我有一些数据，我使用ArcGIS来获取，我想通过分水岭标识符构建数据库（例如HUC_8 = 1404106）。数据包含流域标识符（HUC_8），流域面积，土壤类型和土壤面积。分水岭标识符列为土壤类型的多次。我想创建一个基于分水岭的数据库（标识符只在列中出现一次），并按类型在不同的列中提取土壤区域。我附上了一部分数据，希望很清楚。我对R有点新，但我觉得这可以通过for循环来完成。知道如何做到这一点非常有帮助，因为我在GIS上工作很多，但想在R中进行更多的分析。
HUC_8 WatershedArea Soil SoilArea A_Area B_Area C_Area D_Area Null_Area
14040106 461104.4883 B 96590.33424
14040106 461104.4883 C 86282.93487
14040106 461104.4883 D 24945.9992
14050007 921494.3621 Null 2.861388
14050007 921494.3621 A 87214.28385
14050007 921494.3621 B 131417.8659
14050007 921494.3621 C 268324.5125
14050007 921494.3621 D 314131.5806
14060001 627348.8316 Null 8119.375083
14060001 627348.8316 A 5315.511117
14060001 627348.8316 B 286915.9001
14060001 627348.8316 C 114357.5251
14060001 627348.8316 D 163671.7545
答案 0 :(得分：0)
你可以尝试
lst <- Map(function(x,y) ifelse(df$Soil==x,y, NA),
sort(unique(df$Soil)), list(df$SoilArea))
names(lst) <- paste(names(lst), 'Area', sep="_")
df[names(lst)] <- lst
head(df,3)
# HUC_8 WatershedArea Soil SoilArea A_Area B_Area C_Area D_Area
#1 14040106 461104.5 B 96590.33 NA 96590.33 NA NA
#2 14040106 461104.5 C 86282.93 NA NA 86282.93 NA
#3 14040106 461104.5 D 24946.00 NA NA NA 24946
# Null_Area
#1 NA
#2 NA
#3 NA
如果您想从reshape到long wide，还可以使用base R reshape
df1 <- reshape(df, idvar=c('HUC_8', 'WatershedArea'),
timevar='Soil', direction='wide')
colnames(df1)[-(1:2)] <- paste0(gsub('.*\\.', '',
colnames(df1)[-(1:2)]), '_Area')
df1[,c(1:2,7,3:6)]
# HUC_8 WatershedArea A_Area B_Area C_Area D_Area Null_Area
#1 14040106 461104.5 NA 96590.33 86282.93 24946.0 NA
#4 14050007 921494.4 87214.284 131417.87 268324.51 314131.6 2.861388
#9 14060001 627348.8 5315.511 286915.90 114357.53 163671.8 8119.375083
df <- structure(list(HUC_8 = c(14040106L, 14040106L, 14040106L, 14050007L,
14050007L, 14050007L, 14050007L, 14050007L, 14060001L, 14060001L,
14060001L, 14060001L, 14060001L), WatershedArea = c(461104.4883,
461104.4883, 461104.4883, 921494.3621, 921494.3621, 921494.3621,
921494.3621, 921494.3621, 627348.8316, 627348.8316, 627348.8316,
627348.8316, 627348.8316), Soil = c("B", "C", "D", "Null", "A",
"B", "C", "D", "Null", "A", "B", "C", "D"), SoilArea = c(96590.33424,
86282.93487, 24945.9992, 2.861388, 87214.28385, 131417.8659,
268324.5125, 314131.5806, 8119.375083, 5315.511117, 286915.9001,
114357.5251, 163671.7545)), .Names = c("HUC_8", "WatershedArea",
"Soil", "SoilArea"), class = "data.frame", row.names = c(NA,
-13L))
答案 1 :(得分：0)
基本上，您可能希望将数据从长格式转换为宽格式。 reshape2库可以派上用场
#sample data
dd<-read.table(text="HUC_8 WatershedArea Soil SoilArea
14040106 461104.4883 B 96590.33424
14040106 461104.4883 C 86282.93487
14040106 461104.4883 D 24945.9992
14050007 921494.3621 Null 2.861388
14050007 921494.3621 A 87214.28385
14050007 921494.3621 B 131417.8659
14050007 921494.3621 C 268324.5125
14050007 921494.3621 D 314131.5806
14060001 627348.8316 Null 8119.375083
14060001 627348.8316 A 5315.511117
14060001 627348.8316 B 286915.9001
14060001 627348.8316 C 114357.5251
14060001 627348.8316 D 163671.7545", header=T)
现在转换数据
library(reshape2)
wide <- dcast(dd, HUC_8+ WatershedArea ~ Soil)
#change default column names
soils <- levels(dd$Soil)
names(wide)[match(soils, names(wide))] <- paste(soils,"Area",sep="_")
导致wide数据框看起来像
HUC_8 WatershedArea A_Area B_Area C_Area D_Area Null_Area
1 14040106 461104.5 NA 96590.33 86282.93 24946.0 NA
2 14050007 921494.4 87214.284 131417.87 268324.51 314131.6 2.861388
3 14060001 627348.8 5315.511 286915.90 114357.53 163671.8 8119.375083