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Using data set mtcars, I'm not able to find f)Load mtcars data frame into R console and retrieve the following data from the data table

  • a) Get the headers, dimensions and structure of mtcars data frame

  • b) Get first 15 rows and 15 columns

  • c) Get first column of first 20 rows

  • d) Get second column of first 20 rows

  • e) Get only second column

  • f) Get only alternate rows and all its corresponding columns

Zahra Bayat
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userr45
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    Please read [How do I ask homework questions](https://meta.stackoverflow.com/questions/334822/how-do-i-ask-and-answer-homework-questions) – Ronak Shah Nov 20 '20 at 09:39
  • What you have tried so far? – Daman deep Nov 20 '20 at 09:39
  • head(mtcars) dim(mtcars) str(mtcars) mtcars[1:15,] mtcars[,1:11] as.data.frame(mtcars[1:20,1]) as.data.frame(mtcars[2:20,2]) as.data.frame(mtcars[,2]) – userr45 Nov 20 '20 at 09:59
  • @student45 Edit your question. [Learn](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) how to format your question properly – Daman deep Nov 20 '20 at 10:45

1 Answers1

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your question looks very weird to me. you can use the following codes:

colnames(mtcars)
 [1] "mpg"  "cyl"  "disp" "hp"   "drat" "wt"   "qsec" "vs"   "am"   "gear" "carb"
> dim(mtcars)
[1] 32 11
> str(mtcars)
'data.frame':   32 obs. of  11 variables:
 $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
 $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
 $ disp: num  160 160 108 258 360 ...
 $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
 $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
 $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
 $ qsec: num  16.5 17 18.6 19.4 17 ...
 $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
 $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
 $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
 $ carb: num  4 4 1 1 2 1 4 2 2 4 ...


mtcars[1:15,1:6]
                    mpg cyl  disp  hp drat    wt
Mazda RX4          21.0   6 160.0 110 3.90 2.620
Mazda RX4 Wag      21.0   6 160.0 110 3.90 2.875
Datsun 710         22.8   4 108.0  93 3.85 2.320
Hornet 4 Drive     21.4   6 258.0 110 3.08 3.215
Hornet Sportabout  18.7   8 360.0 175 3.15 3.440
Valiant            18.1   6 225.0 105 2.76 3.460
Duster 360         14.3   8 360.0 245 3.21 3.570
Merc 240D          24.4   4 146.7  62 3.69 3.190
Merc 230           22.8   4 140.8  95 3.92 3.150
Merc 280           19.2   6 167.6 123 3.92 3.440
Merc 280C          17.8   6 167.6 123 3.92 3.440
Merc 450SE         16.4   8 275.8 180 3.07 4.070
Merc 450SL         17.3   8 275.8 180 3.07 3.730
Merc 450SLC        15.2   8 275.8 180 3.07 3.780
Cadillac Fleetwood 10.4   8 472.0 205 2.93 5.250


mtcars[1:20,1]
 [1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4 10.4 14.7 32.4 30.4 33.9

 mtcars[1:20,2]
 [1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4


 mtcars[,2]
 [1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4




mtcars <- mutate(mtcars, name=row.names(mtcars))
> mtcars$ID <- seq(nrow(mtcars))
> mtcars[mtcars$ID %% 2 ==1,]
    mpg cyl  disp  hp drat    wt  qsec vs am gear carb               name ID
1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4          Mazda RX4  1
3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1         Datsun 710  3
5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2  Hornet Sportabout  5
7  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4         Duster 360  7
9  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2           Merc 230  9
11 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4          Merc 280C 11
13 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3         Merc 450SL 13
15 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4 Cadillac Fleetwood 15
17 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4  Chrysler Imperial 17
19 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2        Honda Civic 19
21 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1      Toyota Corona 21
23 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2        AMC Javelin 23
25 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2   Pontiac Firebird 25
27 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2      Porsche 914-2 27
29 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4     Ford Pantera L 29
31 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8      Maserati Bora 31
Kian
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