Rマークダウンを作成中にエラーが発生するPDFレポート

Question

RマークダウンファイルからPDFレポートを作成中にエラーが発生しました。以下は、エラーの抜粋です：

Error in --dayBikeData <- read.csv("D:\\Madhav\\Study\\MSIS\\PredictiveLearning\\Week-1\\Homework\\Bike-Sharing-Dataset\\day.csv") : 
    object 'dayBikeData' not found 
Calls: <Anonymous> ... handle -> withCallingHandlers -> withVisible -> eval -> eval 
Execution halted 

私はセッションでこのオブジェクトに-dayBikeDataを持っていますが、まだそれがエラーを与えているこの上で続行する方法がわかりません。 csvファイルからデータをフェッチする

コード：

```{r} 

dayBikeData <- read.csv("D:\\Madhav\\Study\\MSIS\\PredictiveLearning 
         \\Week-1\\Homework\\Bike-Sharing-Dataset\\day.csv") 

# Performs each of the operation asked in the question 
basicOperations <- function(inputData){ 
    lenData <- length(inputData) 
    avg <- round(mean(inputData, na.rm = TRUE), digits = 2) # mean calculation 
    standardDeviation <- round(sd(inputData), digits = 2) # Standard deviation 
    sem <- round(standardDeviation/sqrt(lenData), digits = 2) 
    # Formula for CI is mean - error where error is 
    error = round(qnorm(0.975)*standardDeviation/sqrt(lenData), digits = 2) 
    lower_ci <- avg - error 
    upper_ci <- avg + error 

    # resultList <- list(obs = lenData, mean = avg, standarDeviation = sd, 
    #     standardMeanError= sem, lowerCI = lower_ci, upperCI = upper_ci 

    resultList <- c(lenData, avg, standardDeviation, sem,lower_ci,upper_ci) 
    print(resultList) 
} 

#Calculations for the Year Wise Data 
# dData2011 <- dayBikeData[dayBikeData$yr==0,] 
# dData2012 <- dayBikeData[dayBikeData$yr==1,] 
dData2011ResultSet <- basicOperations(dayBikeData[dayBikeData$yr==0,]$cnt) 
dData2012ResultSet <- basicOperations(dayBikeData[dayBikeData$yr==1,]$cnt) 

#Calculations for the Holiday Wise Data 
# dDataHoliady_0 <- dayBikeData[dayBikeData$holiday ==0,] 
# dDataHoliady_1 <- dayBikeData[dayBikeData$holiday ==1,] 
dDataHoliady0ResultSet <- basicOperations(dayBikeData[dayBikeData$holiday ==0,]$cnt) 
dDataHoliady1ResultSet <- basicOperations(dayBikeData[dayBikeData$holiday ==1,]$cnt) 

#Calculations for the WorkingDay Wise Data 

# dDataWorkingDay_0 <- dayBikeData[dayBikeData$workingday ==0,] 
# dDataWorkingDay_1 <- dayBikeData[dayBikeData$workingday ==1,] 
dDataWorkingDay0ResultSet <- basicOperations(dayBikeData[dayBikeData$workingday ==0,]$cnt) 
dDataWorkingDay1ResultSet <- basicOperations(dayBikeData[dayBikeData$workingday ==1,]$cnt) 


#Calculations for the Temperature wise data 

avgTemp <- mean(dayBikeData$temp, na.rm = TRUE) 
dDataTempGreaterEq <- dayBikeData[dayBikeData$temp >= avgTemp,] 
dDataTempLess <- dayBikeData[dayBikeData$temp < avgTemp,] 
dDataTempGreaterEqResultSet <- basicOperations(dDataTempGreaterEq$cnt) 
dDataTempLessResultSet <- basicOperations(dDataTempLess$cnt) 

#Calculations for the Weather wise data 
# dDataWeather_1 <- dayBikeData[dayBikeData$weathersit ==1,] 
# dDataWeather_2 <- dayBikeData[dayBikeData$weathersit ==2,] 
# dDataWeather_3 <- dayBikeData[dayBikeData$weathersit ==3,] 
dDataWeather1ResultSet <- basicOperations(dayBikeData[dayBikeData$weathersit ==1,]$cnt) 
dDataWeather2ResultSet <- basicOperations(dayBikeData[dayBikeData$weathersit ==2,]$cnt) 
dDataWeather3ResultSet <- basicOperations(dayBikeData[dayBikeData$weathersit ==3,]$cnt) 

#Calculations for the Season wise data 
# dDataSeason_1 <- dayBikeData[dayBikeData$season ==1,] 
# dDataSeason_2 <- dayBikeData[dayBikeData$season ==2,] 
# dDataSeason_3 <- dayBikeData[dayBikeData$season ==3,] 
# dDataSeason_4 <- dayBikeData[dayBikeData$season ==4,] 
dDataSeason1ResultSet <- basicOperations(dayBikeData[dayBikeData$season ==1,]$cnt) 
dDataSeason2ResultSet <- basicOperations(dayBikeData[dayBikeData$season ==2,]$cnt) 
dDataSeason3ResultSet <- basicOperations(dayBikeData[dayBikeData$season ==3,]$cnt) 
dDataSeason4ResultSet <- basicOperations(dayBikeData[dayBikeData$season ==4,]$cnt) 



#Constrcut a row wise data 
resultData <- rbind(dData2011ResultSet, dData2012ResultSet, dDataHoliady0ResultSet, 
        dDataHoliady1ResultSet,dDataWorkingDay0ResultSet, 
        dDataWorkingDay1ResultSet,dDataTempGreaterEqResultSet, 
        dDataTempLessResultSet, dDataWeather1ResultSet, 
        dDataWeather2ResultSet, dDataWeather3ResultSet,dDataSeason1ResultSet, 
        dDataSeason2ResultSet, dDataSeason3ResultSet,dDataSeason4ResultSet) 
colnames(resultData) <- c("N","Mean","SD" , "SEM","Lower_CI", "UPPER_CI") 


rownames(resultData) <- c("Year-0", "Year-1", "Holiday-0", "Holiday-1", "WorkingDay-0", 
          "WorkingDay-1","Temperature >=","Temperature <", "Weather-1", 
          "Weather-2","Weather-3","Season-1","Season-2", "Season-3", 
          "Season-4") 

df.resultData <- as.data.frame(resultData) 
df.resultData["Value"] <- NA 
df.resultData$Value <- c(2011, 2012, 0,1, 0,1,1, 0, 1,2,3,1,2,3,4) 

df.resultData = df.resultData[,c(7,1,2,3,4,5,6)] 
library(knitr) 
# print(xtable(df.resultData), type = "latex") 
kable(df.resultData, format = "markdown") 
write.csv(df.resultData, file = "D:\\X\\Study\\MSIS\\PredictiveLearning\\OutputResult.csv") 

Answer 1

私は、それを実行した、パスを削除してファイル名を調整し、新しいフォルダにRMDを保存し、UCIマシンLearnignリポジトリからデータセットをダウンロードそれはうまくいった。

セッションが壊れているか、パスが間違っているなどです。私がやったことを試してみるとうまくいきます。

証明：

Answer 2

あなたのファイルパスが間違っている...それの途中で改行やスペースがたくさんあります。

> "D:\\Madhav\\Study\\MSIS\\PredictiveLearning 
+       \\Week-1\\Homework\\Bike-Sharing-Dataset\\day.csv" 
[1] "D:\\Madhav\\Study\\MSIS\\PredictiveLearning\n      \\Week-1\\Homework\\Bike-Sharing-Dataset\\day.csv" 

ファイルが正しく読み込まれないため、オブジェクトはknitrセッションで使用できません。