订单因子水平，其中所述水平显示在数据

这是我从互联网加载的数据帧的一部分使用readHTMLtable：订单因子水平，其中所述水平显示在数据

head(tt,59) 
    year   sport      event  athlete_id medal 
1 1896 Track & Field     100m Men  BURKETOM01 GOLD 
2 1896 Track & Field     100m Men  HOFMAFRI01 SILVER 
3 1896 Track & Field     100m Men  LANEFRA01 BRONZE 
4 1896 Track & Field     100m Men  SZOKOALA01 BRONZE 
5 1896 Track & Field     400m Men  BURKETOM01 GOLD 
6 1896 Track & Field     400m Men  JAMISHER01 SILVER 
7 1896 Track & Field     400m Men  GMELICHA01 BRONZE 
8 1896 Track & Field     800m Men  FLACKTED01 GOLD 
9 1896 Track & Field     800m Men D<C1>NIN<C1>N01 SILVER 
10 1896 Track & Field     800m Men  GOLEMDEM01 BRONZE 
11 1896 Track & Field     1500m Men  FLACKTED01 GOLD 
12 1896 Track & Field     1500m Men  BLAKEART01 SILVER 
13 1896 Track & Field     1500m Men  LERMUALB01 BRONZE 
14 1896 Track & Field    Marathon Men  LOUISSPI01 GOLD 
15 1896 Track & Field    Marathon Men  VASILCHA01 SILVER 
16 1896 Track & Field    Marathon Men  KELLNGYU01 BRONZE 
17 1896 Track & Field   110m Hurdles Men  CURTITOM01 GOLD 
18 1896 Track & Field   110m Hurdles Men  GOULDGRA01 SILVER 
19 1896 Track & Field    High Jump Men  CLARKELL01 GOLD 
20 1896 Track & Field    High Jump Men  CONNOJAM01 SILVER 
21 1896 Track & Field    High Jump Men  GARREBOB01 SILVER 
22 1896 Track & Field    Pole Vault Men  HOYTBIL01 GOLD 
23 1896 Track & Field    Pole Vault Men  TYLERALB01 SILVER 
24 1896 Track & Field    Pole Vault Men  THEODIOA01 BRONZE 
25 1896 Track & Field    Pole Vault Men  DAMASEVA01 BRONZE 
26 1896 Track & Field    Long Jump Men  CLARKELL01 GOLD 
27 1896 Track & Field    Long Jump Men  GARREBOB01 SILVER 
28 1896 Track & Field    Long Jump Men  CONNOJAM01 BRONZE 
29 1896 Track & Field   Triple Jump Men  CONNOJAM01 GOLD 
30 1896 Track & Field   Triple Jump Men TUFF<C8>ALE01 SILVER 
31 1896 Track & Field   Triple Jump Men  PERSAIOA01 BRONZE 
32 1896 Track & Field    Shot Put Men  GARREBOB01 GOLD 
33 1896 Track & Field    Shot Put Men  GOUSKMIL01 SILVER 
34 1896 Track & Field    Shot Put Men  PAPASGEO01 BRONZE 
35 1896 Track & Field   Discus Throw Men  GARREBOB01 GOLD 
36 1896 Track & Field   Discus Throw Men  PARASPAN01 SILVER 
37 1896 Track & Field   Discus Throw Men  VERSISOT01 BRONZE 
38 1896  Cycling 2000m Sprint (Scratch) Men  MASSOPAU01 GOLD 
39 1896  Cycling 2000m Sprint (Scratch) Men  NIKOLSTA01 SILVER 
40 1896  Cycling 2000m Sprint (Scratch) Men FLAMEL<C9>O01 BRONZE 
41 1896  Cycling Individual Road Race Men  KONSTARI01 GOLD 
42 1896  Cycling Individual Road Race Men  GOEDRAUG01 SILVER 
43 1896  Cycling Individual Road Race Men  BATTEEDW01 BRONZE 
44 1896  Cycling    One-Lap Race  MASSOPAU01 GOLD 
45 1896  Cycling    One-Lap Race  NIKOLSTA01 SILVER 
46 1896  Cycling    One-Lap Race  SCHMAADO01 BRONZE 
47 1896  Cycling   10km Track Race  MASSOPAU01 GOLD 
48 1896  Cycling   10km Track Race FLAMEL<C9>O01 SILVER 
49 1896  Cycling   10km Track Race  SCHMAADO01 BRONZE 
50 1896  Cycling   100km Track Race FLAMEL<C9>O01 GOLD 
51 1896  Cycling   100km Track Race  KOLETGEO01 SILVER 
52 1896  Cycling    12-Hour Race  SCHMAADO01 GOLD 
53 1896  Cycling    12-Hour Race  KEEPIFRA01 SILVER 
54 1896  Fencing   Foil, Individual  GRAVEEUG01 GOLD 
55 1896  Fencing   Foil, Individual  CALLOHEN01 SILVER 
56 1896  Fencing   Foil, Individual  PIERRPER01 BRONZE 
57 1896  Fencing   Sabre, Individual  GEORGIOA01 GOLD 
58 1896  Fencing   Sabre, Individual  KARAKTEL01 SILVER 
59 1896  Fencing   Sabre, Individual  NIELSHOL01 BRONZE

正如你可以看到变量sport是一个因素。当我检查的水平，这是我所得到的：

levels(tt$sport) 
[1] "Cycling"  "Fencing"  "Gymnastics" "Shooting"  "Swimming"  "Tennis" 
[7] "Track & Field" "Weightlifting" "Wrestling

出于某种原因，其中水平出现不匹配的数据帧顺序的顺序。我正在寻找一种方式，其中使用水平的功能会给我根据第一次亮相组织级别的列表，类似的东西：

levels(medals.df$tt) 
[1] "Track & Field" "Cycling"  "Fencing"  "Gymnastics" "Shooting" "Swimming" 
[7] "Tennis"  "Weightlifting" "Wrestling"

现在，另一件事要记住的是，列运动是而不是“块设计”，这意味着前59行具有相同的相邻值，但在整个数据框中不是这样。

来源

2016-07-23 Lee

请注意，我必须调整您的数据集，以便您列出的所有级别出现，并按照您指定的顺序进行。从那里，我写了一个简单的函数，按照它们出现在数据集中的顺序输出这些级别。关键是要使用which（其中列出符合标准的观察行数），min（选择最低值）和order（它告诉您使用的顺序以从最低到最高）。

d <- read.table(text="rn year sport   event  athlete_id medal 
1 1896 'Track & Field'     '100m Men'  'BURKETOM01' 'GOLD' 
53 1896  'Cycling'    '12-Hour Race'  'KEEPIFRA01' 'SILVER' 
54 1896  'Fencing'   'Foil, Individual'  'GRAVEEUG01' 'GOLD' 
55 1896  'Gymnastics'   'Foil, Individual'  'CALLOHEN01' 'SILVER' 
56 1896  'Shooting'   'Foil, Individual'  'PIERRPER01' 'BRONZE' 
57 1896  'Swimming'   'Sabre, Individual'  'GEORGIOA01' 'GOLD' 
58 1896  'Tennis'   'Sabre, Individual'  'KARAKTEL01' 'SILVER' 
58 1896  'Weightlifting'   'Sabre, Individual'  'KARAKTEL01' 'SILVER' 
59 1896  'Wrestling'   'Sabre, Individual'  'NIELSHOL01' 'BRONZE'", 
       header=T) 

levels(d$sport) 
# [1] "Cycling"  "Fencing"  "Gymnastics" "Shooting"  
# [5] "Swimming"  "Tennis"  "Track & Field" "Weightlifting" 
# [9] "Wrestling"  

level.order <- function(var){ 
    l <- levels(var) 
    o <- c() 
    for(i in 1:length(l)){ 
    o[i] <- min(which(var==l[i])) 
    } 
    return(l[order(o)]) 
} 
level.order(d$sport) 
# [1] "Track & Field" "Cycling"  "Fencing"  "Gymnastics" 
# [5] "Shooting"  "Swimming"  "Tennis"  "Weightlifting" 
# [9] "Wrestling"

从这里，如果你想改变默认的排序（按字母顺序排列）的水平在数据集中显示的顺序，你会使用factor。试想一下：

levels(d$sport) 
# [1] "Cycling"  "Fencing"  "Gymnastics" "Shooting"  
# [5] "Swimming"  "Tennis"  "Track & Field" "Weightlifting" 
# [9] "Wrestling"  
d$sport <- factor(d$sport, levels=level.order(d$sport)) 
levels(d$sport) 
# [1] "Track & Field" "Cycling"  "Fencing"  "Gymnastics" 
# [5] "Shooting"  "Swimming"  "Tennis"  "Weightlifting" 
# [9] "Wrestling"

来源

2016-07-23 20:25:54 gung

相反的'level.order（）'函数你也可以使用：'d $ sport < - factor（d $ sport，levels = unique（d $ sport））''。 –

不错的一点，@KenS。我不知道'unique（）'总是按照它们出现的顺序列出这些值。你为什么不作出正式答案？ – gung

它的工作，谢谢 – Lee

我使用的数据帧@gung在他的回答设置：

d <- read.table(text="rn year sport   event  athlete_id medal 
1 1896 'Track & Field'     '100m Men'  'BURKETOM01' 'GOLD' 
53 1896  'Cycling'    '12-Hour Race'  'KEEPIFRA01' 'SILVER' 
54 1896  'Fencing'   'Foil, Individual'  'GRAVEEUG01' 'GOLD' 
55 1896  'Gymnastics'   'Foil, Individual'  'CALLOHEN01' 'SILVER' 
56 1896  'Shooting'   'Foil, Individual'  'PIERRPER01' 'BRONZE' 
57 1896  'Swimming'   'Sabre, Individual'  'GEORGIOA01' 'GOLD' 
58 1896  'Tennis'   'Sabre, Individual'  'KARAKTEL01' 'SILVER' 
58 1896  'Weightlifting'   'Sabre, Individual'  'KARAKTEL01' 'SILVER' 
59 1896  'Wrestling'   'Sabre, Individual'  'NIELSHOL01' 'BRONZE'", 
      header=T) 

levels(d$sport)

然后你可以使用unique(d$sport)中的影响因子函数是这样的：

d$sport <- factor(d$sport, levels=unique(d$sport)) 
# Check the results: 
levels(d$sport)

来源

2016-07-24 08:28:18

订单因子水平，其中所述水平显示在数据

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