Question

我无法重现我的数据，因此我将提供类似的样本数据：

lst1 <- list(IT = c("Training", "Helpdesk"), Construction = c("Water", "Waste"))
lst2 <- list(Training = c("Alarm Engineer", "Backend Engineer"),
             Helpdesk = c("Analyst 1", "Analyst 2"),
             Water = c("Water 1", "Water 2"),
             Waste = c("Waste 1", "Waste 2", "Waste 3"))
lst3 <- list(`Alarm Engineer` = head(mtcars), `Backend Engineer` = head(VADeaths),
             `Analyst 1` = head(diamonds), `Analyst 2` = head(ChickWeight),
             `Water 1` = head(state.x77), `Water 2` = head(iris),
             `Waste 1` = head(CO2), `Waste 2` = head(cbind(letters, LETTERS)),
             `Waste 3` = state.abb)

第一个（lst1）我有一个长度为35的小嵌套列表：

head(dis_sub, 2)         
$IT
 [1] "Web Developer"         "Web Designer"          "Training"              "Testing"               "Technician"            "Technical Support"    
 [7] "Systems Engineer"      "Systems Analyst"       "Helpdesk"     

$Construction

 [1] "Water"                     "Waste"                     "Sustainability"            "Structural Engineer"       "Skilled Trades"           
 [6] "Site Manager"              "Mechanical and Electrical"

然后我有第二个长度为250（lst2）的嵌套列表：

head(sub_jobs, 2)
$Mechanical and Electrical

    [1] "Alarm Engineer"          "Backend Engineer"     "Biomass Engineer"                         
  [4] "Building Engineer"         "Cam Engineer"       "Electrician" 

$Helpdesk

 [1] "1st Line Analyst"                 "1st Line Desktop Support Analyst" "1st Line Engineer"                "1st Line Helpdesk"               
 [5] "1st Line Helpdesk Support"    "1st Line IT Support"    "1st Line IT

然后我有一个最终列表（lst3），这个列表是一个数据框列表，所有数据框都有一个公共变量，但有不同的观察数量：

   head(list_all, 2)
$Electrician
                              words
1                     17th edition 
2       17th edition qualification 
3           17th edition qualified 
4                          3 phase 
5                     access point 

$1st Line Helpdesk Support
                                        words
1                 1st line technical support 
2                      2nd line support team 
3                 2nd line technical support

现在您可能已经发现，在第一个列表中，在IT下我们看到了帮助台。在建设中，我们看到机械和电气

我想将这些字符转换为第二列中的列表。

然后从那里我们看到机械和电气下的清单2中我们有电工，在帮助台下我们看到第一线帮助台支持。然后，我希望将这些字符转换为列表3中的data.frames。

我制作这些名单并从那里开始可能是愚蠢的。我显然可以制作35和250的简单列表，我也有一个数据框，如：

dis           sub       norm
IT            Helpdesk  1st Line Helpdesk Support
IT            Helpdesk  Analyst
IT            Testing   Tester
Construction  Mech...   Electrician 
Construction  Mech..    Alarm Engineer 
Construction  Waste     Recycling Engineer

然后是一个完整的csv文件夹，每个文件夹都以上面的每个norm行命名，并包含data.frames，用于生成列表3中的data.frames列表。

我想要的是：

>List
$IT
   Helpdesk
            1st Line Helpdesk Support
                    1                 1st line technical support 
                    2                      2nd line support team 
                    3                 2nd line technical support
                    ...
            Analyst
                    ...
            ...
   Web developer
            ...
                    ...
   ...

$Construction
             Mechanical and Electrical
                             Electrician
                                     1                     17th edition 
                                     2       17th edition qualification 
                                     3           17th edition qualified

Answer 1

我们可以嵌套一个子集。

lst1 <- list(IT = c("Training", "Helpdesk"), Construction = c("Water", "Waste"))
lst2 <- list(Training = c("Alarm Engineer", "Backend Engineer"),
             Helpdesk = c("Analyst 1", "Analyst 2"),
             Water = c("Water 1", "Water 2"),
             Waste = c("Waste 1", "Waste 2", "Waste 3"))
lst3 <- list(`Alarm Engineer` = head(mtcars), `Backend Engineer` = head(VADeaths),
             `Analyst 1` = head(diamonds), `Analyst 2` = head(ChickWeight),
             `Water 1` = head(state.x77), `Water 2` = head(iris),
             `Waste 1` = head(CO2), `Waste 2` = head(cbind(letters, LETTERS)),
             `Waste 3` = state.abb)

数据

lapply(lst1, function(x) lapply(lst2[x], function(.x) lst3[.x])) $IT $IT$Training $IT$Training$`Alarm Engineer` mpg cyl disp hp drat wt qsec vs am gear carb Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1 $IT$Training$`Backend Engineer` Rural Male Rural Female Urban Male Urban Female 50-54 11.7 8.7 15.4 8.4 55-59 18.1 11.7 24.3 13.6 60-64 26.9 20.3 37.0 19.3 65-69 41.0 30.9 54.6 35.1 70-74 66.0 54.3 71.1 50.0 $IT$Helpdesk $IT$Helpdesk$`Analyst 1` # A tibble: 6 × 10 carat cut color clarity depth table price x y z <dbl> <ord> <ord> <ord> <dbl> <dbl> <int> <dbl> <dbl> <dbl> 1 0.23 Ideal E SI2 61.5 55 326 3.95 3.98 2.43 2 0.21 Premium E SI1 59.8 61 326 3.89 3.84 2.31 3 0.23 Good E VS1 56.9 65 327 4.05 4.07 2.31 4 0.29 Premium I VS2 62.4 58 334 4.20 4.23 2.63 5 0.31 Good J SI2 63.3 58 335 4.34 4.35 2.75 6 0.24 Very Good J VVS2 62.8 57 336 3.94 3.96 2.48 $IT$Helpdesk$`Analyst 2` weight Time Chick Diet 1 42 0 1 1 2 51 2 1 1 3 59 4 1 1 4 64 6 1 1 5 76 8 1 1 6 93 10 1 1

<强>输出

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R将列表字符转换为其他列表

1 个答案: