问题描述
我是R的初学者，以前从未处理过此类数据。我有以下两种类型的示例数据集（df1和df2），如下所示：
df1 <- c("{\"\"Wednesday\"\":4,\"\"Monday\"\":5,\"\"Saturday\"\":4,\"\"Thursday\"\":4,\"\"Tuesday\"\":5,\"\"Friday\"\":1,\"\"Sunday\"\":5,\"\"Missing day\"\":2}","{\"\"Wednesday\"\":6,\"\"Saturday\"\":2,\"\"Thursday\"\":6,\"\"Tuesday\"\":0,\"\"Friday\"\":2,\"\"Sunday\"\":4,\"\"Missing day\"\":1}","{\"\"Wednesday\"\":5,\"\"Saturday\"\":3,\"\"Thursday\"\":8,\"\"Tuesday\"\":4,\"\"Friday\"\":3,\"\"Sunday\"\":6,\"\"Missing day\"\":4}","{\"\"Wednesday\"\":3,\"\"Thursday\"\":1,\"\"Friday\"\":4,\"\"Missing day\"\":6}")
df2 <- c("[373,357,382,411,310,315,330,385,367,396,402,348,354,343,392,395,401,376,448,341,373,369,304,298,332,366,287,334,222]","[319,347,284,313,300,292,228,322,291,275,278,289,323,342,272,242,295,290,337,309,268,251,256,266,346,260,232,160]","[165,154,161,152,164,156,150,137,170,147,210,235,190,176,175,191,186,209,157,199,162,149,165,174,171,178,126]","[253,274,240,258,264,231,296,233,230,252,229,270,297,255,253,250,299,305,308,263,141]")
现在，我需要将df1转换为 df1_final ，并将df2转换为 df2_final 。最终数据集如下所示：
df1_final <- data.frame("Day"=c("Wednesday","Monday","Saturday","Thursday","Tuesday","Friday","Sunday","Missing day"),"Count1"=c(4,5,4,1,2),"Count2"=c(6,2,6,1),"Count3"=c(5,3,8,4),"Count4"=c(3,6))
df2_final <- data.frame("group1"=c(373,222),"group2"=c(319,160),"group3"=c(165,126),"group4"=c(253,141))
有人可以帮我解决这个问题吗？感谢任何帮助。谢谢!!
解决方法
因此您可以使用网状或jsonlite。我将使用Jsonlite，如下所示：
df1：
df1_f <- jsonlite::fromJSON(gsub('"+','"',sprintf("[%s]",paste0(df1,collapse = ","))))
data.frame(Day = names(df1_f),`colnames<-`(t(df1_f),paste0("count",1:4)),row.names = NULL)
Day count1 count2 count3 count4
1 Wednesday 4 6 5 3
2 Monday 5 5 5 5
3 Saturday 4 2 3 4
4 Thursday 4 6 8 1
5 Tuesday 5 0 4 5
6 Friday 1 2 3 4
7 Sunday 5 4 6 4
8 Missing day 2 1 4 6
df2的，因为列表不在{}内，我们将必须手动将其转换为数据框：
df2_fin <- jsonlite::fromJSON(sprintf("[%s]",paste0(df2,")))
(df2_final <- setNames(data.frame(t(df2_fin)),paste0("group",1:4)))
group1 group2 group3 group4
1 373 319 165 253
2 357 347 154 274
3 382 284 161 240
4 411 313 152 258
5 310 300 164 264
6 315 292 152 231
7 330 228 156 296
8 385 322 150 233
9 367 291 137 230
10 396 275 170 252
11 402 278 147 210
12 348 289 210 233
13 354 323 235 233
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