R:错误:在dplyr中使用unnest时，长度不兼容 [英] R: Error: Incompatible lengths when using unnest in dplyr

问题描述

我有一个小标题(此处).我通过使用此原始数据集并运行以下数据(之前的文章此处):

I have a large tibble (here). I created it by using this original dataset and running the following (previous post here):

#this code seemed to work
    library(tidyverse)
    df_tib <- df_full_subset %>%
      pivot_longer(cols = everything(), names_to = c("name", ".value"), names_pattern = "(.*)_(.*)") %>%
      select(-name) %>%
      pivot_wider(names_from = "01", values_from = "02", values_fn = list)

从上一篇文章中可以看出，有最后一部分代码可以嵌套该数据.这对我不起作用，因此我修改了小标题，发现了几根垃圾柱(例如，一列NA)，并删除了那些可能会有所帮助的想法.但是，我一直收到相同的错误:"错误:不兼容的长度:254、257" .这对我来说就像 dplyr 在第254行和第257行中的NA挣扎一样，但是我看到其他帖子似乎很容易处理(例如

As can be seen in the previous post, there was a final bit of code to unnest that data. That didn't work for me so I tinkered with the tibble and found a few rubbish columns (e.g. a column of NAs), and removed those thinking that might help. However, I keep getting the same error: "Error: Incompatible lengths: 254, 257". This reads to me like dplyr is struggling with NAs in rows 254 and 257, but I've seen other posts where this seems to be easily dealt with (like this one that used filter), and those solutions did not work for this data.

#cleaning the data
df_tib$habitat <- df_tib$habitat_
df_tib$species <- df_tib$species_
df_tib <- janitor::clean_names(df_tib)
df_tib <- df_tib %>% 
  select(-habitat_,-species_, -na)

df_tib <- df_tib %>% 
  unnest(cols = everything()) #does not work

非常感谢您的帮助.

推荐答案

我刚刚注意到您的数据中有第一列 X ，不需要 包含在您的 pivot_longer 语句中.要透视除X以外的所有列，可以执行 pivot_longer(cols = -X，...).

I just noticed you have a first column X in your data, that does not need to be included in your pivot_longer statement. To pivot all columns except for X, you can do pivot_longer(cols = -X, ...).

我还添加了 drop_na ，您可能打算在 pivot_longer 之后添加.该 NA 列否则缺少值，objectid和editMode.

I also added drop_na which you may have intended after pivot_longer. This NA column otherwise had missing values, objectid, and editMode.

尝试以下方法:

library(tidyverse)

df %>%
  pivot_longer(cols = -X, names_to = c("name", ".value"), names_pattern = "(.*)_(.*)") %>%
  drop_na %>%
  select(-name) %>%
  pivot_wider(names_from = "01", values_from = "02", values_fn = list) %>%
  unnest(cols = everything())

输出

       X bearing_degrees coordinates distance_meters habitat_ how_many_animal… observers species_ was_a_group_of_… was_the_animal_… width_of_the_ro… what_species_of… livestock
   <int> <chr>           <chr>       <chr>           <chr>    <chr>            <chr>     <chr>    <chr>            <chr>            <chr>            <chr>            <chr>    
 1     1 200             N1.20701 E… 100             open_sc… 4                TW2       giraffe  group_           "alive"          single_lane      NA               NA       
 2     2 300             N1.20195 E… 20              commiph… NA               TW2 o     gerenuk  individual       "alive"          single_lane      NA               NA       
 3     3 10              N1.18823 E… 80              open_sc… NA               TW2       bird     individual       "alive"          single_lane      Ostrich          NA       
 4     4 20              N1.15642 E… 180             open_sc… 300              TW2       livesto… group_           "alive"          single_lane      NA               shoat    
 5     5 300             N1.14868 E… 30              open_sc… 7                TW2       livesto… group_           "alive"          single_lane      NA               cattle   
 6     6 70              N1.13874 E… 200             open_sc… 34               TW2       livesto… group_           "alive"          single_lane      NA               cattle   
 7     7 20              N1.11442 E… 40              disturb… 12               TW2       livesto… group_           "alive"          single_lane      NA               cattle   
 8     8 NA              N1.03003 E… NA              commiph… NA               TW2       jackal   NA               "roadkill"       single_lane      NA               NA       
 9     9 40              N1.97961 E… 50              mixed_s… null             TW2       gerenuk  individual       "alive,\n    wh… NA               NA               null     
10    10 20              N0.85822 E… 20              dense_s… 53               TW2       baboon   group_           "alive"          single_lane      NA               NA       
# … with 251 more rows, and 5 more variables: approximate_age_of_individual <chr>, approximate_number_of_days_sinc <chr>, sex_of_animal <chr>, generated_note_survey <chr>,
#   `_date` <chr>

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