282: Lab 1
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✖ dplyr::filter() masks stats::filter()
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ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
Question 1: I opened the preloaded data set trees.
trees_dat<-trees
head(trees)
Girth Height Volume
1 8.3 70 10.3
2 8.6 65 10.3
3 8.8 63 10.2
4 10.5 72 16.4
5 10.7 81 18.8
6 10.8 83 19.7
Questions 2 and 3: I manipulated the initial trees data frame to include more
muttrees_dat<-(mutate(trees, diameter= trees$Girth/12))
muttrees_dat2<-(mutate(muttrees_dat, radius=muttrees_dat$diameter/2))
muttrees_dat2<-(mutate(muttrees_dat2, diainches=muttrees_dat2$diameter*12))
head(muttrees_dat2)
Girth Height Volume diameter radius diainches
1 8.3 70 10.3 0.6916667 0.3458333 8.3
2 8.6 65 10.3 0.7166667 0.3583333 8.6
3 8.8 63 10.2 0.7333333 0.3666667 8.8
4 10.5 72 16.4 0.8750000 0.4375000 10.5
5 10.7 81 18.8 0.8916667 0.4458333 10.7
6 10.8 83 19.7 0.9000000 0.4500000 10.8
Question 4:
pens<-penguins
pens<-filter(penguins, species=='Adelie')
head(pens)
# A tibble: 6 × 8
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
<fct> <fct> <dbl> <dbl> <int> <int>
1 Adelie Torgersen 39.1 18.7 181 3750
2 Adelie Torgersen 39.5 17.4 186 3800
3 Adelie Torgersen 40.3 18 195 3250
4 Adelie Torgersen NA NA NA NA
5 Adelie Torgersen 36.7 19.3 193 3450
6 Adelie Torgersen 39.3 20.6 190 3650
# ℹ 2 more variables: sex <fct>, year <int>
Question 5:
pens2<-filter(penguins, island=='Dream')
head(pens2)
# A tibble: 6 × 8
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
<fct> <fct> <dbl> <dbl> <int> <int>
1 Adelie Dream 39.5 16.7 178 3250
2 Adelie Dream 37.2 18.1 178 3900
3 Adelie Dream 39.5 17.8 188 3300
4 Adelie Dream 40.9 18.9 184 3900
5 Adelie Dream 36.4 17 195 3325
6 Adelie Dream 39.2 21.1 196 4150
# ℹ 2 more variables: sex <fct>, year <int>
Question 6:
pens2<-pens2[,c(1,2,3)]
head(pens2)
# A tibble: 6 × 3
species island bill_length_mm
<fct> <fct> <dbl>
1 Adelie Dream 39.5
2 Adelie Dream 37.2
3 Adelie Dream 39.5
4 Adelie Dream 40.9
5 Adelie Dream 36.4
6 Adelie Dream 39.2
Question 7:
lobs<-Loblolly
head(lobs)
height age Seed
1 4.51 3 301
15 10.89 5 301
29 28.72 10 301
43 41.74 15 301
57 52.70 20 301
71 60.92 25 301
Question 8:
widelobs<-lobs %>%
pivot_wider(names_from=Seed, values_from=height)
head(widelobs)
# A tibble: 6 × 15
age `301` `303` `305` `307` `309` `311` `315` `319` `321` `323` `325` `327`
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 3 4.51 4.55 4.79 3.91 4.81 3.88 4.32 4.57 3.77 4.33 4.38 4.12
2 5 10.9 10.9 11.4 9.48 11.2 9.4 10.4 10.6 9.03 10.8 10.5 9.92
3 10 28.7 29.1 30.2 25.7 28.7 26.0 27.2 27.9 25.4 29.0 27.9 26.5
4 15 41.7 42.8 44.4 39.1 41.7 39.6 40.8 41.1 39.0 42.4 40.2 37.8
5 20 52.7 53.9 55.8 50.8 53.3 51.5 51.3 52.4 49.8 53.2 50.1 48.4
6 25 60.9 63.4 64.1 59.1 63.0 59.6 60.1 60.7 60.3 61.6 58.5 56.8
# ℹ 2 more variables: `329` <dbl>, `331` <dbl>
Question 9:
longlobs<-widelobs %>%
pivot_longer(!age, names_to = 'Seed', values_to = 'height')
head(longlobs)
# A tibble: 6 × 3
age Seed height
<dbl> <chr> <dbl>
1 3 301 4.51
2 3 303 4.55
3 3 305 4.79
4 3 307 3.91
5 3 309 4.81
6 3 311 3.88