Создайте сюжет Ликерта с двумя группами в R - PullRequest
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Создайте сюжет Ликерта с двумя группами в R

1 голос
/ 10 февраля 2020

У меня проблемы с попыткой создать сюжет Ликерта с двумя группами. Я провел опрос в двух сообществах. Теперь я хочу сравнить эти два сообщества. [Это мой фрейм данных] [1]. Пока что я загрузил лист с 3 колонками. Один столбец относится к местоположению (community1, community2), один включает ответы относительно econ_comm (1-6), а другой включает ответы относительно future_persp (1-6). Я создал объект likert и первую фигуру. 

g_likert = likert(g[1:6])
plot(g_likert, ordered = FALSE, group.order = names(g[2:3]))

... и это сработало. Следующее - это то, что я получил до сих пор. [! [введите описание изображения здесь] [2]] [2]

Полагаю, сейчас важно сначала создать объект-объект: both<-g$Location (работал)

Теперь я начинаются проблемы. Следующий код показывает мне ошибки: 

both_likert_2 = likert(both[, c(1:3), drop=FALSE], grouping = both$location)
plot(both_likert_2, include.histogram = TRUE)

Ошибки:

Ошибка в [.data.frame (g, 1: 6): выбраны неопределенные столбцы

Ошибка в [.default (оба, c (1: 3), drop = FALSE): неверное число измерений - объект 'both_likert_2' не найден

[У меня сейчас также приложил скриншот моего R, просто чтобы убедиться.] [4] Я уже довольно долго борюсь и буду очень признателен за помощь. Лучший, Феликс

РЕДАКТИРОВАТЬ: [! [Это моя текущая ситуация в R] [5]] [5] Вот мой код для воспроизведения: 

library(likert)
g<-read.csv2("C:/Users/felix/OneDrive/Documents/R/SurveyData2.csv", sep=";", dec=",", header=TRUE)
both<-g$Location
g <-  within(g, {
  gold_21cent <- factor(gold_21cent, levels=1:6, labels=c("Completely agree", "Agree", "Slightly agree", "Slightly disagree", "Disagree", "Completely disagree"))
  future_persp <- factor(future_persp, levels=1:6, labels=c("Completely agree", "Agree", "Slightly agree", "Slightly disagree", "Disagree", "Completely disagree"))
 jobs_comm <- factor(jobs_comm, levels=1:6, labels=c("Completely agree", "Agree", "Slightly agree", "Slightly disagree", "Disagree", "Completely disagree"))
} )
.........etc............
comm_likert = likert(g[,2:14], grouping=g[,1])
plot(comm_likert)
library(dplyr)
g %>%

rename (It offers important economic perspectives = future_persp, It provides economic prosperity to the community = econ_comm)%>% likert (группировка = расположение)%>% plot ()

РЕДАКТИРОВАТЬ: Использование dput (g) 

structure(list(Location = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L), .Label = c("Huan", "TP"), class = "factor"), 
gold_21cent = structure(c(6L, 6L, 3L, 3L, 2L, 2L, 2L, 2L, 
2L, 6L, 3L, 2L, 2L, 3L, 2L, 3L, 1L, 3L, 2L, NA, NA, 1L, 1L,
6L, 4L, 6L, 5L, 2L, 2L, 2L, 4L, 4L, 3L, 3L, 2L, 3L, 2L, 3L, 
3L, NA, 2L, 3L, 2L, NA, 2L, 2L, 3L, 5L, 3L, 3L, 3L, 3L, 3L, 
3L, 4L, 2L, 3L, 6L), .Label = c("Completely agree", "Agree", 
"Slightly agree", "Slightly disagree", "Disagree", "Completely disagree"
), class = "factor"), life_quality = structure(c(3L, 3L, 
6L, 6L, 5L, 5L, 6L, 5L, 6L, 3L, 3L, 6L, 4L, 6L, 6L, 6L, 6L, 
6L, 6L, NA, NA, 3L, 5L, 6L, 2L, 6L, 5L, 3L, 2L, 3L, 1L, 1L, 
2L, 2L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 3L, 2L, 3L, 1L, 2L, NA, 
3L, 2L, 2L, 3L, 3L, 3L, 5L, 5L, 3L, 2L, 3L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), coexist_tradact = structure(c(6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 2L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 5L, 5L, 6L, 2L, 6L, 1L, 6L, 5L, 6L, 6L, 6L, 1L, 
4L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 4L, 3L, 2L, 3L, 3L, 3L, 
4L, 4L, 3L, 2L, 4L, 5L, 4L, 2L, 4L, 6L, 3L, 2L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), emigration_comm = structure(c(6L, 
6L, 6L, 6L, 6L, 6L, 6L, 5L, 6L, 6L, 5L, NA, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, NA, NA, 4L, 2L, 1L, 3L, 1L, 1L, 6L, 6L, 6L, 2L, 
1L, 3L, 3L, 3L, 1L, 3L, 1L, 2L, 1L, 2L, 2L, 3L, 3L, 2L, 1L, 
4L, 5L, 5L, 2L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 3L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), future_persp = structure(c(3L, 
3L, 5L, 5L, 5L, 5L, 6L, 5L, 5L, 3L, 5L, 6L, 6L, 5L, 3L, 6L, 
5L, 5L, 3L, 3L, 3L, 2L, 1L, 6L, 3L, 6L, 5L, 3L, 3L, 3L, 1L, 
3L, 2L, 2L, 2L, 2L, 3L, 3L, 4L, 2L, 4L, 2L, 2L, 3L, 1L, 2L, 
4L, 4L, 4L, 2L, 4L, 2L, 3L, 5L, 5L, 3L, 2L, 3L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), workers_comm = structure(c(6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 6L, 6L, 2L, 6L, 6L, 
6L, 6L, 6L, 4L, 5L, NA, 1L, 6L, 1L, 6L, 5L, 6L, 6L, 6L, 1L, 
2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 3L, 
3L, 3L, 3L, 1L, 4L, 3L, 4L, 5L, 3L, 3L, 4L, 4L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), work_project = structure(c(6L, 
6L, 6L, 6L, 5L, 5L, 6L, 5L, 6L, 6L, 6L, 6L, 5L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 5L, 3L, 6L, 4L, 6L, 5L, 6L, 6L, 6L, 6L, 
3L, 2L, 2L, 1L, 1L, 3L, 6L, 3L, 3L, 2L, 6L, 3L, 3L, 3L, 1L, 
3L, 6L, 5L, 6L, 5L, 1L, 6L, 6L, 5L, 6L, 2L, 3L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), agree_comm = structure(c(6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 6L, 6L, 6L, 5L, 6L, 
6L, 6L, 6L, 5L, 5L, 5L, 3L, 6L, 2L, 5L, 6L, 6L, 6L, 6L, 3L, 
3L, 2L, 3L, 3L, 1L, 3L, 3L, 3L, 2L, 4L, 1L, 3L, NA, 3L, 2L, 
3L, 3L, NA, 3L, 3L, 4L, 3L, 3L, 3L, 4L, 2L, 3L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), informed_deals = structure(c(4L, 
4L, 1L, 1L, 5L, 6L, 5L, 5L, 5L, 6L, 4L, 5L, 5L, 6L, 4L, 6L, 
5L, 6L, 4L, 6L, 6L, 6L, 1L, 6L, 3L, 6L, 1L, 2L, 2L, 2L, 4L, 
2L, 3L, 3L, 2L, 1L, 5L, 6L, 5L, 2L, 3L, 5L, 3L, 3L, 4L, 4L, 
2L, 4L, 4L, 5L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), fear_environ = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 5L, 1L, 
1L, 1L, 1L, 6L, 6L, 1L, 2L, 1L, 4L, 1L, NA, 1L, 1L, 1L, 4L, 
4L, 3L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 2L, 2L, 2L, 1L, 
NA, 1L, 1L, 2L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 2L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), water_quant = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 6L, 1L, 2L, 1L, 
1L, 1L, 6L, 6L, 6L, 5L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
3L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 3L, NA, 2L, 1L, 
5L, 1L, 1L, 2L, 4L, 1L, 3L, 1L, 2L, 3L, 3L, 2L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), support_govern = structure(c(6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 5L, 6L, 6L, 4L, 5L, 6L, 1L, 5L, 6L, 3L, 3L, 3L, 3L, 
3L, 2L, 3L, 3L, 2L, 5L, 5L, 3L, 2L, 4L, 3L, 3L, NA, 1L, 1L, 
2L, 6L, 3L, 3L, 3L, 4L, 4L, 6L, 4L, 4L, 3L, 3L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), proud_comm = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 6L, 1L, 1L, 1L, 
3L, 1L, 2L, 1L, 1L, 2L, 5L, 2L, 1L, 2L, 2L, 2L, NA, 1L, 1L, 
2L, 2L, 2L, 2L, 2L, 3L, 1L, 2L, 1L, 3L, 2L, 2L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), econ_comm = structure(c(6L, 
6L, 6L, 6L, 5L, 6L, 5L, 5L, 6L, 6L, 3L, 6L, 6L, 5L, 3L, 5L, 
3L, 4L, 5L, 2L, 2L, 5L, 5L, 6L, 2L, 6L, 5L, 5L, 5L, 5L, 3L, 
2L, 3L, 3L, 1L, 1L, 3L, 2L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 1L, 
3L, 2L, 3L, 1L, 5L, 3L, 2L, 5L, 2L, 6L, 3L, 4L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), jobs_comm = structure(c(6L, 
6L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 6L, 6L, 4L, 6L, 4L, 
6L, 4L, 5L, 5L, 5L, 3L, 2L, 6L, 1L, 6L, 5L, 5L, 5L, 5L, 2L, 
2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 
2L, 2L, 2L, 1L, 5L, 2L, 3L, 4L, 2L, 2L, 3L, 2L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), inequality_comm = structure(c(1L, 
1L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 1L, 3L, 6L, 1L, 2L, 6L, 2L, 
6L, 2L, 6L, NA, NA, 5L, 1L, 6L, 3L, 6L, 5L, 5L, 5L, 5L, 1L, 
3L, 3L, 2L, 3L, 4L, 2L, 3L, 4L, 3L, 2L, 4L, 3L, 3L, 5L, 3L, 
4L, 5L, 3L, 1L, 4L, 3L, 4L, 2L, 3L, NA, 3L, 3L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), exp_growth = structure(c(6L, 
6L, 4L, 4L, 6L, 6L, 6L, 5L, 6L, 6L, 4L, 4L, 6L, 2L, 2L, 2L, 
5L, 2L, 3L, NA, NA, 3L, 3L, 6L, 1L, 6L, 5L, 3L, 2L, 6L, 4L, 
2L, 2L, 3L, 2L, 3L, 5L, 2L, 3L, 2L, 3L, 4L, 2L, 3L, 2L, 1L, 
2L, 5L, 3L, 4L, 2L, 4L, 2L, 6L, 3L, 3L, 3L, 3L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), future_region = structure(c(6L, 
6L, 6L, 6L, 6L, 6L, 6L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
5L, 6L, 5L, 2L, 2L, 2L, 2L, 6L, 3L, 6L, 5L, 6L, 6L, 3L, 4L, 
2L, 3L, 3L, 2L, 4L, 5L, 5L, 5L, 2L, 4L, 2L, 4L, 3L, 4L, 1L, 
NA, 6L, 3L, 3L, 3L, 4L, 3L, 4L, 5L, 5L, 2L, 2L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), contamination_environ = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 6L, 1L, 6L, 1L, 
6L, 1L, 1L, 6L, 6L, 6L, 4L, 1L, 4L, 6L, 1L, 1L, 1L, 1L, 4L, 
1L, 2L, 1L, 3L, 3L, 1L, 2L, 1L, 3L, 3L, 5L, 2L, 2L, 1L, 1L, 
NA, 1L, 1L, 1L, 1L, 5L, 2L, 1L, 3L, 2L, 3L, 2L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), conflicts_comm = structure(c(6L, 
6L, 1L, 1L, 6L, 6L, 6L, 6L, 6L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 
2L, 1L, 6L, 5L, 5L, 5L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 4L, 
3L, 3L, 3L, 3L, 1L, 3L, 2L, 4L, 3L, 3L, 4L, 3L, NA, 4L, 2L, 
3L, 2L, 3L, 3L, 5L, 4L, 4L, 1L, 3L, 5L, 3L, 4L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), infrastructure_comm = structure(c(6L, 
6L, 6L, 6L, 6L, 6L, 6L, 5L, 6L, 6L, 4L, 6L, 5L, 6L, 5L, 6L, 
5L, 6L, 3L, 3L, 3L, NA, 1L, 6L, 1L, 6L, 6L, 4L, 4L, 3L, 1L, 
4L, 3L, NA, 3L, 1L, 5L, 6L, 2L, 3L, 3L, 4L, 3L, 2L, 1L, 2L, 
2L, 4L, 2L, 3L, 6L, 4L, 3L, 3L, 3L, 3L, 2L, 2L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), included_mining = structure(c(1L, 
1L, 1L, 1L, 5L, 6L, 6L, 6L, 6L, 6L, 3L, 6L, 6L, 6L, 5L, 6L, 
6L, 6L, 3L, 5L, 5L, 6L, 3L, NA, 3L, NA, NA, 6L, 5L, 5L, 1L, 
3L, 3L, 3L, 3L, 5L, 4L, 6L, 3L, 3L, 2L, 6L, 2L, NA, 2L, 3L, 
2L, 5L, 5L, 3L, 5L, 3L, 3L, 2L, 4L, 5L, 3L, NA), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), investment_region = structure(c(1L, 
1L, 3L, 3L, 6L, 6L, 6L, 5L, 6L, 1L, 2L, 1L, 6L, 2L, 4L, 1L, 
2L, 2L, 3L, NA, NA, 4L, 1L, 5L, 3L, 5L, 5L, 1L, 2L, 2L, 4L, 
2L, 2L, 2L, 4L, 1L, 2L, 3L, 3L, 2L, 3L, 1L, 3L, NA, 3L, 2L, 
NA, 2L, 3L, 3L, 4L, 4L, 3L, 3L, 2L, 2L, 2L, 4L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor"), water_qual = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 6L, 5L, 5L, 5L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
4L, 3L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 3L, NA, 3L, 1L, 
4L, 1L, 1L, 3L, 4L, 2L, 2L, 1L, 2L, 3L, 3L, 2L), .Label = c("Completely agree", 
"Agree", "Slightly agree", "Slightly disagree", "Disagree", 
"Completely disagree"), class = "factor")), row.names = c(NA,

-58L), класс = "data.frame")

1 Ответ

0 голосов
/ 10 февраля 2020

Я думаю, вы только что совершили простую ошибку при печати. И вам не нужно создавать вектор both, так как вы можете передать переменную группировки в вызове функции. Попробуйте: 

both_likert_2 = likert(g[, c(1:3), drop=FALSE], grouping = g$Location)

Редактировать : на основе предоставленной новой информации, как об этом: 

g <-  within(g, {
  future_persp <- factor(future_persp, levels=1:6)
  econ_comm <- factor(econ_comm, levels=1:6)
} )

comm_likert = likert(g[,2:3], grouping=g[,1])
plot(comm_likert)

Редактировать : ОП хотел измените метки тика оси Y на что-то более подходящее. Измените имена столбцов, но используйте dplyr, чтобы вам не приходилось вносить постоянные изменения: 

library(dplyr)
g %>%
   dplyr::select(future_persp, econ_comm) %>%
   rename(`It offers important economic perspectives`=future_persp,
          `It provides economic prosperity to the community`=econ_comm) %>%
   likert(grouping=g[, "Location"]) %>%
   plot()
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