String data in column names
library(tidyverse)
relig_income
# A tibble: 18 × 11
religion `<$10k` `$10-20k` `$20-30k` `$30-40k` `$40-50k` `$50-75k` `$75-100k`
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Agnostic 27 34 60 81 76 137 122
2 Atheist 12 27 37 52 35 70 73
3 Buddhist 27 21 30 34 33 58 62
4 Catholic 418 617 732 670 638 1116 949
5 Don’t k… 15 14 15 11 10 35 21
6 Evangel… 575 869 1064 982 881 1486 949
7 Hindu 1 9 7 9 11 34 47
8 Histori… 228 244 236 238 197 223 131
9 Jehovah… 20 27 24 24 21 30 15
10 Jewish 19 19 25 25 30 95 69
11 Mainlin… 289 495 619 655 651 1107 939
12 Mormon 29 40 48 51 56 112 85
13 Muslim 6 7 9 10 9 23 16
14 Orthodox 13 17 23 32 32 47 38
15 Other C… 9 7 11 13 13 14 18
16 Other F… 20 33 40 46 49 63 46
17 Other W… 5 2 3 4 2 7 3
18 Unaffil… 217 299 374 365 341 528 407
# ℹ 3 more variables: `$100-150k` <dbl>, `>150k` <dbl>,
# `Don't know/refused` <dbl>
This dataset contains three variables:
- religion, stored in the rows,
- income spread across the column names, and
- count stored in the cell values.
Wider w/fish data
This exercise comes from the pivot vignette and concerns the fish_encounters dataset.
# A tibble: 114 × 3
fish station seen
<fct> <fct> <int>
1 4842 Release 1
2 4842 I80_1 1
3 4842 Lisbon 1
4 4842 Rstr 1
5 4842 Base_TD 1
6 4842 BCE 1
7 4842 BCW 1
8 4842 BCE2 1
9 4842 BCW2 1
10 4842 MAE 1
# ℹ 104 more rows
The fish_encounters dataset, contributed by Myfanwy Johnston, describes when fish swimming down a river are detected by automatic monitoring stations: