corr.test 参数暗示不同的行数答案

【问题标题】：corr.test arguments imply differing number of rowscorr.test 参数暗示不同的行数
【发布时间】：2015-12-08 13:36:35
【问题描述】：

我在不同的项目中多次看到这个错误，我想知道是否有办法判断是哪一行导致错误一般？

我的具体情况：

 http://archive.ics.uci.edu/ml/machine-learning-databases/00275/

#using the bike.csv
data<-read.csv("PATH_HERE\\Bike-Sharing-Dataset\\day.csv",header=TRUE)
require(psych)
corr.test(data) 
data<-data[,c("atemp","casual","cnt","holiday","hum","mnth","registered",
              "season","temp","weathersit","weekday","windspeed","workingday","yr")]
data[data=='']<-NA
#View(data)

require(psych)
cors<-corr.test(data)

返回错误：

Error in data.frame(lower = lower, r = r[lower.tri(r)], upper = upper,  : 
  arguments imply differing number of rows: 0, 91

【问题讨论】：

标签： r

【解决方案1】：

对我有用

> #using the bike.csv
> data <- read.csv("day.csv",header=TRUE)
> require(psych)
> corr.test(data) 
Error in cor(x, use = use, method = method) : 'x' must be numeric
> data <- data[,c("atemp","casual","cnt","holiday","hum","mnth","registered",
+               "season","temp","weathersit","weekday","windspeed","workingday","yr")]
> data[data==''] <- NA
> #View(data)
> 
> require(psych)
> cors <- corr.test(data)
> cors
Call:corr.test(x = data)
Correlation matrix 
           atemp casual   cnt holiday   hum  mnth registered season  temp
atemp       1.00   0.54  0.63   -0.03  0.14  0.23       0.54   0.34  0.99
casual      0.54   1.00  0.67    0.05 -0.08  0.12       0.40   0.21  0.54
cnt         0.63   0.67  1.00   -0.07 -0.10  0.28       0.95   0.41  0.63
holiday    -0.03   0.05 -0.07    1.00 -0.02  0.02      -0.11  -0.01 -0.03
hum         0.14  -0.08 -0.10   -0.02  1.00  0.22      -0.09   0.21  0.13
mnth        0.23   0.12  0.28    0.02  0.22  1.00       0.29   0.83  0.22
registered  0.54   0.40  0.95   -0.11 -0.09  0.29       1.00   0.41  0.54
season      0.34   0.21  0.41   -0.01  0.21  0.83       0.41   1.00  0.33
temp        0.99   0.54  0.63   -0.03  0.13  0.22       0.54   0.33  1.00
weathersit -0.12  -0.25 -0.30   -0.03  0.59  0.04      -0.26   0.02 -0.12
weekday    -0.01   0.06  0.07   -0.10 -0.05  0.01       0.06   0.00  0.00
windspeed  -0.18  -0.17 -0.23    0.01 -0.25 -0.21      -0.22  -0.23 -0.16
workingday  0.05  -0.52  0.06   -0.25  0.02 -0.01       0.30   0.01  0.05
yr          0.05   0.25  0.57    0.01 -0.11  0.00       0.59   0.00  0.05
           weathersit weekday windspeed workingday    yr
atemp           -0.12   -0.01     -0.18       0.05  0.05
casual          -0.25    0.06     -0.17      -0.52  0.25
cnt             -0.30    0.07     -0.23       0.06  0.57
holiday         -0.03   -0.10      0.01      -0.25  0.01
hum              0.59   -0.05     -0.25       0.02 -0.11
mnth             0.04    0.01     -0.21      -0.01  0.00
registered      -0.26    0.06     -0.22       0.30  0.59
season           0.02    0.00     -0.23       0.01  0.00
temp            -0.12    0.00     -0.16       0.05  0.05
weathersit       1.00    0.03      0.04       0.06 -0.05
weekday          0.03    1.00      0.01       0.04 -0.01
windspeed        0.04    0.01      1.00      -0.02 -0.01
workingday       0.06    0.04     -0.02       1.00  0.00
yr              -0.05   -0.01     -0.01       0.00  1.00
Sample Size 
[1] 731
Probability values (Entries above the diagonal are adjusted for multiple tests.) 
           atemp casual  cnt holiday  hum mnth registered season temp
atemp       0.00   0.00 0.00    1.00 0.01 0.00       0.00   0.00 0.00
casual      0.00   0.00 0.00    1.00 1.00 0.04       0.00   0.00 0.00
cnt         0.00   0.00 0.00    1.00 0.28 0.00       0.00   0.00 0.00
holiday     0.38   0.14 0.06    0.00 1.00 1.00       0.15   1.00 1.00
hum         0.00   0.04 0.01    0.67 0.00 0.00       0.58   0.00 0.03
mnth        0.00   0.00 0.00    0.60 0.00 0.00       0.00   0.00 0.00
registered  0.00   0.00 0.00    0.00 0.01 0.00       0.00   0.00 0.00
season      0.00   0.00 0.00    0.78 0.00 0.00       0.00   0.00 0.00
temp        0.00   0.00 0.00    0.44 0.00 0.00       0.00   0.00 0.00
weathersit  0.00   0.00 0.00    0.35 0.00 0.24       0.00   0.60 0.00
weekday     0.84   0.11 0.07    0.01 0.16 0.80       0.12   0.93 1.00
windspeed   0.00   0.00 0.00    0.87 0.00 0.00       0.00   0.00 0.00
workingday  0.16   0.00 0.10    0.00 0.51 0.87       0.00   0.74 0.15
yr          0.21   0.00 0.00    0.83 0.00 0.96       0.00   0.96 0.20
           weathersit weekday windspeed workingday   yr
atemp            0.05    1.00      0.00       1.00 1.00
casual           0.00    1.00      0.00       0.00 0.00
cnt              0.00    1.00      0.00       1.00 0.00
holiday          1.00    0.25      1.00       0.00 1.00
hum              0.00    1.00      0.00       1.00 0.13
mnth             1.00    1.00      0.00       1.00 1.00
registered       0.00    1.00      0.00       0.00 0.00
season           1.00    1.00      0.00       1.00 1.00
temp             0.05    1.00      0.00       1.00 1.00
weathersit       0.00    1.00      1.00       1.00 1.00
weekday          0.40    0.00      1.00       1.00 1.00
windspeed        0.29    0.70      0.00       1.00 1.00
workingday       0.10    0.33      0.61       0.00 1.00
yr               0.19    0.88      0.75       0.96 0.00

 To see confidence intervals of the correlations, print with the short=FALSE option
>

【讨论】：

【解决方案2】：

它对我有用:::

rm(list=ls())
# http://archive.ics.uci.edu/ml/machine-learning-databases/00275/

#using the bike.csv

day <- read.csv("Bike-Sharing-Dataset//day.csv")

require(psych)

day<-day[,c("atemp","casual","cnt","holiday","hum","mnth","registered",
              "season","temp","weathersit","weekday","windspeed","workingday","yr")]

day[day=='']<-NA

require(psych)
corr.test(day) 


# corr.test(day)
# Call:corr.test(x = day)
# Correlation matrix 
# atemp casual   cnt holiday   hum  mnth registered season  temp weathersit weekday windspeed workingday    yr
# atemp       1.00   0.54  0.63   -0.03  0.14  0.23       0.54   0.34  0.99      -0.12   -0.01     -0.18       0.05  0.05
# casual      0.54   1.00  0.67    0.05 -0.08  0.12       0.40   0.21  0.54      -0.25    0.06     -0.17      -0.52  0.25
# cnt         0.63   0.67  1.00   -0.07 -0.10  0.28       0.95   0.41  0.63      -0.30    0.07     -0.23       0.06  0.57
# holiday    -0.03   0.05 -0.07    1.00 -0.02  0.02      -0.11  -0.01 -0.03      -0.03   -0.10      0.01      -0.25  0.01
# hum         0.14  -0.08 -0.10   -0.02  1.00  0.22      -0.09   0.21  0.13       0.59   -0.05     -0.25       0.02 -0.11
# mnth        0.23   0.12  0.28    0.02  0.22  1.00       0.29   0.83  0.22       0.04    0.01     -0.21      -0.01  0.00
# registered  0.54   0.40  0.95   -0.11 -0.09  0.29       1.00   0.41  0.54      -0.26    0.06     -0.22       0.30  0.59
# season      0.34   0.21  0.41   -0.01  0.21  0.83       0.41   1.00  0.33       0.02    0.00     -0.23       0.01  0.00
# temp        0.99   0.54  0.63   -0.03  0.13  0.22       0.54   0.33  1.00      -0.12    0.00     -0.16       0.05  0.05
# weathersit -0.12  -0.25 -0.30   -0.03  0.59  0.04      -0.26   0.02 -0.12       1.00    0.03      0.04       0.06 -0.05
# weekday    -0.01   0.06  0.07   -0.10 -0.05  0.01       0.06   0.00  0.00       0.03    1.00      0.01       0.04 -0.01
# windspeed  -0.18  -0.17 -0.23    0.01 -0.25 -0.21      -0.22  -0.23 -0.16       0.04    0.01      1.00      -0.02 -0.01
# workingday  0.05  -0.52  0.06   -0.25  0.02 -0.01       0.30   0.01  0.05       0.06    0.04     -0.02       1.00  0.00
# yr          0.05   0.25  0.57    0.01 -0.11  0.00       0.59   0.00  0.05      -0.05   -0.01     -0.01       0.00  1.00
# Sample Size 
# [1] 731
# Probability values (Entries above the diagonal are adjusted for multiple tests.) 
# atemp casual  cnt holiday  hum mnth registered season temp weathersit weekday windspeed workingday   yr
# atemp       0.00   0.00 0.00    1.00 0.01 0.00       0.00   0.00 0.00       0.05    1.00      0.00       1.00 1.00
# casual      0.00   0.00 0.00    1.00 1.00 0.04       0.00   0.00 0.00       0.00    1.00      0.00       0.00 0.00
# cnt         0.00   0.00 0.00    1.00 0.28 0.00       0.00   0.00 0.00       0.00    1.00      0.00       1.00 0.00
# holiday     0.38   0.14 0.06    0.00 1.00 1.00       0.15   1.00 1.00       1.00    0.25      1.00       0.00 1.00
# hum         0.00   0.04 0.01    0.67 0.00 0.00       0.58   0.00 0.03       0.00    1.00      0.00       1.00 0.13
# mnth        0.00   0.00 0.00    0.60 0.00 0.00       0.00   0.00 0.00       1.00    1.00      0.00       1.00 1.00
# registered  0.00   0.00 0.00    0.00 0.01 0.00       0.00   0.00 0.00       0.00    1.00      0.00       0.00 0.00
# season      0.00   0.00 0.00    0.78 0.00 0.00       0.00   0.00 0.00       1.00    1.00      0.00       1.00 1.00
# temp        0.00   0.00 0.00    0.44 0.00 0.00       0.00   0.00 0.00       0.05    1.00      0.00       1.00 1.00
# weathersit  0.00   0.00 0.00    0.35 0.00 0.24       0.00   0.60 0.00       0.00    1.00      1.00       1.00 1.00
# weekday     0.84   0.11 0.07    0.01 0.16 0.80       0.12   0.93 1.00       0.40    0.00      1.00       1.00 1.00
# windspeed   0.00   0.00 0.00    0.87 0.00 0.00       0.00   0.00 0.00       0.29    0.70      0.00       1.00 1.00
# workingday  0.16   0.00 0.10    0.00 0.51 0.87       0.00   0.74 0.15       0.10    0.33      0.61       0.00 1.00
# yr          0.21   0.00 0.00    0.83 0.00 0.96       0.00   0.96 0.20       0.19    0.88      0.75       0.96 0.00
# 
# To see confidence intervals of the correlations, print with the short=FALSE option

干杯

【讨论】：