[In the exercises below we cover the basics of data frames.]

Answers to the exercises are available here.

Exercise 1

Consider two vectors:
x=seq(1,43,along.with=Id)
y=seq(-20,0,along.with=Id)
Create a data.frame df:
>df Id Letter x y 1 1 a 1.000000 -20.000000 2 1 b 4.818182 -18.181818 3 1 c 8.636364 -16.363636 4 2 a 12.454545 -14.545455 5 2 b 16.272727 -12.727273 6 2 c 20.090909 -10.909091 7 3 a 23.909091 -9.090909 8 3 b 27.727273 -7.272727 9 3 c 31.545455 -5.454545 10 4 a 35.363636 -3.636364 11 4 b 39.181818 -1.818182 12 4 c 43.000000 0.000000

Exercise 2

From the previous one data frame df.
Create this data frame:
Id x.a y.a x.b y.b x.c y.c 1 1 1.00000 -20.000000 4.818182 -18.181818 8.636364 -16.363636 4 2 12.45455 -14.545455 16.272727 -12.727273 20.090909 -10.909091 7 3 23.90909 -9.090909 27.727273 -7.272727 31.545455 -5.454545 10 4 35.36364 -3.636364 39.181818 -1.818182 43.000000 0.000000

Exercise 3

Create two data frame df1 and df2:
> df1 Id Age 1 1 14 2 2 12 3 3 15 4 4 10 > df2 Id Sex Code 1 1 F a 2 2 M b 3 3 M c 4 4 F d
From df1 and df2 create M:
>M Id Age Sex Code 1 1 14 F a 2 2 12 M b 3 3 15 M c 4 4 10 F d

Exercise 4

Create a data frame df3:
> df3 id2 score 1 4 100 2 3 98 3 2 94 4 1 99
From M and df3 create N:
Id Age Sex Code score 1 1 14 F a 99 2 2 12 M b 94 3 3 15 M c 98 4 4 10 F d 100

Exercise 5

Consider the previous one data frame N:
1)Remove the variables Sex and Code
2)From N, create a data frame:

values ind 1 1 Id 2 2 Id 3 3 Id 4 4 Id 5 14 Age 6 12 Age 7 15 Age 8 10 Age 9 99 score 10 94 score 11 98 score 12 100 score

Exercise 6

For this exercise, we’ll use the (built-in) dataset trees.
a) Make sure the object is a data frame, if not change it to a data frame.
b) Create a new data frame A:
>A Girth Height Volume mean_tree 13.24839 76 30.17097 min_tree 8.30000 63 10.20000 max_tree 20.60000 87 77.00000 sum_tree 410.70000 2356 935.30000

Exercise 7

Consider the data frame A:
1)Order the entire data frame by the first column.
2)Rename the row names as follows: mean, min, max, tree

Exercise 8

Create an empty data frame with column types:

> df Ints Logicals Doubles Characters (or 0-length row.names)

Exercise 9

Create a data frame XY
X=c(1,2,3,1,4,5,2) Y=c(0,3,2,0,5,9,3) > XY X Y 1 1 0 2 2 3 3 3 2 4 1 0 5 4 5 6 5 9 7 2 3
1)looks at duplicated elements using a provided R function.
2) keeps only the uniques lines on XY using a provided R function.

Exercise 10
For this exercise, we’ll use the (built-in) dataset Titanic.
a) Make sure the object is a data frame, if not change it to a data frame.
b) Define a data frame with value 1st in Class variable, and value NO in Survived variable
and variables Sex, Age and Freq.
Sex Age Freq 1 Male Child 0 5 Female Child 0 9 Male Adult 118 13 Female Adult 4