我对R完全陌生 - 老实说,真的不知道我在做什么。但我真的需要按照某人的建议用这些数据运行双变量/多变量回归,我被困住了。任何帮助将不胜感激。
rm(list=ls())
setwd("C:/Users/Bogi/Documents/School/Honors Thesis/Voting and Economic Data")
data<-read.csv("BOGDAN_DATA1.csv")
head(data)
round(cor(data[,-1],use="complete.obs"),1)
Error in cor(data[, -1], use = "complete.obs") : 'x' must be numeric
德普特
structure(list(REGION = structure(1:6, .Label = c("Altai Republic",
"Altai Territory", "Amur Region", "Arkhangelsk Region", "Astrakhan region",
"Belgorod region"), class = "factor"), PCT_CHANGE_VOTE = structure(c(2L,
3L, 5L, 4L, 6L, 1L), .Label = c("-13%", "-16%", "-17%", "-25%",
"-26%", "2%"), class = "factor"), PCT_CHANGE_GRP = structure(c(2L,
1L, 4L, 3L, 3L, 4L), .Label = c("10%", "17%", "19%", "27%"), class = "factor"),
PCT_CHANGE_INFLATION = structure(c(1L, 2L, 1L, 3L, 3L, 2L
), .Label = c("-2%", "-3%", "-4%"), class = "factor"), PCT_CHANGE_UNEMP = structure(c(5L,
4L, 1L, 2L, 6L, 3L), .Label = c("-13%", "-14%", "-17%", "-3%",
"5%", "7%"), class = "factor"), POVERTY = c(18.6, 22.6, 20.4,
14.4, 14.2, 8.6), POP_AGE1 = c(25.8, 16.9, 18.5, 17.1, 17.8,
15.2), POP_AGE2 = c(58.8, 59.6, 61.3, 60.4, 60.8, 60.3),
POP_AGE3 = c(15.4, 23.5, 20.2, 22.5, 21.4, 24.5), POP_URBAN = c(28.7,
55.2, 67, 76.2, 66.7, 66.4), POP_RURAL = c(71.3, 44.8, 33,
23.8, 33.3, 33.6), COMPUTER = c(46.4, 54.5, 66.1, 74, 65.1,
55.2), INTERNET = c(32.1, 41, 50.7, 66.5, 60, 50.7)), .Names = c("REGION",
"PCT_CHANGE_VOTE", "PCT_CHANGE_GRP", "PCT_CHANGE_INFLATION",
"PCT_CHANGE_UNEMP", "POVERTY", "POP_AGE1", "POP_AGE2", "POP_AGE3",
"POP_URBAN", "POP_RURAL", "COMPUTER", "INTERNET"), row.names = c(NA,
6L), class = "data.frame")
您可以循环列 2:5 ( lapply(data[2:5], ..)
),删除列 2:5 ( gsub('[%]',..)
) 中的%
并将列转换为 numeric
列。gsub
的输出将character
类,通过as.numeric
将其转换为numeric
data[2:5] <- lapply(data[2:5], function(x)
as.numeric(gsub('[%]', '', x)))
Cor1 <- round(cor(data[-1],use="complete.obs"),1)
或者您可以使用 shell 上的awk
删除这些列中的%
(假设,
作为分隔符)
awk 'BEGIN {OFS=FS=","} function SUB(F) {sub(/%/,"", $F)}{SUB(2);SUB(3);SUB(4);SUB(5)}1' Bogdan.csv > Bogdan2.csv
使用 read.csv
读取文件并运行cor
dat1 <- read.csv('Bogdan2.csv')
Cor2 <- round(cor(dat1[-1], use='complete.obs'), 1)
identical(Cor1, Cor2)
#[1] TRUE