.2837407013815", "13.2837407013815", 
    "13.2837407013815", "13.2837407013815", "13.2837407013815", 
    "13.2837407013815", "13.0675526024363", "13.0675526024363", 
    "13.0675526024363", "13.0675526024363", "13.8188608776844", 
    "13.8188608776844", "13.8188608776844", "13.8188608776844", 
    "14.0430351075878", "14.0430351075878", "14.0430351075878", 
    "14.0430351075878"), sgsc = c("0.414649099500969", "0.414649099500969", 
    "0.414649099500969", "0.414649099500969", "0.414649099500969", 
    "0.414649099500969", "0.414649099500969", "0.414649099500969", 
    "0.385028360121945", "0.385028360121945", "0.385028360121945", 
    "0.385028360121945", "0.461392466167132", "0.461392466167132", 
    "0.461392466167132", "0.461392466167132", "0.376174963976185", 
    "0.376174963976185", "0.376174963976185", "0.376174963976185"
    ), scmorpsi = c("57.9580175265", "57.9580175265", "57.9580175265", 
    "57.9580175265", "57.9580175265", "57.9580175265", "57.9580175265", 
    "57.9580175265", "56.79768659253", "56.79768659253", "56.79768659253", 
    "56.79768659253", "85.1961507631", "85.1961507631", "85.1961507631", 
    "85.1961507631", "64.2900427962", "64.2900427962", "64.2900427962", 
    "64.2900427962"), scmoepsi = c("8.0301959907", "8.0301959907", 
    "8.0301959907", "8.0301959907", "8.0301959907", "8.0301959907", 
    "8.0301959907", "8.0301959907", "6.7912962715", "6.7912962715", 
    "6.7912962715", "6.7912962715", "9.0204579335", "9.0204579335", 
    "9.0204579335", "9.0204579335", "7.1967122773", "7.1967122773", 
    "7.1967122773", "7.1967122773"), rows = 9:28, value = c("0.014680833", 
    "-0.0169", "-0.015241563", "0.013507307", "-0.010687351", 
    "0.000479", "-0.0311", "-7.18e-05", "-0.037", "-0.00349", 
    "-0.0395", "-0.000859", "-0.018", "0.000127", "-0.0234", 
    "0.00215", "-0.0165", "-0.0162", "-0.0286", "-0.0214"), sg42 = c("0.000185853584415584", 
    "9.39393939393943e-05", "8.93772943722944e-05", "0.000183087277056277", 
    "8.86156017316018e-05", "0.000180270562770563", "9.02597402597403e-05", 
    "0.0001831779004329", "8.26839826839824e-05", "0.000167605411255411", 
    "8.44155844155841e-05", "0.000175891774891775", "9.1774891774892e-05", 
    "0.000180465367965368", "9.02597402597405e-05", "0.000178874458874459", 
    "0.000160822510822511", "0.000154978354978355", "8.26839826839826e-05", 
    "0.000159090909090909")), .Names = c("id", "nirid", "group", 
"section", "face", "sample", "treatment", "width", "thick", "length", 
"testweight", "maxload", "loadppl", "ppldistance", "scmor", "scmoe", 
"failure", "mcweight", "odweight", "mc", "sgsc", "scmorpsi", 
"scmoepsi", "rows", "value", "sg42"), row.names = c(NA, 20L), class = "data.frame")

预期结果列newr,newt,newrsg42和newtsg42

非常感谢你 :)

Answer 1

这是一个使用aggregate()和的解决方案reshape():

df <- data.frame(id=c(1L,1L,1L,1L,2L,2L,2L,2L,3L,3L,3L,3L),face=c('r','r','t','t','r','r','t','t','r','r','t','t'),value=c(15L,11L,16L,17L,13L,25L,12L,18L,30L,20L,19L,10L),stringsAsFactors=F);
reshape(transform(aggregate(value~face+id,df,mean),time=face),dir='w',idvar=c('id','face'));
##   face id value.r value.t
## 1    r  1      13      NA
## 2    t  1      NA    16.5
## 3    r  2      19      NA
## 4    t  2      NA    15.0
## 5    r  3      25      NA
## 6    t  3      NA    14.5