Question 1

MyData <- read.csv(file="c:/Users/Dell/Desktop/Acme.csv", header=TRUE, sep=",")

MyData
##     X  month    market      acme
## 1   1 Jan-86 -0.061134  0.030160
## 2   2 Feb-86  0.008220 -0.165457
## 3   3 Mar-86 -0.007381  0.080137
## 4   4 Apr-86 -0.067561 -0.109917
## 5   5 May-86 -0.006238 -0.114853
## 6   6 Jun-86 -0.044251 -0.099254
## 7   7 Jul-86 -0.112070 -0.226846
## 8   8 Aug-86  0.030226  0.073445
## 9   9 Sep-86 -0.129556 -0.143064
## 10 10 Oct-86  0.001319  0.034776
## 11 11 Nov-86 -0.033679 -0.063375
## 12 12 Dec-86 -0.072795 -0.058735
## 13 13 Jan-87  0.073396  0.050214
## 14 14 Feb-87 -0.011618  0.111165
## 15 15 Mar-87 -0.026852 -0.127492
## 16 16 Apr-87 -0.040356  0.054522
## 17 17 May-87 -0.047539 -0.072918
## 18 18 Jun-87 -0.001732 -0.058979
## 19 19 Jul-87 -0.008899  0.236147
## 20 20 Aug-87 -0.020837 -0.094778
## 21 21 Sep-87 -0.084811 -0.135669
## 22 22 Oct-87 -0.262077 -0.284796
## 23 23 Nov-87 -0.110167 -0.171494
## 24 24 Dec-87  0.034955  0.242616
## 25 25 Jan-88  0.012688 -0.063518
## 26 26 Feb-88 -0.002170 -0.117677
## 27 27 Mar-88 -0.073462  0.201674
## 28 28 Apr-88 -0.043419 -0.147728
## 29 29 May-88 -0.054730 -0.170885
## 30 30 Jun-88 -0.011755 -0.014893
## 31 31 Jul-88 -0.061718 -0.110515
## 32 32 Aug-88 -0.101710 -0.168769
## 33 33 Sep-88 -0.032705 -0.135585
## 34 34 Oct-88 -0.045334 -0.084077
## 35 35 Nov-88 -0.079288 -0.164550
## 36 36 Dec-88 -0.036233  0.150269
## 37 37 Jan-89 -0.011494 -0.015672
## 38 38 Feb-89 -0.093729 -0.037860
## 39 39 Mar-89 -0.065215 -0.074712
## 40 40 Apr-89 -0.037113 -0.108530
## 41 41 May-89 -0.044399 -0.036769
## 42 42 Jun-89 -0.084412  0.023912
## 43 43 Jul-89  0.003444 -0.078430
## 44 44 Aug-89 -0.056760 -0.132199
## 45 45 Sep-89 -0.078970 -0.110141
## 46 46 Oct-89 -0.105367 -0.126302
## 47 47 Nov-89 -0.038634 -0.095730
## 48 48 Dec-89 -0.043261  0.065740
## 49 49 Jan-90 -0.139773 -0.120056
## 50 50 Feb-90 -0.059094 -0.085205
## 51 51 Mar-90 -0.057736 -0.130433
## 52 52 Apr-90 -0.102524 -0.116728
## 53 53 May-90  0.023881 -0.078039
## 54 54 Jun-90 -0.079116 -0.170322
## 55 55 Jul-90 -0.078965 -0.077727
## 56 56 Aug-90 -0.161359 -0.277035
## 57 57 Sep-90 -0.119376 -0.207595
## 58 58 Oct-90 -0.076008 -0.070515
## 59 59 Nov-90 -0.006444 -0.046274
## 60 60 Dec-90 -0.026401 -0.190834
summary(MyData)
##        X             month        market              acme         
##  Min.   : 1.00   Apr-86 : 1   Min.   :-0.26208   Min.   :-0.28480  
##  1st Qu.:15.75   Apr-87 : 1   1st Qu.:-0.07901   1st Qu.:-0.13305  
##  Median :30.50   Apr-88 : 1   Median :-0.04487   Median :-0.08999  
##  Mean   :30.50   Apr-89 : 1   Mean   :-0.05117   Mean   :-0.06897  
##  3rd Qu.:45.25   Apr-90 : 1   3rd Qu.:-0.01159   3rd Qu.:-0.03149  
##  Max.   :60.00   Aug-86 : 1   Max.   : 0.07340   Max.   : 0.24262  
##                  (Other):54
mean(MyData$X)
## [1] 30.5
mean(MyData$market)
## [1] -0.0511683
median(MyData$X)
## [1] 30.5
median(MyData$market)
## [1] -0.0448665

Question 2

a<-MyData[c(1:10),c(1:3)]

a
##     X  month    market
## 1   1 Jan-86 -0.061134
## 2   2 Feb-86  0.008220
## 3   3 Mar-86 -0.007381
## 4   4 Apr-86 -0.067561
## 5   5 May-86 -0.006238
## 6   6 Jun-86 -0.044251
## 7   7 Jul-86 -0.112070
## 8   8 Aug-86  0.030226
## 9   9 Sep-86 -0.129556
## 10 10 Oct-86  0.001319
b<-subset(MyData,X<11)

b
##     X  month    market      acme
## 1   1 Jan-86 -0.061134  0.030160
## 2   2 Feb-86  0.008220 -0.165457
## 3   3 Mar-86 -0.007381  0.080137
## 4   4 Apr-86 -0.067561 -0.109917
## 5   5 May-86 -0.006238 -0.114853
## 6   6 Jun-86 -0.044251 -0.099254
## 7   7 Jul-86 -0.112070 -0.226846
## 8   8 Aug-86  0.030226  0.073445
## 9   9 Sep-86 -0.129556 -0.143064
## 10 10 Oct-86  0.001319  0.034776

Question 3

names(a)<-c("X1","month1","market1")

a
##    X1 month1   market1
## 1   1 Jan-86 -0.061134
## 2   2 Feb-86  0.008220
## 3   3 Mar-86 -0.007381
## 4   4 Apr-86 -0.067561
## 5   5 May-86 -0.006238
## 6   6 Jun-86 -0.044251
## 7   7 Jul-86 -0.112070
## 8   8 Aug-86  0.030226
## 9   9 Sep-86 -0.129556
## 10 10 Oct-86  0.001319

Question 4

summary(a)
##        X1            month1     market1          
##  Min.   : 1.00   Apr-86 :1   Min.   :-0.1295560  
##  1st Qu.: 3.25   Aug-86 :1   1st Qu.:-0.0659543  
##  Median : 5.50   Feb-86 :1   Median :-0.0258160  
##  Mean   : 5.50   Jan-86 :1   Mean   :-0.0388426  
##  3rd Qu.: 7.75   Jul-86 :1   3rd Qu.:-0.0005703  
##  Max.   :10.00   Jun-86 :1   Max.   : 0.0302260  
##                  (Other):4
mean(a$X1)
## [1] 5.5
mean(a$market1)
## [1] -0.0388426
median(a$X1)
## [1] 5.5
median(a$market1)
## [1] -0.025816

means and medians have changed

Question 5

a$X1[a$X1==1]<-1000

a$X1[a$X1==2]<-2000

a$X1[a$X1==3]<-3000

a
##      X1 month1   market1
## 1  1000 Jan-86 -0.061134
## 2  2000 Feb-86  0.008220
## 3  3000 Mar-86 -0.007381
## 4     4 Apr-86 -0.067561
## 5     5 May-86 -0.006238
## 6     6 Jun-86 -0.044251
## 7     7 Jul-86 -0.112070
## 8     8 Aug-86  0.030226
## 9     9 Sep-86 -0.129556
## 10   10 Oct-86  0.001319

Question 6

All my dataframes are small and none of them gets truncated when shown in Rmarkdown

Question 7

library(RCurl)
## Loading required package: bitops
x <- getURL("https://raw.githubusercontent.com/mgroysman/CSV-File/master/acme.csv")

y <- read.csv(text = x)

y
##     X  month    market      acme
## 1   1 Jan-86 -0.061134  0.030160
## 2   2 Feb-86  0.008220 -0.165457
## 3   3 Mar-86 -0.007381  0.080137
## 4   4 Apr-86 -0.067561 -0.109917
## 5   5 May-86 -0.006238 -0.114853
## 6   6 Jun-86 -0.044251 -0.099254
## 7   7 Jul-86 -0.112070 -0.226846
## 8   8 Aug-86  0.030226  0.073445
## 9   9 Sep-86 -0.129556 -0.143064
## 10 10 Oct-86  0.001319  0.034776
## 11 11 Nov-86 -0.033679 -0.063375
## 12 12 Dec-86 -0.072795 -0.058735
## 13 13 Jan-87  0.073396  0.050214
## 14 14 Feb-87 -0.011618  0.111165
## 15 15 Mar-87 -0.026852 -0.127492
## 16 16 Apr-87 -0.040356  0.054522
## 17 17 May-87 -0.047539 -0.072918
## 18 18 Jun-87 -0.001732 -0.058979
## 19 19 Jul-87 -0.008899  0.236147
## 20 20 Aug-87 -0.020837 -0.094778
## 21 21 Sep-87 -0.084811 -0.135669
## 22 22 Oct-87 -0.262077 -0.284796
## 23 23 Nov-87 -0.110167 -0.171494
## 24 24 Dec-87  0.034955  0.242616
## 25 25 Jan-88  0.012688 -0.063518
## 26 26 Feb-88 -0.002170 -0.117677
## 27 27 Mar-88 -0.073462  0.201674
## 28 28 Apr-88 -0.043419 -0.147728
## 29 29 May-88 -0.054730 -0.170885
## 30 30 Jun-88 -0.011755 -0.014893
## 31 31 Jul-88 -0.061718 -0.110515
## 32 32 Aug-88 -0.101710 -0.168769
## 33 33 Sep-88 -0.032705 -0.135585
## 34 34 Oct-88 -0.045334 -0.084077
## 35 35 Nov-88 -0.079288 -0.164550
## 36 36 Dec-88 -0.036233  0.150269
## 37 37 Jan-89 -0.011494 -0.015672
## 38 38 Feb-89 -0.093729 -0.037860
## 39 39 Mar-89 -0.065215 -0.074712
## 40 40 Apr-89 -0.037113 -0.108530
## 41 41 May-89 -0.044399 -0.036769
## 42 42 Jun-89 -0.084412  0.023912
## 43 43 Jul-89  0.003444 -0.078430
## 44 44 Aug-89 -0.056760 -0.132199
## 45 45 Sep-89 -0.078970 -0.110141
## 46 46 Oct-89 -0.105367 -0.126302
## 47 47 Nov-89 -0.038634 -0.095730
## 48 48 Dec-89 -0.043261  0.065740
## 49 49 Jan-90 -0.139773 -0.120056
## 50 50 Feb-90 -0.059094 -0.085205
## 51 51 Mar-90 -0.057736 -0.130433
## 52 52 Apr-90 -0.102524 -0.116728
## 53 53 May-90  0.023881 -0.078039
## 54 54 Jun-90 -0.079116 -0.170322
## 55 55 Jul-90 -0.078965 -0.077727
## 56 56 Aug-90 -0.161359 -0.277035
## 57 57 Sep-90 -0.119376 -0.207595
## 58 58 Oct-90 -0.076008 -0.070515
## 59 59 Nov-90 -0.006444 -0.046274
## 60 60 Dec-90 -0.026401 -0.190834