如何在將非空間對象連接到幾何數據/多邊形時獲得NA值？

Question

我想通過「ward.name」將非空間對象（Merged_Census2011）加入到shapefile多邊形（LDN_wards）中。它看起來工作正常，直到我看到新創建的對象，並看到所有數據都變成了NAs。以下是我如何繼續。

#Join Merged_Census2011 data to LDN_wards shapefile 
LDN_wards <- readOGR(dsn = "data", layer = "LDN_wards") 
head(LDN_wards@data) 
#Explore the object 
plot(LDN_wards) 
summary(LDN_wards) 
names(Merged_Census2011) 
names(LDN_wards) 
names(LDN_wards) <- c("Code", "ward.name") #rename LND-wards name heading to ward.name so it can be matched later 

#Join datasets 
LDN_wards@data <- left_join(LDN_wards@data, Merged_Census2011) 
head(LDN_wards@data) 

我也得到：

LDN_wards@data <- left_join(LDN_wards@data, Merged_Census2011) 
Joining by: "ward.name" 
Warning message: 
In left_join_impl(x, y, by$x, by$y) : 
joining factors with different levels, coercing to character vector 
> head(LDN_wards@data) 
    Code ward.name ward.code.x electorate votescast ward.code.y per.owner per.white per.noquals per.degree per.couple 
1 E05000001 Aldersgate  <NA>   NA  NA  <NA>  NA  NA   NA   NA   NA 
2 E05000002  Aldgate  <NA>   NA  NA  <NA>  NA  NA   NA   NA  

我有直覺，這是因爲在兩個集合之間不同的數字行。這可能是問題嗎？是否不可能加入具有不同行級別的數據集（據此，缺少的數據在相應的觀測中仍然不匹配）？ 我曾比較了兩組數據如下：

#Compare the two datasets 
nrow(LDN_wards) 
nrow(Merged_Census2011) 
LDN_wards$ward.name %in% Merged_Census2011$ward.name 
LDN_wards$ward.name %in% Merged_Census2011$ward.name 
> nrow(LDN_wards) 
[1] 787 
> nrow(Merged_Census2011) 
[1] 668 
> LDN_wards$ward.name %in% Merged_Census2011$ward.name 
    [1] FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSEFALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
[21] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE 
    [41] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE ETC... 
> summary(LDN_wards$ward.name %in% Merged_Census2011$ward.name) 
    Mode FALSE TRUE NA's 
logical  24  763  0 

難道是因爲FALSE = 24？如果是這樣，我該如何刪除這些錯誤？

道歉，如果這聽起來很明顯，我是相當新:)

感謝您的幫助！

Answer 1

我剛剛嘗試使用（新發現的）inner_join函數，它似乎工作。如果我理解的很好，inner_join函數只會合併匹配的行......所以我認爲它會更好。事實上，我不再獲得NA值。但奇怪的是，我得到了重複的觀察結果......如果有人有更好的建議，歡迎您分享。請參閱下面的會議錄。

#Join datasets 
LDN_wards@data <- inner_join(LDN_wards@data, Merged_Census2011) 
head(LDN_wards@data, n=10) 

> #Join datasets 
> LDN_wards@data <- inner_join(LDN_wards@data, Merged_Census2011) 
Joining by: c("ward.name", "ward.code.x", "electorate", "votescast","ward.code.y", "per.owner", "per.white", "per.noquals", "per.degree", "per.couple", "per.higher.managerial", "per.christian", "per.no.car", "per.limill", "per.goodhealth", "per.males", "per.aged60plus") 
Warning message: 
In inner_join_impl(x, y, by$x, by$y) : 
joining character vector and factor, coercing into character vector 
> head(LDN_wards@data, n=10) 
    Code  ward.name ward.code.x electorate votescast ward.code.y per.owner per.white per.noquals per.degree per.couple 
1 E05000007   Bridge E05000497  8677  5654 E05000497  69.8  71.9  19.9  29.9  55.3 
2 E05000026   Abbey E05000026  8110  4712 E05000026  32.7  28.1  16.4  34.5  47.2 
3 E05000026   Abbey E05000026  8110  4712 E05000455  48.5  73.4  10.1  55.4  52.4 
4 E05000026   Abbey E05000455  7250  4808 E05000026  32.7  28.1  16.4  34.5  47.2 
5 E05000026   Abbey E05000455  7250  4808 E05000455  48.5  73.4  10.1  55.4  52.4 
6 E05000027   Alibon E05000027  6971  4127 E05000027  45.1  70.1  31.2  16.7  49.2 
7 E05000028  Becontree E05000028  7535  4538 E05000028  46.7  58.8  28.0  20.6