| Date | Time | Details |
|---|---|---|
| 2026-03-12 | 6:00pm ET | Pre-Assignment #06 Due |
| 2026-03-13 | 11:59pm ET | Mini-Project #01 Due |
| 2026-03-19 | 6:00pm ET | Pre-Assignment #07 Due |
| 2026-03-22 | 11:59pm ET | Mini-Project Peer Feedback #01 Due |
| 2026-03-26 | 6:00pm ET | Mid-Semester Check-In Slides Due |
| 2026-04-02 | 11:59pm ET | Mid-Semester Teammate Peer Evaluations Due |
| 2026-04-02 | NA | Classes Cancelled (Spring Break – Week 1) |
Software Tools for Data Analysis
STA 9750
Michael Weylandt
Week 5 – Thursday 2026-03-05
Last Updated: 2026-03-05
STA 9750 Week 5
Today: Lecture #04: Single Table dplyr Verbs
These slides can be found online at:
In-class activities (if any) can be found at:
Upcoming TODO
Upcoming student responsibilities:
STA 9750 Week 5
Today: Lecture #04: Single Table dplyr Verbs
Mini-Project #01
Mini-Project #01 due on 2026-03-13 at 11:59pm ET:
Assessing the Impact of SFFA on Campus Diversity One-Year Later
Topics Covered:
- Reproducible Research Tooling
- Packages and Functions
- Basic Data Manipulation (Today)
- Tables for Data Display (In Assignment)
Not everything has a single right answer - be reasonable, justify, and document
MP#01 Analysis
Analysis:
- College Enrollment
- Steps:
- Data Import and Preparation
- Initial Exploration
- Writing Op-Ed
- Practice
dplyrsingle-table calculations
MP#01 Formatting
Formatting:
qmddocument- “Op-Ed” + supporting analysis
- Put Op-Ed at beginning or end, clearly identified
Submission:
- Push to
GitHub - Tag on GitHub issues (
mp_submission_create) - Print to PDF + Submit on Brightspace
MP#01 Rubric
- 8 graded sections (out of 10)
- 3 automatic 10 as long as you copy+paste my code and follow my EDA
Today
Today
- Brief Review
- Single-Table Verbs
- Introduction to MP#01
- Pre-Assignment #04 FAQs
- Wrap-Up
Brief Review
Vectors
A vector is R’s basic data type:
- Fixed length, ordered, same class
Vectors
By default, R tries to respect vector structure in calculations:
Packages
Packages provide additional functionality:
install.packagesone time to download from CRAN (online repository)libraryeach time to activate package before use
No ‘cost’ to running library repeatedly - include as needed if uncertain
Not Found Errors
Common error:
Three checks:
- Spelling errors
- Do you need to load a package?
- Did you run code to define variable above?
Particularly common when moving code into quarto since quarto runs everything “fresh”: all of the code in the qmd and only the code in the qmd
Single-Table Verbs
data.frame
Last week: Vectors
- 1D structures of same type
- Vectorized semantics
- Building blocks of more complex structures
Today: data.frames
data.frame
penguins is a data frame included in recent versions of R
species island bill_len bill_dep flipper_len body_mass sex year
1 Adelie Torgersen 39.1 18.7 181 3750 male 2007
2 Adelie Torgersen 39.5 17.4 186 3800 female 2007
3 Adelie Torgersen 40.3 18.0 195 3250 female 2007
4 Adelie Torgersen NA NA NA NA <NA> 2007
5 Adelie Torgersen 36.7 19.3 193 3450 female 2007
6 Adelie Torgersen 39.3 20.6 190 3650 male 2007
7 Adelie Torgersen 38.9 17.8 181 3625 female 2007
8 Adelie Torgersen 39.2 19.6 195 4675 male 2007
9 Adelie Torgersen 34.1 18.1 193 3475 <NA> 2007
10 Adelie Torgersen 42.0 20.2 190 4250 <NA> 2007
11 Adelie Torgersen 37.8 17.1 186 3300 <NA> 2007
12 Adelie Torgersen 37.8 17.3 180 3700 <NA> 2007
13 Adelie Torgersen 41.1 17.6 182 3200 female 2007
14 Adelie Torgersen 38.6 21.2 191 3800 male 2007
15 Adelie Torgersen 34.6 21.1 198 4400 male 2007
16 Adelie Torgersen 36.6 17.8 185 3700 female 2007
17 Adelie Torgersen 38.7 19.0 195 3450 female 2007
18 Adelie Torgersen 42.5 20.7 197 4500 male 2007
19 Adelie Torgersen 34.4 18.4 184 3325 female 2007
20 Adelie Torgersen 46.0 21.5 194 4200 male 2007
21 Adelie Biscoe 37.8 18.3 174 3400 female 2007
22 Adelie Biscoe 37.7 18.7 180 3600 male 2007
23 Adelie Biscoe 35.9 19.2 189 3800 female 2007
24 Adelie Biscoe 38.2 18.1 185 3950 male 2007
25 Adelie Biscoe 38.8 17.2 180 3800 male 2007
26 Adelie Biscoe 35.3 18.9 187 3800 female 2007
27 Adelie Biscoe 40.6 18.6 183 3550 male 2007
28 Adelie Biscoe 40.5 17.9 187 3200 female 2007
29 Adelie Biscoe 37.9 18.6 172 3150 female 2007
30 Adelie Biscoe 40.5 18.9 180 3950 male 2007
31 Adelie Dream 39.5 16.7 178 3250 female 2007
32 Adelie Dream 37.2 18.1 178 3900 male 2007
33 Adelie Dream 39.5 17.8 188 3300 female 2007
34 Adelie Dream 40.9 18.9 184 3900 male 2007
35 Adelie Dream 36.4 17.0 195 3325 female 2007
36 Adelie Dream 39.2 21.1 196 4150 male 2007
37 Adelie Dream 38.8 20.0 190 3950 male 2007
38 Adelie Dream 42.2 18.5 180 3550 female 2007
39 Adelie Dream 37.6 19.3 181 3300 female 2007
40 Adelie Dream 39.8 19.1 184 4650 male 2007
41 Adelie Dream 36.5 18.0 182 3150 female 2007
42 Adelie Dream 40.8 18.4 195 3900 male 2007
43 Adelie Dream 36.0 18.5 186 3100 female 2007
44 Adelie Dream 44.1 19.7 196 4400 male 2007
45 Adelie Dream 37.0 16.9 185 3000 female 2007
46 Adelie Dream 39.6 18.8 190 4600 male 2007
47 Adelie Dream 41.1 19.0 182 3425 male 2007
48 Adelie Dream 37.5 18.9 179 2975 <NA> 2007
49 Adelie Dream 36.0 17.9 190 3450 female 2007
50 Adelie Dream 42.3 21.2 191 4150 male 2007
51 Adelie Biscoe 39.6 17.7 186 3500 female 2008
52 Adelie Biscoe 40.1 18.9 188 4300 male 2008
53 Adelie Biscoe 35.0 17.9 190 3450 female 2008
54 Adelie Biscoe 42.0 19.5 200 4050 male 2008
55 Adelie Biscoe 34.5 18.1 187 2900 female 2008
56 Adelie Biscoe 41.4 18.6 191 3700 male 2008
57 Adelie Biscoe 39.0 17.5 186 3550 female 2008
58 Adelie Biscoe 40.6 18.8 193 3800 male 2008
59 Adelie Biscoe 36.5 16.6 181 2850 female 2008
60 Adelie Biscoe 37.6 19.1 194 3750 male 2008
61 Adelie Biscoe 35.7 16.9 185 3150 female 2008
62 Adelie Biscoe 41.3 21.1 195 4400 male 2008
63 Adelie Biscoe 37.6 17.0 185 3600 female 2008
64 Adelie Biscoe 41.1 18.2 192 4050 male 2008
65 Adelie Biscoe 36.4 17.1 184 2850 female 2008
66 Adelie Biscoe 41.6 18.0 192 3950 male 2008
67 Adelie Biscoe 35.5 16.2 195 3350 female 2008
68 Adelie Biscoe 41.1 19.1 188 4100 male 2008
69 Adelie Torgersen 35.9 16.6 190 3050 female 2008
70 Adelie Torgersen 41.8 19.4 198 4450 male 2008
71 Adelie Torgersen 33.5 19.0 190 3600 female 2008
72 Adelie Torgersen 39.7 18.4 190 3900 male 2008
73 Adelie Torgersen 39.6 17.2 196 3550 female 2008
74 Adelie Torgersen 45.8 18.9 197 4150 male 2008
75 Adelie Torgersen 35.5 17.5 190 3700 female 2008
76 Adelie Torgersen 42.8 18.5 195 4250 male 2008
77 Adelie Torgersen 40.9 16.8 191 3700 female 2008
78 Adelie Torgersen 37.2 19.4 184 3900 male 2008
79 Adelie Torgersen 36.2 16.1 187 3550 female 2008
80 Adelie Torgersen 42.1 19.1 195 4000 male 2008
81 Adelie Torgersen 34.6 17.2 189 3200 female 2008
82 Adelie Torgersen 42.9 17.6 196 4700 male 2008
83 Adelie Torgersen 36.7 18.8 187 3800 female 2008
84 Adelie Torgersen 35.1 19.4 193 4200 male 2008
85 Adelie Dream 37.3 17.8 191 3350 female 2008
86 Adelie Dream 41.3 20.3 194 3550 male 2008
87 Adelie Dream 36.3 19.5 190 3800 male 2008
88 Adelie Dream 36.9 18.6 189 3500 female 2008
89 Adelie Dream 38.3 19.2 189 3950 male 2008
90 Adelie Dream 38.9 18.8 190 3600 female 2008
91 Adelie Dream 35.7 18.0 202 3550 female 2008
92 Adelie Dream 41.1 18.1 205 4300 male 2008
93 Adelie Dream 34.0 17.1 185 3400 female 2008
94 Adelie Dream 39.6 18.1 186 4450 male 2008
95 Adelie Dream 36.2 17.3 187 3300 female 2008
96 Adelie Dream 40.8 18.9 208 4300 male 2008
97 Adelie Dream 38.1 18.6 190 3700 female 2008
98 Adelie Dream 40.3 18.5 196 4350 male 2008
99 Adelie Dream 33.1 16.1 178 2900 female 2008
100 Adelie Dream 43.2 18.5 192 4100 male 2008
101 Adelie Biscoe 35.0 17.9 192 3725 female 2009
102 Adelie Biscoe 41.0 20.0 203 4725 male 2009
103 Adelie Biscoe 37.7 16.0 183 3075 female 2009
104 Adelie Biscoe 37.8 20.0 190 4250 male 2009
105 Adelie Biscoe 37.9 18.6 193 2925 female 2009
106 Adelie Biscoe 39.7 18.9 184 3550 male 2009
107 Adelie Biscoe 38.6 17.2 199 3750 female 2009
108 Adelie Biscoe 38.2 20.0 190 3900 male 2009
109 Adelie Biscoe 38.1 17.0 181 3175 female 2009
110 Adelie Biscoe 43.2 19.0 197 4775 male 2009
111 Adelie Biscoe 38.1 16.5 198 3825 female 2009
112 Adelie Biscoe 45.6 20.3 191 4600 male 2009
113 Adelie Biscoe 39.7 17.7 193 3200 female 2009
114 Adelie Biscoe 42.2 19.5 197 4275 male 2009
115 Adelie Biscoe 39.6 20.7 191 3900 female 2009
116 Adelie Biscoe 42.7 18.3 196 4075 male 2009
117 Adelie Torgersen 38.6 17.0 188 2900 female 2009
118 Adelie Torgersen 37.3 20.5 199 3775 male 2009
119 Adelie Torgersen 35.7 17.0 189 3350 female 2009
120 Adelie Torgersen 41.1 18.6 189 3325 male 2009
121 Adelie Torgersen 36.2 17.2 187 3150 female 2009
122 Adelie Torgersen 37.7 19.8 198 3500 male 2009
123 Adelie Torgersen 40.2 17.0 176 3450 female 2009
124 Adelie Torgersen 41.4 18.5 202 3875 male 2009
125 Adelie Torgersen 35.2 15.9 186 3050 female 2009
126 Adelie Torgersen 40.6 19.0 199 4000 male 2009
127 Adelie Torgersen 38.8 17.6 191 3275 female 2009
128 Adelie Torgersen 41.5 18.3 195 4300 male 2009
129 Adelie Torgersen 39.0 17.1 191 3050 female 2009
130 Adelie Torgersen 44.1 18.0 210 4000 male 2009
131 Adelie Torgersen 38.5 17.9 190 3325 female 2009
132 Adelie Torgersen 43.1 19.2 197 3500 male 2009
133 Adelie Dream 36.8 18.5 193 3500 female 2009
134 Adelie Dream 37.5 18.5 199 4475 male 2009
135 Adelie Dream 38.1 17.6 187 3425 female 2009
136 Adelie Dream 41.1 17.5 190 3900 male 2009
137 Adelie Dream 35.6 17.5 191 3175 female 2009
138 Adelie Dream 40.2 20.1 200 3975 male 2009
139 Adelie Dream 37.0 16.5 185 3400 female 2009
140 Adelie Dream 39.7 17.9 193 4250 male 2009
141 Adelie Dream 40.2 17.1 193 3400 female 2009
142 Adelie Dream 40.6 17.2 187 3475 male 2009
143 Adelie Dream 32.1 15.5 188 3050 female 2009
144 Adelie Dream 40.7 17.0 190 3725 male 2009
145 Adelie Dream 37.3 16.8 192 3000 female 2009
146 Adelie Dream 39.0 18.7 185 3650 male 2009
147 Adelie Dream 39.2 18.6 190 4250 male 2009
148 Adelie Dream 36.6 18.4 184 3475 female 2009
149 Adelie Dream 36.0 17.8 195 3450 female 2009
150 Adelie Dream 37.8 18.1 193 3750 male 2009
151 Adelie Dream 36.0 17.1 187 3700 female 2009
152 Adelie Dream 41.5 18.5 201 4000 male 2009
153 Gentoo Biscoe 46.1 13.2 211 4500 female 2007
154 Gentoo Biscoe 50.0 16.3 230 5700 male 2007
155 Gentoo Biscoe 48.7 14.1 210 4450 female 2007
156 Gentoo Biscoe 50.0 15.2 218 5700 male 2007
157 Gentoo Biscoe 47.6 14.5 215 5400 male 2007
158 Gentoo Biscoe 46.5 13.5 210 4550 female 2007
159 Gentoo Biscoe 45.4 14.6 211 4800 female 2007
160 Gentoo Biscoe 46.7 15.3 219 5200 male 2007
161 Gentoo Biscoe 43.3 13.4 209 4400 female 2007
162 Gentoo Biscoe 46.8 15.4 215 5150 male 2007
163 Gentoo Biscoe 40.9 13.7 214 4650 female 2007
164 Gentoo Biscoe 49.0 16.1 216 5550 male 2007
165 Gentoo Biscoe 45.5 13.7 214 4650 female 2007
166 Gentoo Biscoe 48.4 14.6 213 5850 male 2007
167 Gentoo Biscoe 45.8 14.6 210 4200 female 2007
168 Gentoo Biscoe 49.3 15.7 217 5850 male 2007
169 Gentoo Biscoe 42.0 13.5 210 4150 female 2007
170 Gentoo Biscoe 49.2 15.2 221 6300 male 2007
171 Gentoo Biscoe 46.2 14.5 209 4800 female 2007
172 Gentoo Biscoe 48.7 15.1 222 5350 male 2007
173 Gentoo Biscoe 50.2 14.3 218 5700 male 2007
174 Gentoo Biscoe 45.1 14.5 215 5000 female 2007
175 Gentoo Biscoe 46.5 14.5 213 4400 female 2007
176 Gentoo Biscoe 46.3 15.8 215 5050 male 2007
177 Gentoo Biscoe 42.9 13.1 215 5000 female 2007
178 Gentoo Biscoe 46.1 15.1 215 5100 male 2007
179 Gentoo Biscoe 44.5 14.3 216 4100 <NA> 2007
180 Gentoo Biscoe 47.8 15.0 215 5650 male 2007
181 Gentoo Biscoe 48.2 14.3 210 4600 female 2007
182 Gentoo Biscoe 50.0 15.3 220 5550 male 2007
183 Gentoo Biscoe 47.3 15.3 222 5250 male 2007
184 Gentoo Biscoe 42.8 14.2 209 4700 female 2007
185 Gentoo Biscoe 45.1 14.5 207 5050 female 2007
186 Gentoo Biscoe 59.6 17.0 230 6050 male 2007
187 Gentoo Biscoe 49.1 14.8 220 5150 female 2008
188 Gentoo Biscoe 48.4 16.3 220 5400 male 2008
189 Gentoo Biscoe 42.6 13.7 213 4950 female 2008
190 Gentoo Biscoe 44.4 17.3 219 5250 male 2008
191 Gentoo Biscoe 44.0 13.6 208 4350 female 2008
192 Gentoo Biscoe 48.7 15.7 208 5350 male 2008
193 Gentoo Biscoe 42.7 13.7 208 3950 female 2008
194 Gentoo Biscoe 49.6 16.0 225 5700 male 2008
195 Gentoo Biscoe 45.3 13.7 210 4300 female 2008
196 Gentoo Biscoe 49.6 15.0 216 4750 male 2008
197 Gentoo Biscoe 50.5 15.9 222 5550 male 2008
198 Gentoo Biscoe 43.6 13.9 217 4900 female 2008
199 Gentoo Biscoe 45.5 13.9 210 4200 female 2008
200 Gentoo Biscoe 50.5 15.9 225 5400 male 2008
201 Gentoo Biscoe 44.9 13.3 213 5100 female 2008
202 Gentoo Biscoe 45.2 15.8 215 5300 male 2008
203 Gentoo Biscoe 46.6 14.2 210 4850 female 2008
204 Gentoo Biscoe 48.5 14.1 220 5300 male 2008
205 Gentoo Biscoe 45.1 14.4 210 4400 female 2008
206 Gentoo Biscoe 50.1 15.0 225 5000 male 2008
207 Gentoo Biscoe 46.5 14.4 217 4900 female 2008
208 Gentoo Biscoe 45.0 15.4 220 5050 male 2008
209 Gentoo Biscoe 43.8 13.9 208 4300 female 2008
210 Gentoo Biscoe 45.5 15.0 220 5000 male 2008
211 Gentoo Biscoe 43.2 14.5 208 4450 female 2008
212 Gentoo Biscoe 50.4 15.3 224 5550 male 2008
213 Gentoo Biscoe 45.3 13.8 208 4200 female 2008
214 Gentoo Biscoe 46.2 14.9 221 5300 male 2008
215 Gentoo Biscoe 45.7 13.9 214 4400 female 2008
216 Gentoo Biscoe 54.3 15.7 231 5650 male 2008
217 Gentoo Biscoe 45.8 14.2 219 4700 female 2008
218 Gentoo Biscoe 49.8 16.8 230 5700 male 2008
219 Gentoo Biscoe 46.2 14.4 214 4650 <NA> 2008
220 Gentoo Biscoe 49.5 16.2 229 5800 male 2008
221 Gentoo Biscoe 43.5 14.2 220 4700 female 2008
222 Gentoo Biscoe 50.7 15.0 223 5550 male 2008
223 Gentoo Biscoe 47.7 15.0 216 4750 female 2008
224 Gentoo Biscoe 46.4 15.6 221 5000 male 2008
225 Gentoo Biscoe 48.2 15.6 221 5100 male 2008
226 Gentoo Biscoe 46.5 14.8 217 5200 female 2008
227 Gentoo Biscoe 46.4 15.0 216 4700 female 2008
228 Gentoo Biscoe 48.6 16.0 230 5800 male 2008
229 Gentoo Biscoe 47.5 14.2 209 4600 female 2008
230 Gentoo Biscoe 51.1 16.3 220 6000 male 2008
231 Gentoo Biscoe 45.2 13.8 215 4750 female 2008
232 Gentoo Biscoe 45.2 16.4 223 5950 male 2008
233 Gentoo Biscoe 49.1 14.5 212 4625 female 2009
234 Gentoo Biscoe 52.5 15.6 221 5450 male 2009
235 Gentoo Biscoe 47.4 14.6 212 4725 female 2009
236 Gentoo Biscoe 50.0 15.9 224 5350 male 2009
237 Gentoo Biscoe 44.9 13.8 212 4750 female 2009
238 Gentoo Biscoe 50.8 17.3 228 5600 male 2009
239 Gentoo Biscoe 43.4 14.4 218 4600 female 2009
240 Gentoo Biscoe 51.3 14.2 218 5300 male 2009
241 Gentoo Biscoe 47.5 14.0 212 4875 female 2009
242 Gentoo Biscoe 52.1 17.0 230 5550 male 2009
243 Gentoo Biscoe 47.5 15.0 218 4950 female 2009
244 Gentoo Biscoe 52.2 17.1 228 5400 male 2009
245 Gentoo Biscoe 45.5 14.5 212 4750 female 2009
246 Gentoo Biscoe 49.5 16.1 224 5650 male 2009
247 Gentoo Biscoe 44.5 14.7 214 4850 female 2009
248 Gentoo Biscoe 50.8 15.7 226 5200 male 2009
249 Gentoo Biscoe 49.4 15.8 216 4925 male 2009
250 Gentoo Biscoe 46.9 14.6 222 4875 female 2009
251 Gentoo Biscoe 48.4 14.4 203 4625 female 2009
252 Gentoo Biscoe 51.1 16.5 225 5250 male 2009
253 Gentoo Biscoe 48.5 15.0 219 4850 female 2009
254 Gentoo Biscoe 55.9 17.0 228 5600 male 2009
255 Gentoo Biscoe 47.2 15.5 215 4975 female 2009
256 Gentoo Biscoe 49.1 15.0 228 5500 male 2009
257 Gentoo Biscoe 47.3 13.8 216 4725 <NA> 2009
258 Gentoo Biscoe 46.8 16.1 215 5500 male 2009
259 Gentoo Biscoe 41.7 14.7 210 4700 female 2009
260 Gentoo Biscoe 53.4 15.8 219 5500 male 2009
261 Gentoo Biscoe 43.3 14.0 208 4575 female 2009
262 Gentoo Biscoe 48.1 15.1 209 5500 male 2009
263 Gentoo Biscoe 50.5 15.2 216 5000 female 2009
264 Gentoo Biscoe 49.8 15.9 229 5950 male 2009
265 Gentoo Biscoe 43.5 15.2 213 4650 female 2009
266 Gentoo Biscoe 51.5 16.3 230 5500 male 2009
267 Gentoo Biscoe 46.2 14.1 217 4375 female 2009
268 Gentoo Biscoe 55.1 16.0 230 5850 male 2009
269 Gentoo Biscoe 44.5 15.7 217 4875 <NA> 2009
270 Gentoo Biscoe 48.8 16.2 222 6000 male 2009
271 Gentoo Biscoe 47.2 13.7 214 4925 female 2009
272 Gentoo Biscoe NA NA NA NA <NA> 2009
273 Gentoo Biscoe 46.8 14.3 215 4850 female 2009
274 Gentoo Biscoe 50.4 15.7 222 5750 male 2009
275 Gentoo Biscoe 45.2 14.8 212 5200 female 2009
276 Gentoo Biscoe 49.9 16.1 213 5400 male 2009
277 Chinstrap Dream 46.5 17.9 192 3500 female 2007
278 Chinstrap Dream 50.0 19.5 196 3900 male 2007
279 Chinstrap Dream 51.3 19.2 193 3650 male 2007
280 Chinstrap Dream 45.4 18.7 188 3525 female 2007
281 Chinstrap Dream 52.7 19.8 197 3725 male 2007
282 Chinstrap Dream 45.2 17.8 198 3950 female 2007
283 Chinstrap Dream 46.1 18.2 178 3250 female 2007
284 Chinstrap Dream 51.3 18.2 197 3750 male 2007
285 Chinstrap Dream 46.0 18.9 195 4150 female 2007
286 Chinstrap Dream 51.3 19.9 198 3700 male 2007
287 Chinstrap Dream 46.6 17.8 193 3800 female 2007
288 Chinstrap Dream 51.7 20.3 194 3775 male 2007
289 Chinstrap Dream 47.0 17.3 185 3700 female 2007
290 Chinstrap Dream 52.0 18.1 201 4050 male 2007
291 Chinstrap Dream 45.9 17.1 190 3575 female 2007
292 Chinstrap Dream 50.5 19.6 201 4050 male 2007
293 Chinstrap Dream 50.3 20.0 197 3300 male 2007
294 Chinstrap Dream 58.0 17.8 181 3700 female 2007
295 Chinstrap Dream 46.4 18.6 190 3450 female 2007
296 Chinstrap Dream 49.2 18.2 195 4400 male 2007
297 Chinstrap Dream 42.4 17.3 181 3600 female 2007
298 Chinstrap Dream 48.5 17.5 191 3400 male 2007
299 Chinstrap Dream 43.2 16.6 187 2900 female 2007
300 Chinstrap Dream 50.6 19.4 193 3800 male 2007
301 Chinstrap Dream 46.7 17.9 195 3300 female 2007
302 Chinstrap Dream 52.0 19.0 197 4150 male 2007
303 Chinstrap Dream 50.5 18.4 200 3400 female 2008
304 Chinstrap Dream 49.5 19.0 200 3800 male 2008
305 Chinstrap Dream 46.4 17.8 191 3700 female 2008
306 Chinstrap Dream 52.8 20.0 205 4550 male 2008
307 Chinstrap Dream 40.9 16.6 187 3200 female 2008
308 Chinstrap Dream 54.2 20.8 201 4300 male 2008
309 Chinstrap Dream 42.5 16.7 187 3350 female 2008
310 Chinstrap Dream 51.0 18.8 203 4100 male 2008
311 Chinstrap Dream 49.7 18.6 195 3600 male 2008
312 Chinstrap Dream 47.5 16.8 199 3900 female 2008
313 Chinstrap Dream 47.6 18.3 195 3850 female 2008
314 Chinstrap Dream 52.0 20.7 210 4800 male 2008
315 Chinstrap Dream 46.9 16.6 192 2700 female 2008
316 Chinstrap Dream 53.5 19.9 205 4500 male 2008
317 Chinstrap Dream 49.0 19.5 210 3950 male 2008
318 Chinstrap Dream 46.2 17.5 187 3650 female 2008
319 Chinstrap Dream 50.9 19.1 196 3550 male 2008
320 Chinstrap Dream 45.5 17.0 196 3500 female 2008
321 Chinstrap Dream 50.9 17.9 196 3675 female 2009
322 Chinstrap Dream 50.8 18.5 201 4450 male 2009
323 Chinstrap Dream 50.1 17.9 190 3400 female 2009
324 Chinstrap Dream 49.0 19.6 212 4300 male 2009
325 Chinstrap Dream 51.5 18.7 187 3250 male 2009
326 Chinstrap Dream 49.8 17.3 198 3675 female 2009
327 Chinstrap Dream 48.1 16.4 199 3325 female 2009
328 Chinstrap Dream 51.4 19.0 201 3950 male 2009
329 Chinstrap Dream 45.7 17.3 193 3600 female 2009
330 Chinstrap Dream 50.7 19.7 203 4050 male 2009
331 Chinstrap Dream 42.5 17.3 187 3350 female 2009
332 Chinstrap Dream 52.2 18.8 197 3450 male 2009
333 Chinstrap Dream 45.2 16.6 191 3250 female 2009
334 Chinstrap Dream 49.3 19.9 203 4050 male 2009
335 Chinstrap Dream 50.2 18.8 202 3800 male 2009
336 Chinstrap Dream 45.6 19.4 194 3525 female 2009
337 Chinstrap Dream 51.9 19.5 206 3950 male 2009
338 Chinstrap Dream 46.8 16.5 189 3650 female 2009
339 Chinstrap Dream 45.7 17.0 195 3650 female 2009
340 Chinstrap Dream 55.8 19.8 207 4000 male 2009
341 Chinstrap Dream 43.5 18.1 202 3400 female 2009
342 Chinstrap Dream 49.6 18.2 193 3775 male 2009
343 Chinstrap Dream 50.8 19.0 210 4100 male 2009
344 Chinstrap Dream 50.2 18.7 198 3775 female 2009data.frame
A data frame is a
- Rectangular array of data; where
- Each row corresponds to a single observation
- Each column is a single ‘feature’ implemented as a vector
- Same type within columns; different types across columns
An inherently tidy data structure
Tidy Data
The concept of “tidyness”:
- Principles to make data manipulation safe and easy
- Decrease chance of errors
- Increase productivity
Standard format used by all tidyverse packages
Tidy Data
Recall our penguins:
species bill_len flipper_len body_mass sex
1 Adelie 39.1 181 3750 male
2 Adelie 39.5 186 3800 female
3 Adelie 40.3 195 3250 female
4 Adelie NA NA NA <NA>
5 Adelie 36.7 193 3450 female
6 Adelie 39.3 190 3650 maleKey features:
- Each row is one observation (🐧)
- Each column has one and only one fact
- All values are in the table
- Not hiding in row and column names
Tidy Data
Figure from
Rfor Data Science by H. Wickham
Tidy - Why?
Why emphasize tidy data?
Minimize distractions:
- Free to focus on analysis not code
Once data is “tidy”, you can focus on the real questions
First goal for data pre-processing (“tidying up”)
Tidy - Who (and When)?
The name and principles of “tidy data” were popularized by H. Wickham (2014)
Core ideas are much older, dating back to (at least) Codd’s Relational Model in the 1970s, now ubiquitous in relational databases (SQL)
Now found in:
- Python (
pandas) - Julia (
DataFrames) - Rust (
polars) - and more
Tidy - How (and Where)?
tidyverse - Packages for Manipulating Tidy Data:
ggplot2: Visualizationdplyr:SQL-like operationstidyr: Reshaping and cleaning datareadr: Ingest tidy data intoR- Tidy manipulation of different data types:
stringr,forcats,lubridate
More helpers in the background (tibble, vctrs, …)
Aside: tibbles
You will sometimes see tibble (tbl_df) as a synonym for data.frame
- Minor differences in output formatting
- Fewer edge cases
Some Untidy Examples
Baruch college business core enrollment:
# A tibble: 6 × 4
Semester Course Enrollment Cap
<chr> <chr> <dbl> <dbl>
1 Fall Accounting 200 250
2 Fall Law 100 125
3 Fall Statistics 200 200
4 Spring Accounting 300 350
5 Spring Law 50 100
6 Spring Statistics 400 400Tidy! ✅
- Each row is one unit (a class) 👍
- Columns are well-typed 👍
- One piece of information per column 👍
Some Untidy Examples
A different structure:
# A tibble: 6 × 3
Semester Course Enrollment
<chr> <chr> <chr>
1 Fall Accounting "200 of 250"
2 Fall Law "100 of 125"
3 Fall Statistics "200 of 200"
4 Spring Accounting "300 of 350"
5 Spring Law " 50 of 100"
6 Spring Statistics "400 of 400"Untidy! ❌
Multiple pieces of information per cell (Enrollment)
Some Untidy Examples
A different structure:
# A tibble: 12 × 4
Semester Course Number Type
<chr> <chr> <dbl> <chr>
1 Fall Accounting 200 Enrollment
2 Fall Accounting 250 Cap
3 Fall Law 100 Enrollment
4 Fall Law 125 Cap
5 Fall Statistics 200 Enrollment
6 Fall Statistics 200 Cap
7 Spring Accounting 300 Enrollment
8 Spring Accounting 350 Cap
9 Spring Law 50 Enrollment
10 Spring Law 100 Cap
11 Spring Statistics 400 Enrollment
12 Spring Statistics 400 Cap Untidy! ❌
Mixing two pieces of information (Enrollments and Caps)
Tip: When one unit spans multiple rows, likely untidy
Some Untidy Examples
A different structure:
# A tibble: 6 × 3
Semester Course Enrollment
<chr> <chr> <dbl>
1 Fall Accounting 200
2 Fall Law 100
3 Fall Statistics 200
# ℹ 3 more rowsand
# A tibble: 6 × 3
Semester Course Cap
<chr> <chr> <dbl>
1 Fall Accounting 250
2 Fall Law 125
3 Fall Statistics 200
# ℹ 3 more rows[A little bit] Untidy! ❌
Data spread across multiple tables - we will handle this next week
dplyr
The dplyr package exists for SQL-type manipulations of data.frames
Can load directly
library(dplyr)
or with the tidyverse meta-package
library(tidyverse)
tidyverse will give some messages about name conflicts - these are harmless
Data Frame Structure
Use the glimpse function to get a high-level summary of a data frame:
Rows: 344
Columns: 8
$ species <fct> Adelie, Adelie, Adelie, Adelie, Adelie, Adelie, Adelie, Ad…
$ island <fct> Torgersen, Torgersen, Torgersen, Torgersen, Torgersen, Tor…
$ bill_len <dbl> 39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39.2, 34.1, 42.0, …
$ bill_dep <dbl> 18.7, 17.4, 18.0, NA, 19.3, 20.6, 17.8, 19.6, 18.1, 20.2, …
$ flipper_len <int> 181, 186, 195, NA, 193, 190, 181, 195, 193, 190, 186, 180,…
$ body_mass <int> 3750, 3800, 3250, NA, 3450, 3650, 3625, 4675, 3475, 4250, …
$ sex <fct> male, female, female, NA, female, male, female, male, NA, …
$ year <int> 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007…select and rename
How can we select certain columns?
select() will pick columns
species island bill_dep
1 Adelie Torgersen 18.7
2 Adelie Torgersen 17.4
3 Adelie Torgersen 18.0
4 Adelie Torgersen NA
5 Adelie Torgersen 19.3
6 Adelie Torgersen 20.6
7 Adelie Torgersen 17.8
8 Adelie Torgersen 19.6
9 Adelie Torgersen 18.1
10 Adelie Torgersen 20.2
11 Adelie Torgersen 17.1
12 Adelie Torgersen 17.3
13 Adelie Torgersen 17.6
14 Adelie Torgersen 21.2
15 Adelie Torgersen 21.1
16 Adelie Torgersen 17.8
17 Adelie Torgersen 19.0
18 Adelie Torgersen 20.7
19 Adelie Torgersen 18.4
20 Adelie Torgersen 21.5
21 Adelie Biscoe 18.3
22 Adelie Biscoe 18.7
23 Adelie Biscoe 19.2
24 Adelie Biscoe 18.1
25 Adelie Biscoe 17.2
26 Adelie Biscoe 18.9
27 Adelie Biscoe 18.6
28 Adelie Biscoe 17.9
29 Adelie Biscoe 18.6
30 Adelie Biscoe 18.9
31 Adelie Dream 16.7
32 Adelie Dream 18.1
33 Adelie Dream 17.8
34 Adelie Dream 18.9
35 Adelie Dream 17.0
36 Adelie Dream 21.1
37 Adelie Dream 20.0
38 Adelie Dream 18.5
39 Adelie Dream 19.3
40 Adelie Dream 19.1
41 Adelie Dream 18.0
42 Adelie Dream 18.4
43 Adelie Dream 18.5
44 Adelie Dream 19.7
45 Adelie Dream 16.9
46 Adelie Dream 18.8
47 Adelie Dream 19.0
48 Adelie Dream 18.9
49 Adelie Dream 17.9
50 Adelie Dream 21.2
51 Adelie Biscoe 17.7
52 Adelie Biscoe 18.9
53 Adelie Biscoe 17.9
54 Adelie Biscoe 19.5
55 Adelie Biscoe 18.1
56 Adelie Biscoe 18.6
57 Adelie Biscoe 17.5
58 Adelie Biscoe 18.8
59 Adelie Biscoe 16.6
60 Adelie Biscoe 19.1
61 Adelie Biscoe 16.9
62 Adelie Biscoe 21.1
63 Adelie Biscoe 17.0
64 Adelie Biscoe 18.2
65 Adelie Biscoe 17.1
66 Adelie Biscoe 18.0
67 Adelie Biscoe 16.2
68 Adelie Biscoe 19.1
69 Adelie Torgersen 16.6
70 Adelie Torgersen 19.4
71 Adelie Torgersen 19.0
72 Adelie Torgersen 18.4
73 Adelie Torgersen 17.2
74 Adelie Torgersen 18.9
75 Adelie Torgersen 17.5
76 Adelie Torgersen 18.5
77 Adelie Torgersen 16.8
78 Adelie Torgersen 19.4
79 Adelie Torgersen 16.1
80 Adelie Torgersen 19.1
81 Adelie Torgersen 17.2
82 Adelie Torgersen 17.6
83 Adelie Torgersen 18.8
84 Adelie Torgersen 19.4
85 Adelie Dream 17.8
86 Adelie Dream 20.3
87 Adelie Dream 19.5
88 Adelie Dream 18.6
89 Adelie Dream 19.2
90 Adelie Dream 18.8
91 Adelie Dream 18.0
92 Adelie Dream 18.1
93 Adelie Dream 17.1
94 Adelie Dream 18.1
95 Adelie Dream 17.3
96 Adelie Dream 18.9
97 Adelie Dream 18.6
98 Adelie Dream 18.5
99 Adelie Dream 16.1
100 Adelie Dream 18.5
101 Adelie Biscoe 17.9
102 Adelie Biscoe 20.0
103 Adelie Biscoe 16.0
104 Adelie Biscoe 20.0
105 Adelie Biscoe 18.6
106 Adelie Biscoe 18.9
107 Adelie Biscoe 17.2
108 Adelie Biscoe 20.0
109 Adelie Biscoe 17.0
110 Adelie Biscoe 19.0
111 Adelie Biscoe 16.5
112 Adelie Biscoe 20.3
113 Adelie Biscoe 17.7
114 Adelie Biscoe 19.5
115 Adelie Biscoe 20.7
116 Adelie Biscoe 18.3
117 Adelie Torgersen 17.0
118 Adelie Torgersen 20.5
119 Adelie Torgersen 17.0
120 Adelie Torgersen 18.6
121 Adelie Torgersen 17.2
122 Adelie Torgersen 19.8
123 Adelie Torgersen 17.0
124 Adelie Torgersen 18.5
125 Adelie Torgersen 15.9
126 Adelie Torgersen 19.0
127 Adelie Torgersen 17.6
128 Adelie Torgersen 18.3
129 Adelie Torgersen 17.1
130 Adelie Torgersen 18.0
131 Adelie Torgersen 17.9
132 Adelie Torgersen 19.2
133 Adelie Dream 18.5
134 Adelie Dream 18.5
135 Adelie Dream 17.6
136 Adelie Dream 17.5
137 Adelie Dream 17.5
138 Adelie Dream 20.1
139 Adelie Dream 16.5
140 Adelie Dream 17.9
141 Adelie Dream 17.1
142 Adelie Dream 17.2
143 Adelie Dream 15.5
144 Adelie Dream 17.0
145 Adelie Dream 16.8
146 Adelie Dream 18.7
147 Adelie Dream 18.6
148 Adelie Dream 18.4
149 Adelie Dream 17.8
150 Adelie Dream 18.1
151 Adelie Dream 17.1
152 Adelie Dream 18.5
153 Gentoo Biscoe 13.2
154 Gentoo Biscoe 16.3
155 Gentoo Biscoe 14.1
156 Gentoo Biscoe 15.2
157 Gentoo Biscoe 14.5
158 Gentoo Biscoe 13.5
159 Gentoo Biscoe 14.6
160 Gentoo Biscoe 15.3
161 Gentoo Biscoe 13.4
162 Gentoo Biscoe 15.4
163 Gentoo Biscoe 13.7
164 Gentoo Biscoe 16.1
165 Gentoo Biscoe 13.7
166 Gentoo Biscoe 14.6
167 Gentoo Biscoe 14.6
168 Gentoo Biscoe 15.7
169 Gentoo Biscoe 13.5
170 Gentoo Biscoe 15.2
171 Gentoo Biscoe 14.5
172 Gentoo Biscoe 15.1
173 Gentoo Biscoe 14.3
174 Gentoo Biscoe 14.5
175 Gentoo Biscoe 14.5
176 Gentoo Biscoe 15.8
177 Gentoo Biscoe 13.1
178 Gentoo Biscoe 15.1
179 Gentoo Biscoe 14.3
180 Gentoo Biscoe 15.0
181 Gentoo Biscoe 14.3
182 Gentoo Biscoe 15.3
183 Gentoo Biscoe 15.3
184 Gentoo Biscoe 14.2
185 Gentoo Biscoe 14.5
186 Gentoo Biscoe 17.0
187 Gentoo Biscoe 14.8
188 Gentoo Biscoe 16.3
189 Gentoo Biscoe 13.7
190 Gentoo Biscoe 17.3
191 Gentoo Biscoe 13.6
192 Gentoo Biscoe 15.7
193 Gentoo Biscoe 13.7
194 Gentoo Biscoe 16.0
195 Gentoo Biscoe 13.7
196 Gentoo Biscoe 15.0
197 Gentoo Biscoe 15.9
198 Gentoo Biscoe 13.9
199 Gentoo Biscoe 13.9
200 Gentoo Biscoe 15.9
201 Gentoo Biscoe 13.3
202 Gentoo Biscoe 15.8
203 Gentoo Biscoe 14.2
204 Gentoo Biscoe 14.1
205 Gentoo Biscoe 14.4
206 Gentoo Biscoe 15.0
207 Gentoo Biscoe 14.4
208 Gentoo Biscoe 15.4
209 Gentoo Biscoe 13.9
210 Gentoo Biscoe 15.0
211 Gentoo Biscoe 14.5
212 Gentoo Biscoe 15.3
213 Gentoo Biscoe 13.8
214 Gentoo Biscoe 14.9
215 Gentoo Biscoe 13.9
216 Gentoo Biscoe 15.7
217 Gentoo Biscoe 14.2
218 Gentoo Biscoe 16.8
219 Gentoo Biscoe 14.4
220 Gentoo Biscoe 16.2
221 Gentoo Biscoe 14.2
222 Gentoo Biscoe 15.0
223 Gentoo Biscoe 15.0
224 Gentoo Biscoe 15.6
225 Gentoo Biscoe 15.6
226 Gentoo Biscoe 14.8
227 Gentoo Biscoe 15.0
228 Gentoo Biscoe 16.0
229 Gentoo Biscoe 14.2
230 Gentoo Biscoe 16.3
231 Gentoo Biscoe 13.8
232 Gentoo Biscoe 16.4
233 Gentoo Biscoe 14.5
234 Gentoo Biscoe 15.6
235 Gentoo Biscoe 14.6
236 Gentoo Biscoe 15.9
237 Gentoo Biscoe 13.8
238 Gentoo Biscoe 17.3
239 Gentoo Biscoe 14.4
240 Gentoo Biscoe 14.2
241 Gentoo Biscoe 14.0
242 Gentoo Biscoe 17.0
243 Gentoo Biscoe 15.0
244 Gentoo Biscoe 17.1
245 Gentoo Biscoe 14.5
246 Gentoo Biscoe 16.1
247 Gentoo Biscoe 14.7
248 Gentoo Biscoe 15.7
249 Gentoo Biscoe 15.8
250 Gentoo Biscoe 14.6
251 Gentoo Biscoe 14.4
252 Gentoo Biscoe 16.5
253 Gentoo Biscoe 15.0
254 Gentoo Biscoe 17.0
255 Gentoo Biscoe 15.5
256 Gentoo Biscoe 15.0
257 Gentoo Biscoe 13.8
258 Gentoo Biscoe 16.1
259 Gentoo Biscoe 14.7
260 Gentoo Biscoe 15.8
261 Gentoo Biscoe 14.0
262 Gentoo Biscoe 15.1
263 Gentoo Biscoe 15.2
264 Gentoo Biscoe 15.9
265 Gentoo Biscoe 15.2
266 Gentoo Biscoe 16.3
267 Gentoo Biscoe 14.1
268 Gentoo Biscoe 16.0
269 Gentoo Biscoe 15.7
270 Gentoo Biscoe 16.2
271 Gentoo Biscoe 13.7
272 Gentoo Biscoe NA
273 Gentoo Biscoe 14.3
274 Gentoo Biscoe 15.7
275 Gentoo Biscoe 14.8
276 Gentoo Biscoe 16.1
277 Chinstrap Dream 17.9
278 Chinstrap Dream 19.5
279 Chinstrap Dream 19.2
280 Chinstrap Dream 18.7
281 Chinstrap Dream 19.8
282 Chinstrap Dream 17.8
283 Chinstrap Dream 18.2
284 Chinstrap Dream 18.2
285 Chinstrap Dream 18.9
286 Chinstrap Dream 19.9
287 Chinstrap Dream 17.8
288 Chinstrap Dream 20.3
289 Chinstrap Dream 17.3
290 Chinstrap Dream 18.1
291 Chinstrap Dream 17.1
292 Chinstrap Dream 19.6
293 Chinstrap Dream 20.0
294 Chinstrap Dream 17.8
295 Chinstrap Dream 18.6
296 Chinstrap Dream 18.2
297 Chinstrap Dream 17.3
298 Chinstrap Dream 17.5
299 Chinstrap Dream 16.6
300 Chinstrap Dream 19.4
301 Chinstrap Dream 17.9
302 Chinstrap Dream 19.0
303 Chinstrap Dream 18.4
304 Chinstrap Dream 19.0
305 Chinstrap Dream 17.8
306 Chinstrap Dream 20.0
307 Chinstrap Dream 16.6
308 Chinstrap Dream 20.8
309 Chinstrap Dream 16.7
310 Chinstrap Dream 18.8
311 Chinstrap Dream 18.6
312 Chinstrap Dream 16.8
313 Chinstrap Dream 18.3
314 Chinstrap Dream 20.7
315 Chinstrap Dream 16.6
316 Chinstrap Dream 19.9
317 Chinstrap Dream 19.5
318 Chinstrap Dream 17.5
319 Chinstrap Dream 19.1
320 Chinstrap Dream 17.0
321 Chinstrap Dream 17.9
322 Chinstrap Dream 18.5
323 Chinstrap Dream 17.9
324 Chinstrap Dream 19.6
325 Chinstrap Dream 18.7
326 Chinstrap Dream 17.3
327 Chinstrap Dream 16.4
328 Chinstrap Dream 19.0
329 Chinstrap Dream 17.3
330 Chinstrap Dream 19.7
331 Chinstrap Dream 17.3
332 Chinstrap Dream 18.8
333 Chinstrap Dream 16.6
334 Chinstrap Dream 19.9
335 Chinstrap Dream 18.8
336 Chinstrap Dream 19.4
337 Chinstrap Dream 19.5
338 Chinstrap Dream 16.5
339 Chinstrap Dream 17.0
340 Chinstrap Dream 19.8
341 Chinstrap Dream 18.1
342 Chinstrap Dream 18.2
343 Chinstrap Dream 19.0
344 Chinstrap Dream 18.7Pipe Syntax
Pipe syntax (|>) is syntactic sugar - read as “and then”
Just makes code easier to read:
Exactly the same execution: improved UX
%>% is an older way of doing essentially the same thing - avoid it
Pipe Syntax
Pipe syntax is useful for longer multi-step operations:
Read top to bottom instead of inside out
select and rename
Can also use select to drop columns:
bill_len flipper_len body_mass sex year
1 39.1 181 3750 male 2007
2 39.5 186 3800 female 2007
3 40.3 195 3250 female 2007
4 NA NA NA <NA> 2007
5 36.7 193 3450 female 2007
6 39.3 190 3650 male 2007
7 38.9 181 3625 female 2007
8 39.2 195 4675 male 2007
9 34.1 193 3475 <NA> 2007
10 42.0 190 4250 <NA> 2007
11 37.8 186 3300 <NA> 2007
12 37.8 180 3700 <NA> 2007
13 41.1 182 3200 female 2007
14 38.6 191 3800 male 2007
15 34.6 198 4400 male 2007
16 36.6 185 3700 female 2007
17 38.7 195 3450 female 2007
18 42.5 197 4500 male 2007
19 34.4 184 3325 female 2007
20 46.0 194 4200 male 2007
21 37.8 174 3400 female 2007
22 37.7 180 3600 male 2007
23 35.9 189 3800 female 2007
24 38.2 185 3950 male 2007
25 38.8 180 3800 male 2007
26 35.3 187 3800 female 2007
27 40.6 183 3550 male 2007
28 40.5 187 3200 female 2007
29 37.9 172 3150 female 2007
30 40.5 180 3950 male 2007
31 39.5 178 3250 female 2007
32 37.2 178 3900 male 2007
33 39.5 188 3300 female 2007
34 40.9 184 3900 male 2007
35 36.4 195 3325 female 2007
36 39.2 196 4150 male 2007
37 38.8 190 3950 male 2007
38 42.2 180 3550 female 2007
39 37.6 181 3300 female 2007
40 39.8 184 4650 male 2007
41 36.5 182 3150 female 2007
42 40.8 195 3900 male 2007
43 36.0 186 3100 female 2007
44 44.1 196 4400 male 2007
45 37.0 185 3000 female 2007
46 39.6 190 4600 male 2007
47 41.1 182 3425 male 2007
48 37.5 179 2975 <NA> 2007
49 36.0 190 3450 female 2007
50 42.3 191 4150 male 2007
51 39.6 186 3500 female 2008
52 40.1 188 4300 male 2008
53 35.0 190 3450 female 2008
54 42.0 200 4050 male 2008
55 34.5 187 2900 female 2008
56 41.4 191 3700 male 2008
57 39.0 186 3550 female 2008
58 40.6 193 3800 male 2008
59 36.5 181 2850 female 2008
60 37.6 194 3750 male 2008
61 35.7 185 3150 female 2008
62 41.3 195 4400 male 2008
63 37.6 185 3600 female 2008
64 41.1 192 4050 male 2008
65 36.4 184 2850 female 2008
66 41.6 192 3950 male 2008
67 35.5 195 3350 female 2008
68 41.1 188 4100 male 2008
69 35.9 190 3050 female 2008
70 41.8 198 4450 male 2008
71 33.5 190 3600 female 2008
72 39.7 190 3900 male 2008
73 39.6 196 3550 female 2008
74 45.8 197 4150 male 2008
75 35.5 190 3700 female 2008
76 42.8 195 4250 male 2008
77 40.9 191 3700 female 2008
78 37.2 184 3900 male 2008
79 36.2 187 3550 female 2008
80 42.1 195 4000 male 2008
81 34.6 189 3200 female 2008
82 42.9 196 4700 male 2008
83 36.7 187 3800 female 2008
84 35.1 193 4200 male 2008
85 37.3 191 3350 female 2008
86 41.3 194 3550 male 2008
87 36.3 190 3800 male 2008
88 36.9 189 3500 female 2008
89 38.3 189 3950 male 2008
90 38.9 190 3600 female 2008
91 35.7 202 3550 female 2008
92 41.1 205 4300 male 2008
93 34.0 185 3400 female 2008
94 39.6 186 4450 male 2008
95 36.2 187 3300 female 2008
96 40.8 208 4300 male 2008
97 38.1 190 3700 female 2008
98 40.3 196 4350 male 2008
99 33.1 178 2900 female 2008
100 43.2 192 4100 male 2008
101 35.0 192 3725 female 2009
102 41.0 203 4725 male 2009
103 37.7 183 3075 female 2009
104 37.8 190 4250 male 2009
105 37.9 193 2925 female 2009
106 39.7 184 3550 male 2009
107 38.6 199 3750 female 2009
108 38.2 190 3900 male 2009
109 38.1 181 3175 female 2009
110 43.2 197 4775 male 2009
111 38.1 198 3825 female 2009
112 45.6 191 4600 male 2009
113 39.7 193 3200 female 2009
114 42.2 197 4275 male 2009
115 39.6 191 3900 female 2009
116 42.7 196 4075 male 2009
117 38.6 188 2900 female 2009
118 37.3 199 3775 male 2009
119 35.7 189 3350 female 2009
120 41.1 189 3325 male 2009
121 36.2 187 3150 female 2009
122 37.7 198 3500 male 2009
123 40.2 176 3450 female 2009
124 41.4 202 3875 male 2009
125 35.2 186 3050 female 2009
126 40.6 199 4000 male 2009
127 38.8 191 3275 female 2009
128 41.5 195 4300 male 2009
129 39.0 191 3050 female 2009
130 44.1 210 4000 male 2009
131 38.5 190 3325 female 2009
132 43.1 197 3500 male 2009
133 36.8 193 3500 female 2009
134 37.5 199 4475 male 2009
135 38.1 187 3425 female 2009
136 41.1 190 3900 male 2009
137 35.6 191 3175 female 2009
138 40.2 200 3975 male 2009
139 37.0 185 3400 female 2009
140 39.7 193 4250 male 2009
141 40.2 193 3400 female 2009
142 40.6 187 3475 male 2009
143 32.1 188 3050 female 2009
144 40.7 190 3725 male 2009
145 37.3 192 3000 female 2009
146 39.0 185 3650 male 2009
147 39.2 190 4250 male 2009
148 36.6 184 3475 female 2009
149 36.0 195 3450 female 2009
150 37.8 193 3750 male 2009
151 36.0 187 3700 female 2009
152 41.5 201 4000 male 2009
153 46.1 211 4500 female 2007
154 50.0 230 5700 male 2007
155 48.7 210 4450 female 2007
156 50.0 218 5700 male 2007
157 47.6 215 5400 male 2007
158 46.5 210 4550 female 2007
159 45.4 211 4800 female 2007
160 46.7 219 5200 male 2007
161 43.3 209 4400 female 2007
162 46.8 215 5150 male 2007
163 40.9 214 4650 female 2007
164 49.0 216 5550 male 2007
165 45.5 214 4650 female 2007
166 48.4 213 5850 male 2007
167 45.8 210 4200 female 2007
168 49.3 217 5850 male 2007
169 42.0 210 4150 female 2007
170 49.2 221 6300 male 2007
171 46.2 209 4800 female 2007
172 48.7 222 5350 male 2007
173 50.2 218 5700 male 2007
174 45.1 215 5000 female 2007
175 46.5 213 4400 female 2007
176 46.3 215 5050 male 2007
177 42.9 215 5000 female 2007
178 46.1 215 5100 male 2007
179 44.5 216 4100 <NA> 2007
180 47.8 215 5650 male 2007
181 48.2 210 4600 female 2007
182 50.0 220 5550 male 2007
183 47.3 222 5250 male 2007
184 42.8 209 4700 female 2007
185 45.1 207 5050 female 2007
186 59.6 230 6050 male 2007
187 49.1 220 5150 female 2008
188 48.4 220 5400 male 2008
189 42.6 213 4950 female 2008
190 44.4 219 5250 male 2008
191 44.0 208 4350 female 2008
192 48.7 208 5350 male 2008
193 42.7 208 3950 female 2008
194 49.6 225 5700 male 2008
195 45.3 210 4300 female 2008
196 49.6 216 4750 male 2008
197 50.5 222 5550 male 2008
198 43.6 217 4900 female 2008
199 45.5 210 4200 female 2008
200 50.5 225 5400 male 2008
201 44.9 213 5100 female 2008
202 45.2 215 5300 male 2008
203 46.6 210 4850 female 2008
204 48.5 220 5300 male 2008
205 45.1 210 4400 female 2008
206 50.1 225 5000 male 2008
207 46.5 217 4900 female 2008
208 45.0 220 5050 male 2008
209 43.8 208 4300 female 2008
210 45.5 220 5000 male 2008
211 43.2 208 4450 female 2008
212 50.4 224 5550 male 2008
213 45.3 208 4200 female 2008
214 46.2 221 5300 male 2008
215 45.7 214 4400 female 2008
216 54.3 231 5650 male 2008
217 45.8 219 4700 female 2008
218 49.8 230 5700 male 2008
219 46.2 214 4650 <NA> 2008
220 49.5 229 5800 male 2008
221 43.5 220 4700 female 2008
222 50.7 223 5550 male 2008
223 47.7 216 4750 female 2008
224 46.4 221 5000 male 2008
225 48.2 221 5100 male 2008
226 46.5 217 5200 female 2008
227 46.4 216 4700 female 2008
228 48.6 230 5800 male 2008
229 47.5 209 4600 female 2008
230 51.1 220 6000 male 2008
231 45.2 215 4750 female 2008
232 45.2 223 5950 male 2008
233 49.1 212 4625 female 2009
234 52.5 221 5450 male 2009
235 47.4 212 4725 female 2009
236 50.0 224 5350 male 2009
237 44.9 212 4750 female 2009
238 50.8 228 5600 male 2009
239 43.4 218 4600 female 2009
240 51.3 218 5300 male 2009
241 47.5 212 4875 female 2009
242 52.1 230 5550 male 2009
243 47.5 218 4950 female 2009
244 52.2 228 5400 male 2009
245 45.5 212 4750 female 2009
246 49.5 224 5650 male 2009
247 44.5 214 4850 female 2009
248 50.8 226 5200 male 2009
249 49.4 216 4925 male 2009
250 46.9 222 4875 female 2009
251 48.4 203 4625 female 2009
252 51.1 225 5250 male 2009
253 48.5 219 4850 female 2009
254 55.9 228 5600 male 2009
255 47.2 215 4975 female 2009
256 49.1 228 5500 male 2009
257 47.3 216 4725 <NA> 2009
258 46.8 215 5500 male 2009
259 41.7 210 4700 female 2009
260 53.4 219 5500 male 2009
261 43.3 208 4575 female 2009
262 48.1 209 5500 male 2009
263 50.5 216 5000 female 2009
264 49.8 229 5950 male 2009
265 43.5 213 4650 female 2009
266 51.5 230 5500 male 2009
267 46.2 217 4375 female 2009
268 55.1 230 5850 male 2009
269 44.5 217 4875 <NA> 2009
270 48.8 222 6000 male 2009
271 47.2 214 4925 female 2009
272 NA NA NA <NA> 2009
273 46.8 215 4850 female 2009
274 50.4 222 5750 male 2009
275 45.2 212 5200 female 2009
276 49.9 213 5400 male 2009
277 46.5 192 3500 female 2007
278 50.0 196 3900 male 2007
279 51.3 193 3650 male 2007
280 45.4 188 3525 female 2007
281 52.7 197 3725 male 2007
282 45.2 198 3950 female 2007
283 46.1 178 3250 female 2007
284 51.3 197 3750 male 2007
285 46.0 195 4150 female 2007
286 51.3 198 3700 male 2007
287 46.6 193 3800 female 2007
288 51.7 194 3775 male 2007
289 47.0 185 3700 female 2007
290 52.0 201 4050 male 2007
291 45.9 190 3575 female 2007
292 50.5 201 4050 male 2007
293 50.3 197 3300 male 2007
294 58.0 181 3700 female 2007
295 46.4 190 3450 female 2007
296 49.2 195 4400 male 2007
297 42.4 181 3600 female 2007
298 48.5 191 3400 male 2007
299 43.2 187 2900 female 2007
300 50.6 193 3800 male 2007
301 46.7 195 3300 female 2007
302 52.0 197 4150 male 2007
303 50.5 200 3400 female 2008
304 49.5 200 3800 male 2008
305 46.4 191 3700 female 2008
306 52.8 205 4550 male 2008
307 40.9 187 3200 female 2008
308 54.2 201 4300 male 2008
309 42.5 187 3350 female 2008
310 51.0 203 4100 male 2008
311 49.7 195 3600 male 2008
312 47.5 199 3900 female 2008
313 47.6 195 3850 female 2008
314 52.0 210 4800 male 2008
315 46.9 192 2700 female 2008
316 53.5 205 4500 male 2008
317 49.0 210 3950 male 2008
318 46.2 187 3650 female 2008
319 50.9 196 3550 male 2008
320 45.5 196 3500 female 2008
321 50.9 196 3675 female 2009
322 50.8 201 4450 male 2009
323 50.1 190 3400 female 2009
324 49.0 212 4300 male 2009
325 51.5 187 3250 male 2009
326 49.8 198 3675 female 2009
327 48.1 199 3325 female 2009
328 51.4 201 3950 male 2009
329 45.7 193 3600 female 2009
330 50.7 203 4050 male 2009
331 42.5 187 3350 female 2009
332 52.2 197 3450 male 2009
333 45.2 191 3250 female 2009
334 49.3 203 4050 male 2009
335 50.2 202 3800 male 2009
336 45.6 194 3525 female 2009
337 51.9 206 3950 male 2009
338 46.8 189 3650 female 2009
339 45.7 195 3650 female 2009
340 55.8 207 4000 male 2009
341 43.5 202 3400 female 2009
342 49.6 193 3775 male 2009
343 50.8 210 4100 male 2009
344 50.2 198 3775 female 2009select and rename
You can but shouldn’t mix select and drop - results non-intuitive
species
1 Adelie
2 Adelie
3 Adelie
4 Adelie
5 Adelie
6 Adelie
7 Adelie
8 Adelie
9 Adelie
10 Adelie
11 Adelie
12 Adelie
13 Adelie
14 Adelie
15 Adelie
16 Adelie
17 Adelie
18 Adelie
19 Adelie
20 Adelie
21 Adelie
22 Adelie
23 Adelie
24 Adelie
25 Adelie
26 Adelie
27 Adelie
28 Adelie
29 Adelie
30 Adelie
31 Adelie
32 Adelie
33 Adelie
34 Adelie
35 Adelie
36 Adelie
37 Adelie
38 Adelie
39 Adelie
40 Adelie
41 Adelie
42 Adelie
43 Adelie
44 Adelie
45 Adelie
46 Adelie
47 Adelie
48 Adelie
49 Adelie
50 Adelie
51 Adelie
52 Adelie
53 Adelie
54 Adelie
55 Adelie
56 Adelie
57 Adelie
58 Adelie
59 Adelie
60 Adelie
61 Adelie
62 Adelie
63 Adelie
64 Adelie
65 Adelie
66 Adelie
67 Adelie
68 Adelie
69 Adelie
70 Adelie
71 Adelie
72 Adelie
73 Adelie
74 Adelie
75 Adelie
76 Adelie
77 Adelie
78 Adelie
79 Adelie
80 Adelie
81 Adelie
82 Adelie
83 Adelie
84 Adelie
85 Adelie
86 Adelie
87 Adelie
88 Adelie
89 Adelie
90 Adelie
91 Adelie
92 Adelie
93 Adelie
94 Adelie
95 Adelie
96 Adelie
97 Adelie
98 Adelie
99 Adelie
100 Adelie
101 Adelie
102 Adelie
103 Adelie
104 Adelie
105 Adelie
106 Adelie
107 Adelie
108 Adelie
109 Adelie
110 Adelie
111 Adelie
112 Adelie
113 Adelie
114 Adelie
115 Adelie
116 Adelie
117 Adelie
118 Adelie
119 Adelie
120 Adelie
121 Adelie
122 Adelie
123 Adelie
124 Adelie
125 Adelie
126 Adelie
127 Adelie
128 Adelie
129 Adelie
130 Adelie
131 Adelie
132 Adelie
133 Adelie
134 Adelie
135 Adelie
136 Adelie
137 Adelie
138 Adelie
139 Adelie
140 Adelie
141 Adelie
142 Adelie
143 Adelie
144 Adelie
145 Adelie
146 Adelie
147 Adelie
148 Adelie
149 Adelie
150 Adelie
151 Adelie
152 Adelie
153 Gentoo
154 Gentoo
155 Gentoo
156 Gentoo
157 Gentoo
158 Gentoo
159 Gentoo
160 Gentoo
161 Gentoo
162 Gentoo
163 Gentoo
164 Gentoo
165 Gentoo
166 Gentoo
167 Gentoo
168 Gentoo
169 Gentoo
170 Gentoo
171 Gentoo
172 Gentoo
173 Gentoo
174 Gentoo
175 Gentoo
176 Gentoo
177 Gentoo
178 Gentoo
179 Gentoo
180 Gentoo
181 Gentoo
182 Gentoo
183 Gentoo
184 Gentoo
185 Gentoo
186 Gentoo
187 Gentoo
188 Gentoo
189 Gentoo
190 Gentoo
191 Gentoo
192 Gentoo
193 Gentoo
194 Gentoo
195 Gentoo
196 Gentoo
197 Gentoo
198 Gentoo
199 Gentoo
200 Gentoo
201 Gentoo
202 Gentoo
203 Gentoo
204 Gentoo
205 Gentoo
206 Gentoo
207 Gentoo
208 Gentoo
209 Gentoo
210 Gentoo
211 Gentoo
212 Gentoo
213 Gentoo
214 Gentoo
215 Gentoo
216 Gentoo
217 Gentoo
218 Gentoo
219 Gentoo
220 Gentoo
221 Gentoo
222 Gentoo
223 Gentoo
224 Gentoo
225 Gentoo
226 Gentoo
227 Gentoo
228 Gentoo
229 Gentoo
230 Gentoo
231 Gentoo
232 Gentoo
233 Gentoo
234 Gentoo
235 Gentoo
236 Gentoo
237 Gentoo
238 Gentoo
239 Gentoo
240 Gentoo
241 Gentoo
242 Gentoo
243 Gentoo
244 Gentoo
245 Gentoo
246 Gentoo
247 Gentoo
248 Gentoo
249 Gentoo
250 Gentoo
251 Gentoo
252 Gentoo
253 Gentoo
254 Gentoo
255 Gentoo
256 Gentoo
257 Gentoo
258 Gentoo
259 Gentoo
260 Gentoo
261 Gentoo
262 Gentoo
263 Gentoo
264 Gentoo
265 Gentoo
266 Gentoo
267 Gentoo
268 Gentoo
269 Gentoo
270 Gentoo
271 Gentoo
272 Gentoo
273 Gentoo
274 Gentoo
275 Gentoo
276 Gentoo
277 Chinstrap
278 Chinstrap
279 Chinstrap
280 Chinstrap
281 Chinstrap
282 Chinstrap
283 Chinstrap
284 Chinstrap
285 Chinstrap
286 Chinstrap
287 Chinstrap
288 Chinstrap
289 Chinstrap
290 Chinstrap
291 Chinstrap
292 Chinstrap
293 Chinstrap
294 Chinstrap
295 Chinstrap
296 Chinstrap
297 Chinstrap
298 Chinstrap
299 Chinstrap
300 Chinstrap
301 Chinstrap
302 Chinstrap
303 Chinstrap
304 Chinstrap
305 Chinstrap
306 Chinstrap
307 Chinstrap
308 Chinstrap
309 Chinstrap
310 Chinstrap
311 Chinstrap
312 Chinstrap
313 Chinstrap
314 Chinstrap
315 Chinstrap
316 Chinstrap
317 Chinstrap
318 Chinstrap
319 Chinstrap
320 Chinstrap
321 Chinstrap
322 Chinstrap
323 Chinstrap
324 Chinstrap
325 Chinstrap
326 Chinstrap
327 Chinstrap
328 Chinstrap
329 Chinstrap
330 Chinstrap
331 Chinstrap
332 Chinstrap
333 Chinstrap
334 Chinstrap
335 Chinstrap
336 Chinstrap
337 Chinstrap
338 Chinstrap
339 Chinstrap
340 Chinstrap
341 Chinstrap
342 Chinstrap
343 Chinstrap
344 Chinstrapselect and rename
To avoid printing too much, let’s take a smaller subset of rows:
tidyselect
dplyr has many more selection functions for getting groups of related columns
See tidyselect for details
Creating Columns
The mutate command can be used to create new columns from old:
Named Arguments
mutate (and later summarize) create new columns:
mutatecreates “one-to-one”summarizecreates “one-per-group”
If you want to name them (so you can use them later), use named argument
Named Arguments
Default name is tricky to use:
species island bill_len bill_dep flipper_len body_mass year n()
1 Adelie Torgersen 39.1 18.7 181 3750 2007 5
2 Adelie Torgersen 39.5 17.4 186 3800 2007 5
3 Adelie Torgersen 40.3 18.0 195 3250 2007 5
4 Adelie Torgersen NA NA NA NA 2007 5
5 Adelie Torgersen 36.7 19.3 193 3450 2007 5vs
species island bill_len bill_dep flipper_len body_mass year n_penguins
1 Adelie Torgersen 39.1 18.7 181 3750 2007 5
2 Adelie Torgersen 39.5 17.4 186 3800 2007 5
3 Adelie Torgersen 40.3 18.0 195 3250 2007 5
4 Adelie Torgersen NA NA NA NA 2007 5
5 Adelie Torgersen 36.7 19.3 193 3450 2007 5Provide a “valid” variable name for easiest use (alphanumeric, no punctuation other than _, starts with a letter)
mutate
Can create and use variables in order with mutate:
five_penguins |>
select(body_mass, flipper_len, sex) |>
mutate(body_mass_kg = body_mass / 1000,
flipper_len_m = flipper_len / 1000,
penguin_bmi = body_mass_kg / flipper_len_m^2) body_mass flipper_len sex body_mass_kg flipper_len_m penguin_bmi
1 3750 181 male 3.75 0.181 114.46537
2 3800 186 female 3.80 0.186 109.83929
3 3250 195 female 3.25 0.195 85.47009
4 NA NA <NA> NA NA NA
5 3450 193 female 3.45 0.193 92.61994BMI probably isn’t accurate for penguins
mutate
Image from jgoode.com
mutate
Variables are created in order (top to bottom) - this fails:
five_penguins |>
select(body_mass, flipper_len, sex) |>
mutate(penguin_bmi = body_mass_kg / flipper_len_m^2,
body_mass_kg = body_mass / 1000,
flipper_len_m = flipper_len / 1000)Error in `mutate()`:
ℹ In argument: `penguin_bmi = body_mass_kg/flipper_len_m^2`.
Caused by error:
! object 'body_mass_kg' not foundmutate helpers
Helper functions for working with complex mutate commands:
five_penguins |>
select(body_mass, flipper_len, sex) |>
mutate(body_mass_kg = body_mass / 1000,
flipper_len_m = flipper_len / 1000,
penguin_bmi = body_mass_kg / flipper_len_m^2,
is_husky = if_else(penguin_bmi > 120, TRUE, FALSE)) body_mass flipper_len sex body_mass_kg flipper_len_m penguin_bmi is_husky
1 3750 181 male 3.75 0.181 114.46537 FALSE
2 3800 186 female 3.80 0.186 109.83929 FALSE
3 3250 195 female 3.25 0.195 85.47009 FALSE
4 NA NA <NA> NA NA NA NA
5 3450 193 female 3.45 0.193 92.61994 FALSEVectorized analogue of the if/else conditional construct
mutate helpers
case_when for multiple conditions:
five_penguins |> select(body_mass, flipper_len, sex) |>
mutate(body_mass_kg = body_mass / 1000,
flipper_len_m = flipper_len / 1000,
penguin_bmi = body_mass_kg / flipper_len_m^2,
is_big_guy = case_when(
sex == "female" ~ FALSE,
penguin_bmi < 120 ~ FALSE,
.default = TRUE)) body_mass flipper_len sex body_mass_kg flipper_len_m penguin_bmi
1 3750 181 male 3.75 0.181 114.46537
2 3800 186 female 3.80 0.186 109.83929
3 3250 195 female 3.25 0.195 85.47009
4 NA NA <NA> NA NA NA
5 3450 193 female 3.45 0.193 92.61994
is_big_guy
1 FALSE
2 FALSE
3 FALSE
4 TRUE
5 FALSEDefines a sequence of tests: first to pass takes value from RHS of ~
mutate helpers
More advanced helpers for recoding and replacing in dplyr v1.2 (February 2026)
case_whenreplace_whenrecode_valuesreplace_valuesSee announcement for more details
filter Operations
While select is used to isolate columns, filter is used to isolate rows:
species island bill_len bill_dep flipper_len body_mass sex year
1 Adelie Torgersen 39.1 18.7 181 3750 male 2007
2 Adelie Torgersen 39.5 17.4 186 3800 female 2007
3 Adelie Torgersen 40.3 18.0 195 3250 female 2007
4 Adelie Torgersen NA NA NA NA <NA> 2007
5 Adelie Torgersen 36.7 19.3 193 3450 female 2007
6 Adelie Torgersen 39.3 20.6 190 3650 male 2007
7 Adelie Torgersen 38.9 17.8 181 3625 female 2007
8 Adelie Torgersen 39.2 19.6 195 4675 male 2007
9 Adelie Torgersen 34.1 18.1 193 3475 <NA> 2007
10 Adelie Torgersen 42.0 20.2 190 4250 <NA> 2007
11 Adelie Torgersen 37.8 17.1 186 3300 <NA> 2007
12 Adelie Torgersen 37.8 17.3 180 3700 <NA> 2007
13 Adelie Torgersen 41.1 17.6 182 3200 female 2007
14 Adelie Torgersen 38.6 21.2 191 3800 male 2007
15 Adelie Torgersen 34.6 21.1 198 4400 male 2007
16 Adelie Torgersen 36.6 17.8 185 3700 female 2007
17 Adelie Torgersen 38.7 19.0 195 3450 female 2007
18 Adelie Torgersen 42.5 20.7 197 4500 male 2007
19 Adelie Torgersen 34.4 18.4 184 3325 female 2007
20 Adelie Torgersen 46.0 21.5 194 4200 male 2007
21 Adelie Biscoe 37.8 18.3 174 3400 female 2007
22 Adelie Biscoe 37.7 18.7 180 3600 male 2007
23 Adelie Biscoe 35.9 19.2 189 3800 female 2007
24 Adelie Biscoe 38.2 18.1 185 3950 male 2007
25 Adelie Biscoe 38.8 17.2 180 3800 male 2007
26 Adelie Biscoe 35.3 18.9 187 3800 female 2007
27 Adelie Biscoe 40.6 18.6 183 3550 male 2007
28 Adelie Biscoe 40.5 17.9 187 3200 female 2007
29 Adelie Biscoe 37.9 18.6 172 3150 female 2007
30 Adelie Biscoe 40.5 18.9 180 3950 male 2007
31 Adelie Dream 39.5 16.7 178 3250 female 2007
32 Adelie Dream 37.2 18.1 178 3900 male 2007
33 Adelie Dream 39.5 17.8 188 3300 female 2007
34 Adelie Dream 40.9 18.9 184 3900 male 2007
35 Adelie Dream 36.4 17.0 195 3325 female 2007
36 Adelie Dream 39.2 21.1 196 4150 male 2007
37 Adelie Dream 38.8 20.0 190 3950 male 2007
38 Adelie Dream 42.2 18.5 180 3550 female 2007
39 Adelie Dream 37.6 19.3 181 3300 female 2007
40 Adelie Dream 39.8 19.1 184 4650 male 2007
41 Adelie Dream 36.5 18.0 182 3150 female 2007
42 Adelie Dream 40.8 18.4 195 3900 male 2007
43 Adelie Dream 36.0 18.5 186 3100 female 2007
44 Adelie Dream 44.1 19.7 196 4400 male 2007
45 Adelie Dream 37.0 16.9 185 3000 female 2007
46 Adelie Dream 39.6 18.8 190 4600 male 2007
47 Adelie Dream 41.1 19.0 182 3425 male 2007
48 Adelie Dream 37.5 18.9 179 2975 <NA> 2007
49 Adelie Dream 36.0 17.9 190 3450 female 2007
50 Adelie Dream 42.3 21.2 191 4150 male 2007
51 Adelie Biscoe 39.6 17.7 186 3500 female 2008
52 Adelie Biscoe 40.1 18.9 188 4300 male 2008
53 Adelie Biscoe 35.0 17.9 190 3450 female 2008
54 Adelie Biscoe 42.0 19.5 200 4050 male 2008
55 Adelie Biscoe 34.5 18.1 187 2900 female 2008
56 Adelie Biscoe 41.4 18.6 191 3700 male 2008
57 Adelie Biscoe 39.0 17.5 186 3550 female 2008
58 Adelie Biscoe 40.6 18.8 193 3800 male 2008
59 Adelie Biscoe 36.5 16.6 181 2850 female 2008
60 Adelie Biscoe 37.6 19.1 194 3750 male 2008
61 Adelie Biscoe 35.7 16.9 185 3150 female 2008
62 Adelie Biscoe 41.3 21.1 195 4400 male 2008
63 Adelie Biscoe 37.6 17.0 185 3600 female 2008
64 Adelie Biscoe 41.1 18.2 192 4050 male 2008
65 Adelie Biscoe 36.4 17.1 184 2850 female 2008
66 Adelie Biscoe 41.6 18.0 192 3950 male 2008
67 Adelie Biscoe 35.5 16.2 195 3350 female 2008
68 Adelie Biscoe 41.1 19.1 188 4100 male 2008
69 Adelie Torgersen 35.9 16.6 190 3050 female 2008
70 Adelie Torgersen 41.8 19.4 198 4450 male 2008
71 Adelie Torgersen 33.5 19.0 190 3600 female 2008
72 Adelie Torgersen 39.7 18.4 190 3900 male 2008
73 Adelie Torgersen 39.6 17.2 196 3550 female 2008
74 Adelie Torgersen 45.8 18.9 197 4150 male 2008
75 Adelie Torgersen 35.5 17.5 190 3700 female 2008
76 Adelie Torgersen 42.8 18.5 195 4250 male 2008
77 Adelie Torgersen 40.9 16.8 191 3700 female 2008
78 Adelie Torgersen 37.2 19.4 184 3900 male 2008
79 Adelie Torgersen 36.2 16.1 187 3550 female 2008
80 Adelie Torgersen 42.1 19.1 195 4000 male 2008
81 Adelie Torgersen 34.6 17.2 189 3200 female 2008
82 Adelie Torgersen 42.9 17.6 196 4700 male 2008
83 Adelie Torgersen 36.7 18.8 187 3800 female 2008
84 Adelie Torgersen 35.1 19.4 193 4200 male 2008
85 Adelie Dream 37.3 17.8 191 3350 female 2008
86 Adelie Dream 41.3 20.3 194 3550 male 2008
87 Adelie Dream 36.3 19.5 190 3800 male 2008
88 Adelie Dream 36.9 18.6 189 3500 female 2008
89 Adelie Dream 38.3 19.2 189 3950 male 2008
90 Adelie Dream 38.9 18.8 190 3600 female 2008
91 Adelie Dream 35.7 18.0 202 3550 female 2008
92 Adelie Dream 41.1 18.1 205 4300 male 2008
93 Adelie Dream 34.0 17.1 185 3400 female 2008
94 Adelie Dream 39.6 18.1 186 4450 male 2008
95 Adelie Dream 36.2 17.3 187 3300 female 2008
96 Adelie Dream 40.8 18.9 208 4300 male 2008
97 Adelie Dream 38.1 18.6 190 3700 female 2008
98 Adelie Dream 40.3 18.5 196 4350 male 2008
99 Adelie Dream 33.1 16.1 178 2900 female 2008
100 Adelie Dream 43.2 18.5 192 4100 male 2008
101 Adelie Biscoe 35.0 17.9 192 3725 female 2009
102 Adelie Biscoe 41.0 20.0 203 4725 male 2009
103 Adelie Biscoe 37.7 16.0 183 3075 female 2009
104 Adelie Biscoe 37.8 20.0 190 4250 male 2009
105 Adelie Biscoe 37.9 18.6 193 2925 female 2009
106 Adelie Biscoe 39.7 18.9 184 3550 male 2009
107 Adelie Biscoe 38.6 17.2 199 3750 female 2009
108 Adelie Biscoe 38.2 20.0 190 3900 male 2009
109 Adelie Biscoe 38.1 17.0 181 3175 female 2009
110 Adelie Biscoe 43.2 19.0 197 4775 male 2009
111 Adelie Biscoe 38.1 16.5 198 3825 female 2009
112 Adelie Biscoe 45.6 20.3 191 4600 male 2009
113 Adelie Biscoe 39.7 17.7 193 3200 female 2009
114 Adelie Biscoe 42.2 19.5 197 4275 male 2009
115 Adelie Biscoe 39.6 20.7 191 3900 female 2009
116 Adelie Biscoe 42.7 18.3 196 4075 male 2009
117 Adelie Torgersen 38.6 17.0 188 2900 female 2009
118 Adelie Torgersen 37.3 20.5 199 3775 male 2009
119 Adelie Torgersen 35.7 17.0 189 3350 female 2009
120 Adelie Torgersen 41.1 18.6 189 3325 male 2009
121 Adelie Torgersen 36.2 17.2 187 3150 female 2009
122 Adelie Torgersen 37.7 19.8 198 3500 male 2009
123 Adelie Torgersen 40.2 17.0 176 3450 female 2009
124 Adelie Torgersen 41.4 18.5 202 3875 male 2009
125 Adelie Torgersen 35.2 15.9 186 3050 female 2009
126 Adelie Torgersen 40.6 19.0 199 4000 male 2009
127 Adelie Torgersen 38.8 17.6 191 3275 female 2009
128 Adelie Torgersen 41.5 18.3 195 4300 male 2009
129 Adelie Torgersen 39.0 17.1 191 3050 female 2009
130 Adelie Torgersen 44.1 18.0 210 4000 male 2009
131 Adelie Torgersen 38.5 17.9 190 3325 female 2009
132 Adelie Torgersen 43.1 19.2 197 3500 male 2009
133 Adelie Dream 36.8 18.5 193 3500 female 2009
134 Adelie Dream 37.5 18.5 199 4475 male 2009
135 Adelie Dream 38.1 17.6 187 3425 female 2009
136 Adelie Dream 41.1 17.5 190 3900 male 2009
137 Adelie Dream 35.6 17.5 191 3175 female 2009
138 Adelie Dream 40.2 20.1 200 3975 male 2009
139 Adelie Dream 37.0 16.5 185 3400 female 2009
140 Adelie Dream 39.7 17.9 193 4250 male 2009
141 Adelie Dream 40.2 17.1 193 3400 female 2009
142 Adelie Dream 40.6 17.2 187 3475 male 2009
143 Adelie Dream 32.1 15.5 188 3050 female 2009
144 Adelie Dream 40.7 17.0 190 3725 male 2009
145 Adelie Dream 37.3 16.8 192 3000 female 2009
146 Adelie Dream 39.0 18.7 185 3650 male 2009
147 Adelie Dream 39.2 18.6 190 4250 male 2009
148 Adelie Dream 36.6 18.4 184 3475 female 2009
149 Adelie Dream 36.0 17.8 195 3450 female 2009
150 Adelie Dream 37.8 18.1 193 3750 male 2009
151 Adelie Dream 36.0 17.1 187 3700 female 2009
152 Adelie Dream 41.5 18.5 201 4000 male 2009filter Operations
Pass multiple arguments to get the intersection
species island bill_len bill_dep flipper_len body_mass sex year
1 Adelie Biscoe 37.8 18.3 174 3400 female 2007
2 Adelie Biscoe 37.7 18.7 180 3600 male 2007
3 Adelie Biscoe 35.9 19.2 189 3800 female 2007
4 Adelie Biscoe 38.2 18.1 185 3950 male 2007
5 Adelie Biscoe 38.8 17.2 180 3800 male 2007
6 Adelie Biscoe 35.3 18.9 187 3800 female 2007
7 Adelie Biscoe 40.6 18.6 183 3550 male 2007
8 Adelie Biscoe 40.5 17.9 187 3200 female 2007
9 Adelie Biscoe 37.9 18.6 172 3150 female 2007
10 Adelie Biscoe 40.5 18.9 180 3950 male 2007
11 Adelie Biscoe 39.6 17.7 186 3500 female 2008
12 Adelie Biscoe 40.1 18.9 188 4300 male 2008
13 Adelie Biscoe 35.0 17.9 190 3450 female 2008
14 Adelie Biscoe 42.0 19.5 200 4050 male 2008
15 Adelie Biscoe 34.5 18.1 187 2900 female 2008
16 Adelie Biscoe 41.4 18.6 191 3700 male 2008
17 Adelie Biscoe 39.0 17.5 186 3550 female 2008
18 Adelie Biscoe 40.6 18.8 193 3800 male 2008
19 Adelie Biscoe 36.5 16.6 181 2850 female 2008
20 Adelie Biscoe 37.6 19.1 194 3750 male 2008
21 Adelie Biscoe 35.7 16.9 185 3150 female 2008
22 Adelie Biscoe 41.3 21.1 195 4400 male 2008
23 Adelie Biscoe 37.6 17.0 185 3600 female 2008
24 Adelie Biscoe 41.1 18.2 192 4050 male 2008
25 Adelie Biscoe 36.4 17.1 184 2850 female 2008
26 Adelie Biscoe 41.6 18.0 192 3950 male 2008
27 Adelie Biscoe 35.5 16.2 195 3350 female 2008
28 Adelie Biscoe 41.1 19.1 188 4100 male 2008
29 Adelie Biscoe 35.0 17.9 192 3725 female 2009
30 Adelie Biscoe 41.0 20.0 203 4725 male 2009
31 Adelie Biscoe 37.7 16.0 183 3075 female 2009
32 Adelie Biscoe 37.8 20.0 190 4250 male 2009
33 Adelie Biscoe 37.9 18.6 193 2925 female 2009
34 Adelie Biscoe 39.7 18.9 184 3550 male 2009
35 Adelie Biscoe 38.6 17.2 199 3750 female 2009
36 Adelie Biscoe 38.2 20.0 190 3900 male 2009
37 Adelie Biscoe 38.1 17.0 181 3175 female 2009
38 Adelie Biscoe 43.2 19.0 197 4775 male 2009
39 Adelie Biscoe 38.1 16.5 198 3825 female 2009
40 Adelie Biscoe 45.6 20.3 191 4600 male 2009
41 Adelie Biscoe 39.7 17.7 193 3200 female 2009
42 Adelie Biscoe 42.2 19.5 197 4275 male 2009
43 Adelie Biscoe 39.6 20.7 191 3900 female 2009
44 Adelie Biscoe 42.7 18.3 196 4075 male 2009filter Operations
Can compute quantities inside of filter
To select heavier than average penguins:
species island bill_len bill_dep flipper_len body_mass sex year
1 Adelie Torgersen 39.1 18.7 181 3750 male 2007
2 Adelie Torgersen 39.5 17.4 186 3800 female 2007Reminder: Why do we need na.rm=TRUE?
slice_min and slice_max
The slice_min and slice_max functions replace and extend the common filter(x == max(x)) idiom:
slice_min and slice_max
Arguments:
n: How many rows to return (top/bottom \(k\))prop: Percent of rows to return
E.g., 10% lightest
species island bill_len bill_dep flipper_len body_mass sex year
1 Chinstrap Dream 46.9 16.6 192 2700 female 2008
2 Adelie Biscoe 36.5 16.6 181 2850 female 2008
3 Adelie Biscoe 36.4 17.1 184 2850 female 2008
4 Adelie Biscoe 34.5 18.1 187 2900 female 2008
5 Adelie Dream 33.1 16.1 178 2900 female 2008
6 Adelie Torgersen 38.6 17.0 188 2900 female 2009
7 Chinstrap Dream 43.2 16.6 187 2900 female 2007
8 Adelie Biscoe 37.9 18.6 193 2925 female 2009
9 Adelie Dream 37.5 18.9 179 2975 <NA> 2007
10 Adelie Dream 37.0 16.9 185 3000 female 2007
11 Adelie Dream 37.3 16.8 192 3000 female 2009
12 Adelie Torgersen 35.9 16.6 190 3050 female 2008
13 Adelie Torgersen 35.2 15.9 186 3050 female 2009
14 Adelie Torgersen 39.0 17.1 191 3050 female 2009
15 Adelie Dream 32.1 15.5 188 3050 female 2009
16 Adelie Biscoe 37.7 16.0 183 3075 female 2009
17 Adelie Dream 36.0 18.5 186 3100 female 2007
18 Adelie Biscoe 37.9 18.6 172 3150 female 2007
19 Adelie Dream 36.5 18.0 182 3150 female 2007
20 Adelie Biscoe 35.7 16.9 185 3150 female 2008
21 Adelie Torgersen 36.2 17.2 187 3150 female 2009
22 Adelie Biscoe 38.1 17.0 181 3175 female 2009
23 Adelie Dream 35.6 17.5 191 3175 female 2009
24 Adelie Torgersen 41.1 17.6 182 3200 female 2007
25 Adelie Biscoe 40.5 17.9 187 3200 female 2007
26 Adelie Torgersen 34.6 17.2 189 3200 female 2008
27 Adelie Biscoe 39.7 17.7 193 3200 female 2009
28 Chinstrap Dream 40.9 16.6 187 3200 female 2008
29 Adelie Torgersen 40.3 18.0 195 3250 female 2007
30 Adelie Dream 39.5 16.7 178 3250 female 2007
31 Chinstrap Dream 46.1 18.2 178 3250 female 2007
32 Chinstrap Dream 51.5 18.7 187 3250 male 2009
33 Chinstrap Dream 45.2 16.6 191 3250 female 2009
34 Adelie Torgersen 38.8 17.6 191 3275 female 2009slice_sample
slice_sample generates a random subset:
- Useful for getting a smaller and faster “exploratory set”
species island bill_len bill_dep flipper_len body_mass sex year
1 Gentoo Biscoe 50.5 15.9 225 5400 male 2008
2 Adelie Dream 36.3 19.5 190 3800 male 2008
3 Adelie Dream 36.6 18.4 184 3475 female 2009
4 Gentoo Biscoe 45.4 14.6 211 4800 female 2007
5 Adelie Biscoe 41.1 18.2 192 4050 male 2008
6 Gentoo Biscoe 48.6 16.0 230 5800 male 2008
7 Gentoo Biscoe 43.8 13.9 208 4300 female 2008
8 Gentoo Biscoe 44.5 15.7 217 4875 <NA> 2009
9 Chinstrap Dream 46.1 18.2 178 3250 female 2007
10 Gentoo Biscoe 50.8 15.7 226 5200 male 2009
11 Chinstrap Dream 50.9 19.1 196 3550 male 2008
12 Chinstrap Dream 53.5 19.9 205 4500 male 2008
13 Gentoo Biscoe 46.6 14.2 210 4850 female 2008
14 Chinstrap Dream 45.4 18.7 188 3525 female 2007
15 Gentoo Biscoe 47.3 15.3 222 5250 male 2007
16 Gentoo Biscoe 50.4 15.7 222 5750 male 2009
17 Adelie Torgersen 36.2 16.1 187 3550 female 2008
18 Chinstrap Dream 51.7 20.3 194 3775 male 2007
19 Chinstrap Dream 45.2 17.8 198 3950 female 2007
20 Gentoo Biscoe 47.6 14.5 215 5400 male 2007
21 Adelie Dream 39.6 18.8 190 4600 male 2007
22 Adelie Biscoe 45.6 20.3 191 4600 male 2009
23 Gentoo Biscoe 46.1 15.1 215 5100 male 2007
24 Chinstrap Dream 46.5 17.9 192 3500 female 2007
25 Chinstrap Dream 46.4 17.8 191 3700 female 2008summarize Operations
The summarize function is used to combine rows:
- \(n\) rows down to 1
- Computes specified summary statistics
summarize Operations
Can provide multiple summaries - and even multiple summaries of the same column:
penguins |> summarize(avg_body_mass = mean(body_mass, na.rm=TRUE),
max_body_mass = max(body_mass, na.rm=TRUE),
min_body_mass = min(body_mass, na.rm=TRUE),
avg_flipper_len = mean(flipper_len, na.rm=TRUE),
max_flipper_len = max(flipper_len, na.rm=TRUE),
min_flipper_len = min(flipper_len, na.rm=TRUE)) avg_body_mass max_body_mass min_body_mass avg_flipper_len max_flipper_len
1 4201.754 6300 2700 200.9152 231
min_flipper_len
1 172Advanced: Use across to avoid this type of repetition
Counting Rows
Very common summarization: counting
tallyto get straight counts (equivalent to|> summarize(n = n()))add_tallyadds count column without summarizing (equivalent to|> mutate(n = n()))n_distinctto get number of unique values (equivalent to|> distinct() |> tally())
Counting Rows
Row count functions:
species island bill_len bill_dep flipper_len body_mass sex year n
1 Adelie Torgersen 39.1 18.7 181 3750 male 2007 5
2 Adelie Torgersen 39.5 17.4 186 3800 female 2007 5
3 Adelie Torgersen 40.3 18.0 195 3250 female 2007 5
4 Adelie Torgersen NA NA NA NA <NA> 2007 5
5 Adelie Torgersen 36.7 19.3 193 3450 female 2007 5Comparisons
Column Operations:
select: get a subset of existing columnsmutate: create new columns from old (keeps old)
Row Operations:
filter: get a subset of existing rowssummarize: create new rows from old (combines and discards)
Sorting
The arrange function will sort the rows without changing anything:
species island sex body_mass
1 Chinstrap Dream female 2700
2 Adelie Biscoe female 2850
3 Adelie Biscoe female 2850
4 Adelie Biscoe female 2900
5 Adelie Dream female 2900
6 Adelie Torgersen female 2900
7 Chinstrap Dream female 2900
8 Adelie Biscoe female 2925
9 Adelie Dream <NA> 2975
10 Adelie Dream female 3000
11 Adelie Dream female 3000
12 Adelie Torgersen female 3050
13 Adelie Torgersen female 3050
14 Adelie Torgersen female 3050
15 Adelie Dream female 3050
16 Adelie Biscoe female 3075
17 Adelie Dream female 3100
18 Adelie Biscoe female 3150
19 Adelie Dream female 3150
20 Adelie Biscoe female 3150
21 Adelie Torgersen female 3150
22 Adelie Biscoe female 3175
23 Adelie Dream female 3175
24 Adelie Torgersen female 3200
25 Adelie Biscoe female 3200
26 Adelie Torgersen female 3200
27 Adelie Biscoe female 3200
28 Chinstrap Dream female 3200
29 Adelie Torgersen female 3250
30 Adelie Dream female 3250
31 Chinstrap Dream female 3250
32 Chinstrap Dream male 3250
33 Chinstrap Dream female 3250
34 Adelie Torgersen female 3275
35 Adelie Torgersen <NA> 3300
36 Adelie Dream female 3300
37 Adelie Dream female 3300
38 Adelie Dream female 3300
39 Chinstrap Dream male 3300
40 Chinstrap Dream female 3300
41 Adelie Torgersen female 3325
42 Adelie Dream female 3325
43 Adelie Torgersen male 3325
44 Adelie Torgersen female 3325
45 Chinstrap Dream female 3325
46 Adelie Biscoe female 3350
47 Adelie Dream female 3350
48 Adelie Torgersen female 3350
49 Chinstrap Dream female 3350
50 Chinstrap Dream female 3350
51 Adelie Biscoe female 3400
52 Adelie Dream female 3400
53 Adelie Dream female 3400
54 Adelie Dream female 3400
55 Chinstrap Dream male 3400
56 Chinstrap Dream female 3400
57 Chinstrap Dream female 3400
58 Chinstrap Dream female 3400
59 Adelie Dream male 3425
60 Adelie Dream female 3425
61 Adelie Torgersen female 3450
62 Adelie Torgersen female 3450
63 Adelie Dream female 3450
64 Adelie Biscoe female 3450
65 Adelie Torgersen female 3450
66 Adelie Dream female 3450
67 Chinstrap Dream female 3450
68 Chinstrap Dream male 3450
69 Adelie Torgersen <NA> 3475
70 Adelie Dream male 3475
71 Adelie Dream female 3475
72 Adelie Biscoe female 3500
73 Adelie Dream female 3500
74 Adelie Torgersen male 3500
75 Adelie Torgersen male 3500
76 Adelie Dream female 3500
77 Chinstrap Dream female 3500
78 Chinstrap Dream female 3500
79 Chinstrap Dream female 3525
80 Chinstrap Dream female 3525
81 Adelie Biscoe male 3550
82 Adelie Dream female 3550
83 Adelie Biscoe female 3550
84 Adelie Torgersen female 3550
85 Adelie Torgersen female 3550
86 Adelie Dream male 3550
87 Adelie Dream female 3550
88 Adelie Biscoe male 3550
89 Chinstrap Dream male 3550
90 Chinstrap Dream female 3575
91 Adelie Biscoe male 3600
92 Adelie Biscoe female 3600
93 Adelie Torgersen female 3600
94 Adelie Dream female 3600
95 Chinstrap Dream female 3600
96 Chinstrap Dream male 3600
97 Chinstrap Dream female 3600
98 Adelie Torgersen female 3625
99 Adelie Torgersen male 3650
100 Adelie Dream male 3650
101 Chinstrap Dream male 3650
102 Chinstrap Dream female 3650
103 Chinstrap Dream female 3650
104 Chinstrap Dream female 3650
105 Chinstrap Dream female 3675
106 Chinstrap Dream female 3675
107 Adelie Torgersen <NA> 3700
108 Adelie Torgersen female 3700
109 Adelie Biscoe male 3700
110 Adelie Torgersen female 3700
111 Adelie Torgersen female 3700
112 Adelie Dream female 3700
113 Adelie Dream female 3700
114 Chinstrap Dream male 3700
115 Chinstrap Dream female 3700
116 Chinstrap Dream female 3700
117 Chinstrap Dream female 3700
118 Adelie Biscoe female 3725
119 Adelie Dream male 3725
120 Chinstrap Dream male 3725
121 Adelie Torgersen male 3750
122 Adelie Biscoe male 3750
123 Adelie Biscoe female 3750
124 Adelie Dream male 3750
125 Chinstrap Dream male 3750
126 Adelie Torgersen male 3775
127 Chinstrap Dream male 3775
128 Chinstrap Dream male 3775
129 Chinstrap Dream female 3775
130 Adelie Torgersen female 3800
131 Adelie Torgersen male 3800
132 Adelie Biscoe female 3800
133 Adelie Biscoe male 3800
134 Adelie Biscoe female 3800
135 Adelie Biscoe male 3800
136 Adelie Torgersen female 3800
137 Adelie Dream male 3800
138 Chinstrap Dream female 3800
139 Chinstrap Dream male 3800
140 Chinstrap Dream male 3800
141 Chinstrap Dream male 3800
142 Adelie Biscoe female 3825
143 Chinstrap Dream female 3850
144 Adelie Torgersen male 3875
145 Adelie Dream male 3900
146 Adelie Dream male 3900
147 Adelie Dream male 3900
148 Adelie Torgersen male 3900
149 Adelie Torgersen male 3900
150 Adelie Biscoe male 3900
151 Adelie Biscoe female 3900
152 Adelie Dream male 3900
153 Chinstrap Dream male 3900
154 Chinstrap Dream female 3900
155 Adelie Biscoe male 3950
156 Adelie Biscoe male 3950
157 Adelie Dream male 3950
158 Adelie Biscoe male 3950
159 Adelie Dream male 3950
160 Gentoo Biscoe female 3950
161 Chinstrap Dream female 3950
162 Chinstrap Dream male 3950
163 Chinstrap Dream male 3950
164 Chinstrap Dream male 3950
165 Adelie Dream male 3975
166 Adelie Torgersen male 4000
167 Adelie Torgersen male 4000
168 Adelie Torgersen male 4000
169 Adelie Dream male 4000
170 Chinstrap Dream male 4000
171 Adelie Biscoe male 4050
172 Adelie Biscoe male 4050
173 Chinstrap Dream male 4050
174 Chinstrap Dream male 4050
175 Chinstrap Dream male 4050
176 Chinstrap Dream male 4050
177 Adelie Biscoe male 4075
178 Adelie Biscoe male 4100
179 Adelie Dream male 4100
180 Gentoo Biscoe <NA> 4100
181 Chinstrap Dream male 4100
182 Chinstrap Dream male 4100
183 Adelie Dream male 4150
184 Adelie Dream male 4150
185 Adelie Torgersen male 4150
186 Gentoo Biscoe female 4150
187 Chinstrap Dream female 4150
188 Chinstrap Dream male 4150
189 Adelie Torgersen male 4200
190 Adelie Torgersen male 4200
191 Gentoo Biscoe female 4200
192 Gentoo Biscoe female 4200
193 Gentoo Biscoe female 4200
194 Adelie Torgersen <NA> 4250
195 Adelie Torgersen male 4250
196 Adelie Biscoe male 4250
197 Adelie Dream male 4250
198 Adelie Dream male 4250
199 Adelie Biscoe male 4275
200 Adelie Biscoe male 4300
201 Adelie Dream male 4300
202 Adelie Dream male 4300
203 Adelie Torgersen male 4300
204 Gentoo Biscoe female 4300
205 Gentoo Biscoe female 4300
206 Chinstrap Dream male 4300
207 Chinstrap Dream male 4300
208 Adelie Dream male 4350
209 Gentoo Biscoe female 4350
210 Gentoo Biscoe female 4375
211 Adelie Torgersen male 4400
212 Adelie Dream male 4400
213 Adelie Biscoe male 4400
214 Gentoo Biscoe female 4400
215 Gentoo Biscoe female 4400
216 Gentoo Biscoe female 4400
217 Gentoo Biscoe female 4400
218 Chinstrap Dream male 4400
219 Adelie Torgersen male 4450
220 Adelie Dream male 4450
221 Gentoo Biscoe female 4450
222 Gentoo Biscoe female 4450
223 Chinstrap Dream male 4450
224 Adelie Dream male 4475
225 Adelie Torgersen male 4500
226 Gentoo Biscoe female 4500
227 Chinstrap Dream male 4500
228 Gentoo Biscoe female 4550
229 Chinstrap Dream male 4550
230 Gentoo Biscoe female 4575
231 Adelie Dream male 4600
232 Adelie Biscoe male 4600
233 Gentoo Biscoe female 4600
234 Gentoo Biscoe female 4600
235 Gentoo Biscoe female 4600
236 Gentoo Biscoe female 4625
237 Gentoo Biscoe female 4625
238 Adelie Dream male 4650
239 Gentoo Biscoe female 4650
240 Gentoo Biscoe female 4650
241 Gentoo Biscoe <NA> 4650
242 Gentoo Biscoe female 4650
243 Adelie Torgersen male 4675
244 Adelie Torgersen male 4700
245 Gentoo Biscoe female 4700
246 Gentoo Biscoe female 4700
247 Gentoo Biscoe female 4700
248 Gentoo Biscoe female 4700
249 Gentoo Biscoe female 4700
250 Adelie Biscoe male 4725
251 Gentoo Biscoe female 4725
252 Gentoo Biscoe <NA> 4725
253 Gentoo Biscoe male 4750
254 Gentoo Biscoe female 4750
255 Gentoo Biscoe female 4750
256 Gentoo Biscoe female 4750
257 Gentoo Biscoe female 4750
258 Adelie Biscoe male 4775
259 Gentoo Biscoe female 4800
260 Gentoo Biscoe female 4800
261 Chinstrap Dream male 4800
262 Gentoo Biscoe female 4850
263 Gentoo Biscoe female 4850
264 Gentoo Biscoe female 4850
265 Gentoo Biscoe female 4850
266 Gentoo Biscoe female 4875
267 Gentoo Biscoe female 4875
268 Gentoo Biscoe <NA> 4875
269 Gentoo Biscoe female 4900
270 Gentoo Biscoe female 4900
271 Gentoo Biscoe male 4925
272 Gentoo Biscoe female 4925
273 Gentoo Biscoe female 4950
274 Gentoo Biscoe female 4950
275 Gentoo Biscoe female 4975
276 Gentoo Biscoe female 5000
277 Gentoo Biscoe female 5000
278 Gentoo Biscoe male 5000
279 Gentoo Biscoe male 5000
280 Gentoo Biscoe male 5000
281 Gentoo Biscoe female 5000
282 Gentoo Biscoe male 5050
283 Gentoo Biscoe female 5050
284 Gentoo Biscoe male 5050
285 Gentoo Biscoe male 5100
286 Gentoo Biscoe female 5100
287 Gentoo Biscoe male 5100
288 Gentoo Biscoe male 5150
289 Gentoo Biscoe female 5150
290 Gentoo Biscoe male 5200
291 Gentoo Biscoe female 5200
292 Gentoo Biscoe male 5200
293 Gentoo Biscoe female 5200
294 Gentoo Biscoe male 5250
295 Gentoo Biscoe male 5250
296 Gentoo Biscoe male 5250
297 Gentoo Biscoe male 5300
298 Gentoo Biscoe male 5300
299 Gentoo Biscoe male 5300
300 Gentoo Biscoe male 5300
301 Gentoo Biscoe male 5350
302 Gentoo Biscoe male 5350
303 Gentoo Biscoe male 5350
304 Gentoo Biscoe male 5400
305 Gentoo Biscoe male 5400
306 Gentoo Biscoe male 5400
307 Gentoo Biscoe male 5400
308 Gentoo Biscoe male 5400
309 Gentoo Biscoe male 5450
310 Gentoo Biscoe male 5500
311 Gentoo Biscoe male 5500
312 Gentoo Biscoe male 5500
313 Gentoo Biscoe male 5500
314 Gentoo Biscoe male 5500
315 Gentoo Biscoe male 5550
316 Gentoo Biscoe male 5550
317 Gentoo Biscoe male 5550
318 Gentoo Biscoe male 5550
319 Gentoo Biscoe male 5550
320 Gentoo Biscoe male 5550
321 Gentoo Biscoe male 5600
322 Gentoo Biscoe male 5600
323 Gentoo Biscoe male 5650
324 Gentoo Biscoe male 5650
325 Gentoo Biscoe male 5650
326 Gentoo Biscoe male 5700
327 Gentoo Biscoe male 5700
328 Gentoo Biscoe male 5700
329 Gentoo Biscoe male 5700
330 Gentoo Biscoe male 5700
331 Gentoo Biscoe male 5750
332 Gentoo Biscoe male 5800
333 Gentoo Biscoe male 5800
334 Gentoo Biscoe male 5850
335 Gentoo Biscoe male 5850
336 Gentoo Biscoe male 5850
337 Gentoo Biscoe male 5950
338 Gentoo Biscoe male 5950
339 Gentoo Biscoe male 6000
340 Gentoo Biscoe male 6000
341 Gentoo Biscoe male 6050
342 Gentoo Biscoe male 6300
343 Adelie Torgersen <NA> NA
344 Gentoo Biscoe <NA> NAIncreasing by default
Sorting
Use desc wrapper to sort in descending order:
species island sex body_mass
1 Gentoo Biscoe male 6300
2 Gentoo Biscoe male 6050
3 Gentoo Biscoe male 6000
4 Gentoo Biscoe male 6000
5 Gentoo Biscoe male 5950
6 Gentoo Biscoe male 5950
7 Gentoo Biscoe male 5850
8 Gentoo Biscoe male 5850
9 Gentoo Biscoe male 5850
10 Gentoo Biscoe male 5800
11 Gentoo Biscoe male 5800
12 Gentoo Biscoe male 5750
13 Gentoo Biscoe male 5700
14 Gentoo Biscoe male 5700
15 Gentoo Biscoe male 5700
16 Gentoo Biscoe male 5700
17 Gentoo Biscoe male 5700
18 Gentoo Biscoe male 5650
19 Gentoo Biscoe male 5650
20 Gentoo Biscoe male 5650
21 Gentoo Biscoe male 5600
22 Gentoo Biscoe male 5600
23 Gentoo Biscoe male 5550
24 Gentoo Biscoe male 5550
25 Gentoo Biscoe male 5550
26 Gentoo Biscoe male 5550
27 Gentoo Biscoe male 5550
28 Gentoo Biscoe male 5550
29 Gentoo Biscoe male 5500
30 Gentoo Biscoe male 5500
31 Gentoo Biscoe male 5500
32 Gentoo Biscoe male 5500
33 Gentoo Biscoe male 5500
34 Gentoo Biscoe male 5450
35 Gentoo Biscoe male 5400
36 Gentoo Biscoe male 5400
37 Gentoo Biscoe male 5400
38 Gentoo Biscoe male 5400
39 Gentoo Biscoe male 5400
40 Gentoo Biscoe male 5350
41 Gentoo Biscoe male 5350
42 Gentoo Biscoe male 5350
43 Gentoo Biscoe male 5300
44 Gentoo Biscoe male 5300
45 Gentoo Biscoe male 5300
46 Gentoo Biscoe male 5300
47 Gentoo Biscoe male 5250
48 Gentoo Biscoe male 5250
49 Gentoo Biscoe male 5250
50 Gentoo Biscoe male 5200
51 Gentoo Biscoe female 5200
52 Gentoo Biscoe male 5200
53 Gentoo Biscoe female 5200
54 Gentoo Biscoe male 5150
55 Gentoo Biscoe female 5150
56 Gentoo Biscoe male 5100
57 Gentoo Biscoe female 5100
58 Gentoo Biscoe male 5100
59 Gentoo Biscoe male 5050
60 Gentoo Biscoe female 5050
61 Gentoo Biscoe male 5050
62 Gentoo Biscoe female 5000
63 Gentoo Biscoe female 5000
64 Gentoo Biscoe male 5000
65 Gentoo Biscoe male 5000
66 Gentoo Biscoe male 5000
67 Gentoo Biscoe female 5000
68 Gentoo Biscoe female 4975
69 Gentoo Biscoe female 4950
70 Gentoo Biscoe female 4950
71 Gentoo Biscoe male 4925
72 Gentoo Biscoe female 4925
73 Gentoo Biscoe female 4900
74 Gentoo Biscoe female 4900
75 Gentoo Biscoe female 4875
76 Gentoo Biscoe female 4875
77 Gentoo Biscoe <NA> 4875
78 Gentoo Biscoe female 4850
79 Gentoo Biscoe female 4850
80 Gentoo Biscoe female 4850
81 Gentoo Biscoe female 4850
82 Gentoo Biscoe female 4800
83 Gentoo Biscoe female 4800
84 Chinstrap Dream male 4800
85 Adelie Biscoe male 4775
86 Gentoo Biscoe male 4750
87 Gentoo Biscoe female 4750
88 Gentoo Biscoe female 4750
89 Gentoo Biscoe female 4750
90 Gentoo Biscoe female 4750
91 Adelie Biscoe male 4725
92 Gentoo Biscoe female 4725
93 Gentoo Biscoe <NA> 4725
94 Adelie Torgersen male 4700
95 Gentoo Biscoe female 4700
96 Gentoo Biscoe female 4700
97 Gentoo Biscoe female 4700
98 Gentoo Biscoe female 4700
99 Gentoo Biscoe female 4700
100 Adelie Torgersen male 4675
101 Adelie Dream male 4650
102 Gentoo Biscoe female 4650
103 Gentoo Biscoe female 4650
104 Gentoo Biscoe <NA> 4650
105 Gentoo Biscoe female 4650
106 Gentoo Biscoe female 4625
107 Gentoo Biscoe female 4625
108 Adelie Dream male 4600
109 Adelie Biscoe male 4600
110 Gentoo Biscoe female 4600
111 Gentoo Biscoe female 4600
112 Gentoo Biscoe female 4600
113 Gentoo Biscoe female 4575
114 Gentoo Biscoe female 4550
115 Chinstrap Dream male 4550
116 Adelie Torgersen male 4500
117 Gentoo Biscoe female 4500
118 Chinstrap Dream male 4500
119 Adelie Dream male 4475
120 Adelie Torgersen male 4450
121 Adelie Dream male 4450
122 Gentoo Biscoe female 4450
123 Gentoo Biscoe female 4450
124 Chinstrap Dream male 4450
125 Adelie Torgersen male 4400
126 Adelie Dream male 4400
127 Adelie Biscoe male 4400
128 Gentoo Biscoe female 4400
129 Gentoo Biscoe female 4400
130 Gentoo Biscoe female 4400
131 Gentoo Biscoe female 4400
132 Chinstrap Dream male 4400
133 Gentoo Biscoe female 4375
134 Adelie Dream male 4350
135 Gentoo Biscoe female 4350
136 Adelie Biscoe male 4300
137 Adelie Dream male 4300
138 Adelie Dream male 4300
139 Adelie Torgersen male 4300
140 Gentoo Biscoe female 4300
141 Gentoo Biscoe female 4300
142 Chinstrap Dream male 4300
143 Chinstrap Dream male 4300
144 Adelie Biscoe male 4275
145 Adelie Torgersen <NA> 4250
146 Adelie Torgersen male 4250
147 Adelie Biscoe male 4250
148 Adelie Dream male 4250
149 Adelie Dream male 4250
150 Adelie Torgersen male 4200
151 Adelie Torgersen male 4200
152 Gentoo Biscoe female 4200
153 Gentoo Biscoe female 4200
154 Gentoo Biscoe female 4200
155 Adelie Dream male 4150
156 Adelie Dream male 4150
157 Adelie Torgersen male 4150
158 Gentoo Biscoe female 4150
159 Chinstrap Dream female 4150
160 Chinstrap Dream male 4150
161 Adelie Biscoe male 4100
162 Adelie Dream male 4100
163 Gentoo Biscoe <NA> 4100
164 Chinstrap Dream male 4100
165 Chinstrap Dream male 4100
166 Adelie Biscoe male 4075
167 Adelie Biscoe male 4050
168 Adelie Biscoe male 4050
169 Chinstrap Dream male 4050
170 Chinstrap Dream male 4050
171 Chinstrap Dream male 4050
172 Chinstrap Dream male 4050
173 Adelie Torgersen male 4000
174 Adelie Torgersen male 4000
175 Adelie Torgersen male 4000
176 Adelie Dream male 4000
177 Chinstrap Dream male 4000
178 Adelie Dream male 3975
179 Adelie Biscoe male 3950
180 Adelie Biscoe male 3950
181 Adelie Dream male 3950
182 Adelie Biscoe male 3950
183 Adelie Dream male 3950
184 Gentoo Biscoe female 3950
185 Chinstrap Dream female 3950
186 Chinstrap Dream male 3950
187 Chinstrap Dream male 3950
188 Chinstrap Dream male 3950
189 Adelie Dream male 3900
190 Adelie Dream male 3900
191 Adelie Dream male 3900
192 Adelie Torgersen male 3900
193 Adelie Torgersen male 3900
194 Adelie Biscoe male 3900
195 Adelie Biscoe female 3900
196 Adelie Dream male 3900
197 Chinstrap Dream male 3900
198 Chinstrap Dream female 3900
199 Adelie Torgersen male 3875
200 Chinstrap Dream female 3850
201 Adelie Biscoe female 3825
202 Adelie Torgersen female 3800
203 Adelie Torgersen male 3800
204 Adelie Biscoe female 3800
205 Adelie Biscoe male 3800
206 Adelie Biscoe female 3800
207 Adelie Biscoe male 3800
208 Adelie Torgersen female 3800
209 Adelie Dream male 3800
210 Chinstrap Dream female 3800
211 Chinstrap Dream male 3800
212 Chinstrap Dream male 3800
213 Chinstrap Dream male 3800
214 Adelie Torgersen male 3775
215 Chinstrap Dream male 3775
216 Chinstrap Dream male 3775
217 Chinstrap Dream female 3775
218 Adelie Torgersen male 3750
219 Adelie Biscoe male 3750
220 Adelie Biscoe female 3750
221 Adelie Dream male 3750
222 Chinstrap Dream male 3750
223 Adelie Biscoe female 3725
224 Adelie Dream male 3725
225 Chinstrap Dream male 3725
226 Adelie Torgersen <NA> 3700
227 Adelie Torgersen female 3700
228 Adelie Biscoe male 3700
229 Adelie Torgersen female 3700
230 Adelie Torgersen female 3700
231 Adelie Dream female 3700
232 Adelie Dream female 3700
233 Chinstrap Dream male 3700
234 Chinstrap Dream female 3700
235 Chinstrap Dream female 3700
236 Chinstrap Dream female 3700
237 Chinstrap Dream female 3675
238 Chinstrap Dream female 3675
239 Adelie Torgersen male 3650
240 Adelie Dream male 3650
241 Chinstrap Dream male 3650
242 Chinstrap Dream female 3650
243 Chinstrap Dream female 3650
244 Chinstrap Dream female 3650
245 Adelie Torgersen female 3625
246 Adelie Biscoe male 3600
247 Adelie Biscoe female 3600
248 Adelie Torgersen female 3600
249 Adelie Dream female 3600
250 Chinstrap Dream female 3600
251 Chinstrap Dream male 3600
252 Chinstrap Dream female 3600
253 Chinstrap Dream female 3575
254 Adelie Biscoe male 3550
255 Adelie Dream female 3550
256 Adelie Biscoe female 3550
257 Adelie Torgersen female 3550
258 Adelie Torgersen female 3550
259 Adelie Dream male 3550
260 Adelie Dream female 3550
261 Adelie Biscoe male 3550
262 Chinstrap Dream male 3550
263 Chinstrap Dream female 3525
264 Chinstrap Dream female 3525
265 Adelie Biscoe female 3500
266 Adelie Dream female 3500
267 Adelie Torgersen male 3500
268 Adelie Torgersen male 3500
269 Adelie Dream female 3500
270 Chinstrap Dream female 3500
271 Chinstrap Dream female 3500
272 Adelie Torgersen <NA> 3475
273 Adelie Dream male 3475
274 Adelie Dream female 3475
275 Adelie Torgersen female 3450
276 Adelie Torgersen female 3450
277 Adelie Dream female 3450
278 Adelie Biscoe female 3450
279 Adelie Torgersen female 3450
280 Adelie Dream female 3450
281 Chinstrap Dream female 3450
282 Chinstrap Dream male 3450
283 Adelie Dream male 3425
284 Adelie Dream female 3425
285 Adelie Biscoe female 3400
286 Adelie Dream female 3400
287 Adelie Dream female 3400
288 Adelie Dream female 3400
289 Chinstrap Dream male 3400
290 Chinstrap Dream female 3400
291 Chinstrap Dream female 3400
292 Chinstrap Dream female 3400
293 Adelie Biscoe female 3350
294 Adelie Dream female 3350
295 Adelie Torgersen female 3350
296 Chinstrap Dream female 3350
297 Chinstrap Dream female 3350
298 Adelie Torgersen female 3325
299 Adelie Dream female 3325
300 Adelie Torgersen male 3325
301 Adelie Torgersen female 3325
302 Chinstrap Dream female 3325
303 Adelie Torgersen <NA> 3300
304 Adelie Dream female 3300
305 Adelie Dream female 3300
306 Adelie Dream female 3300
307 Chinstrap Dream male 3300
308 Chinstrap Dream female 3300
309 Adelie Torgersen female 3275
310 Adelie Torgersen female 3250
311 Adelie Dream female 3250
312 Chinstrap Dream female 3250
313 Chinstrap Dream male 3250
314 Chinstrap Dream female 3250
315 Adelie Torgersen female 3200
316 Adelie Biscoe female 3200
317 Adelie Torgersen female 3200
318 Adelie Biscoe female 3200
319 Chinstrap Dream female 3200
320 Adelie Biscoe female 3175
321 Adelie Dream female 3175
322 Adelie Biscoe female 3150
323 Adelie Dream female 3150
324 Adelie Biscoe female 3150
325 Adelie Torgersen female 3150
326 Adelie Dream female 3100
327 Adelie Biscoe female 3075
328 Adelie Torgersen female 3050
329 Adelie Torgersen female 3050
330 Adelie Torgersen female 3050
331 Adelie Dream female 3050
332 Adelie Dream female 3000
333 Adelie Dream female 3000
334 Adelie Dream <NA> 2975
335 Adelie Biscoe female 2925
336 Adelie Biscoe female 2900
337 Adelie Dream female 2900
338 Adelie Torgersen female 2900
339 Chinstrap Dream female 2900
340 Adelie Biscoe female 2850
341 Adelie Biscoe female 2850
342 Chinstrap Dream female 2700
343 Adelie Torgersen <NA> NA
344 Gentoo Biscoe <NA> NASorting
Pass additional arguments to break ties
species island sex body_mass
1 Adelie Biscoe female 3400
2 Adelie Biscoe female 3800
3 Adelie Biscoe female 3800
4 Adelie Biscoe female 3200
5 Adelie Biscoe female 3150
6 Adelie Biscoe female 3500
7 Adelie Biscoe female 3450
8 Adelie Biscoe female 2900
9 Adelie Biscoe female 3550
10 Adelie Biscoe female 2850
11 Adelie Biscoe female 3150
12 Adelie Biscoe female 3600
13 Adelie Biscoe female 2850
14 Adelie Biscoe female 3350
15 Adelie Biscoe female 3725
16 Adelie Biscoe female 3075
17 Adelie Biscoe female 2925
18 Adelie Biscoe female 3750
19 Adelie Biscoe female 3175
20 Adelie Biscoe female 3825
21 Adelie Biscoe female 3200
22 Adelie Biscoe female 3900
23 Adelie Biscoe male 3600
24 Adelie Biscoe male 3950
25 Adelie Biscoe male 3800
26 Adelie Biscoe male 3550
27 Adelie Biscoe male 3950
28 Adelie Biscoe male 4300
29 Adelie Biscoe male 4050
30 Adelie Biscoe male 3700
31 Adelie Biscoe male 3800
32 Adelie Biscoe male 3750
33 Adelie Biscoe male 4400
34 Adelie Biscoe male 4050
35 Adelie Biscoe male 3950
36 Adelie Biscoe male 4100
37 Adelie Biscoe male 4725
38 Adelie Biscoe male 4250
39 Adelie Biscoe male 3550
40 Adelie Biscoe male 3900
41 Adelie Biscoe male 4775
42 Adelie Biscoe male 4600
43 Adelie Biscoe male 4275
44 Adelie Biscoe male 4075
45 Adelie Dream female 3250
46 Adelie Dream female 3300
47 Adelie Dream female 3325
48 Adelie Dream female 3550
49 Adelie Dream female 3300
50 Adelie Dream female 3150
51 Adelie Dream female 3100
52 Adelie Dream female 3000
53 Adelie Dream female 3450
54 Adelie Dream female 3350
55 Adelie Dream female 3500
56 Adelie Dream female 3600
57 Adelie Dream female 3550
58 Adelie Dream female 3400
59 Adelie Dream female 3300
60 Adelie Dream female 3700
61 Adelie Dream female 2900
62 Adelie Dream female 3500
63 Adelie Dream female 3425
64 Adelie Dream female 3175
65 Adelie Dream female 3400
66 Adelie Dream female 3400
67 Adelie Dream female 3050
68 Adelie Dream female 3000
69 Adelie Dream female 3475
70 Adelie Dream female 3450
71 Adelie Dream female 3700
72 Adelie Dream male 3900
73 Adelie Dream male 3900
74 Adelie Dream male 4150
75 Adelie Dream male 3950
76 Adelie Dream male 4650
77 Adelie Dream male 3900
78 Adelie Dream male 4400
79 Adelie Dream male 4600
80 Adelie Dream male 3425
81 Adelie Dream male 4150
82 Adelie Dream male 3550
83 Adelie Dream male 3800
84 Adelie Dream male 3950
85 Adelie Dream male 4300
86 Adelie Dream male 4450
87 Adelie Dream male 4300
88 Adelie Dream male 4350
89 Adelie Dream male 4100
90 Adelie Dream male 4475
91 Adelie Dream male 3900
92 Adelie Dream male 3975
93 Adelie Dream male 4250
94 Adelie Dream male 3475
95 Adelie Dream male 3725
96 Adelie Dream male 3650
97 Adelie Dream male 4250
98 Adelie Dream male 3750
99 Adelie Dream male 4000
100 Adelie Dream <NA> 2975
101 Adelie Torgersen female 3800
102 Adelie Torgersen female 3250
103 Adelie Torgersen female 3450
104 Adelie Torgersen female 3625
105 Adelie Torgersen female 3200
106 Adelie Torgersen female 3700
107 Adelie Torgersen female 3450
108 Adelie Torgersen female 3325
109 Adelie Torgersen female 3050
110 Adelie Torgersen female 3600
111 Adelie Torgersen female 3550
112 Adelie Torgersen female 3700
113 Adelie Torgersen female 3700
114 Adelie Torgersen female 3550
115 Adelie Torgersen female 3200
116 Adelie Torgersen female 3800
117 Adelie Torgersen female 2900
118 Adelie Torgersen female 3350
119 Adelie Torgersen female 3150
120 Adelie Torgersen female 3450
121 Adelie Torgersen female 3050
122 Adelie Torgersen female 3275
123 Adelie Torgersen female 3050
124 Adelie Torgersen female 3325
125 Adelie Torgersen male 3750
126 Adelie Torgersen male 3650
127 Adelie Torgersen male 4675
128 Adelie Torgersen male 3800
129 Adelie Torgersen male 4400
130 Adelie Torgersen male 4500
131 Adelie Torgersen male 4200
132 Adelie Torgersen male 4450
133 Adelie Torgersen male 3900
134 Adelie Torgersen male 4150
135 Adelie Torgersen male 4250
136 Adelie Torgersen male 3900
137 Adelie Torgersen male 4000
138 Adelie Torgersen male 4700
139 Adelie Torgersen male 4200
140 Adelie Torgersen male 3775
141 Adelie Torgersen male 3325
142 Adelie Torgersen male 3500
143 Adelie Torgersen male 3875
144 Adelie Torgersen male 4000
145 Adelie Torgersen male 4300
146 Adelie Torgersen male 4000
147 Adelie Torgersen male 3500
148 Adelie Torgersen <NA> NA
149 Adelie Torgersen <NA> 3475
150 Adelie Torgersen <NA> 4250
151 Adelie Torgersen <NA> 3300
152 Adelie Torgersen <NA> 3700
153 Chinstrap Dream female 3500
154 Chinstrap Dream female 3525
155 Chinstrap Dream female 3950
156 Chinstrap Dream female 3250
157 Chinstrap Dream female 4150
158 Chinstrap Dream female 3800
159 Chinstrap Dream female 3700
160 Chinstrap Dream female 3575
161 Chinstrap Dream female 3700
162 Chinstrap Dream female 3450
163 Chinstrap Dream female 3600
164 Chinstrap Dream female 2900
165 Chinstrap Dream female 3300
166 Chinstrap Dream female 3400
167 Chinstrap Dream female 3700
168 Chinstrap Dream female 3200
169 Chinstrap Dream female 3350
170 Chinstrap Dream female 3900
171 Chinstrap Dream female 3850
172 Chinstrap Dream female 2700
173 Chinstrap Dream female 3650
174 Chinstrap Dream female 3500
175 Chinstrap Dream female 3675
176 Chinstrap Dream female 3400
177 Chinstrap Dream female 3675
178 Chinstrap Dream female 3325
179 Chinstrap Dream female 3600
180 Chinstrap Dream female 3350
181 Chinstrap Dream female 3250
182 Chinstrap Dream female 3525
183 Chinstrap Dream female 3650
184 Chinstrap Dream female 3650
185 Chinstrap Dream female 3400
186 Chinstrap Dream female 3775
187 Chinstrap Dream male 3900
188 Chinstrap Dream male 3650
189 Chinstrap Dream male 3725
190 Chinstrap Dream male 3750
191 Chinstrap Dream male 3700
192 Chinstrap Dream male 3775
193 Chinstrap Dream male 4050
194 Chinstrap Dream male 4050
195 Chinstrap Dream male 3300
196 Chinstrap Dream male 4400
197 Chinstrap Dream male 3400
198 Chinstrap Dream male 3800
199 Chinstrap Dream male 4150
200 Chinstrap Dream male 3800
201 Chinstrap Dream male 4550
202 Chinstrap Dream male 4300
203 Chinstrap Dream male 4100
204 Chinstrap Dream male 3600
205 Chinstrap Dream male 4800
206 Chinstrap Dream male 4500
207 Chinstrap Dream male 3950
208 Chinstrap Dream male 3550
209 Chinstrap Dream male 4450
210 Chinstrap Dream male 4300
211 Chinstrap Dream male 3250
212 Chinstrap Dream male 3950
213 Chinstrap Dream male 4050
214 Chinstrap Dream male 3450
215 Chinstrap Dream male 4050
216 Chinstrap Dream male 3800
217 Chinstrap Dream male 3950
218 Chinstrap Dream male 4000
219 Chinstrap Dream male 3775
220 Chinstrap Dream male 4100
221 Gentoo Biscoe female 4500
222 Gentoo Biscoe female 4450
223 Gentoo Biscoe female 4550
224 Gentoo Biscoe female 4800
225 Gentoo Biscoe female 4400
226 Gentoo Biscoe female 4650
227 Gentoo Biscoe female 4650
228 Gentoo Biscoe female 4200
229 Gentoo Biscoe female 4150
230 Gentoo Biscoe female 4800
231 Gentoo Biscoe female 5000
232 Gentoo Biscoe female 4400
233 Gentoo Biscoe female 5000
234 Gentoo Biscoe female 4600
235 Gentoo Biscoe female 4700
236 Gentoo Biscoe female 5050
237 Gentoo Biscoe female 5150
238 Gentoo Biscoe female 4950
239 Gentoo Biscoe female 4350
240 Gentoo Biscoe female 3950
241 Gentoo Biscoe female 4300
242 Gentoo Biscoe female 4900
243 Gentoo Biscoe female 4200
244 Gentoo Biscoe female 5100
245 Gentoo Biscoe female 4850
246 Gentoo Biscoe female 4400
247 Gentoo Biscoe female 4900
248 Gentoo Biscoe female 4300
249 Gentoo Biscoe female 4450
250 Gentoo Biscoe female 4200
251 Gentoo Biscoe female 4400
252 Gentoo Biscoe female 4700
253 Gentoo Biscoe female 4700
254 Gentoo Biscoe female 4750
255 Gentoo Biscoe female 5200
256 Gentoo Biscoe female 4700
257 Gentoo Biscoe female 4600
258 Gentoo Biscoe female 4750
259 Gentoo Biscoe female 4625
260 Gentoo Biscoe female 4725
261 Gentoo Biscoe female 4750
262 Gentoo Biscoe female 4600
263 Gentoo Biscoe female 4875
264 Gentoo Biscoe female 4950
265 Gentoo Biscoe female 4750
266 Gentoo Biscoe female 4850
267 Gentoo Biscoe female 4875
268 Gentoo Biscoe female 4625
269 Gentoo Biscoe female 4850
270 Gentoo Biscoe female 4975
271 Gentoo Biscoe female 4700
272 Gentoo Biscoe female 4575
273 Gentoo Biscoe female 5000
274 Gentoo Biscoe female 4650
275 Gentoo Biscoe female 4375
276 Gentoo Biscoe female 4925
277 Gentoo Biscoe female 4850
278 Gentoo Biscoe female 5200
279 Gentoo Biscoe male 5700
280 Gentoo Biscoe male 5700
281 Gentoo Biscoe male 5400
282 Gentoo Biscoe male 5200
283 Gentoo Biscoe male 5150
284 Gentoo Biscoe male 5550
285 Gentoo Biscoe male 5850
286 Gentoo Biscoe male 5850
287 Gentoo Biscoe male 6300
288 Gentoo Biscoe male 5350
289 Gentoo Biscoe male 5700
290 Gentoo Biscoe male 5050
291 Gentoo Biscoe male 5100
292 Gentoo Biscoe male 5650
293 Gentoo Biscoe male 5550
294 Gentoo Biscoe male 5250
295 Gentoo Biscoe male 6050
296 Gentoo Biscoe male 5400
297 Gentoo Biscoe male 5250
298 Gentoo Biscoe male 5350
299 Gentoo Biscoe male 5700
300 Gentoo Biscoe male 4750
301 Gentoo Biscoe male 5550
302 Gentoo Biscoe male 5400
303 Gentoo Biscoe male 5300
304 Gentoo Biscoe male 5300
305 Gentoo Biscoe male 5000
306 Gentoo Biscoe male 5050
307 Gentoo Biscoe male 5000
308 Gentoo Biscoe male 5550
309 Gentoo Biscoe male 5300
310 Gentoo Biscoe male 5650
311 Gentoo Biscoe male 5700
312 Gentoo Biscoe male 5800
313 Gentoo Biscoe male 5550
314 Gentoo Biscoe male 5000
315 Gentoo Biscoe male 5100
316 Gentoo Biscoe male 5800
317 Gentoo Biscoe male 6000
318 Gentoo Biscoe male 5950
319 Gentoo Biscoe male 5450
320 Gentoo Biscoe male 5350
321 Gentoo Biscoe male 5600
322 Gentoo Biscoe male 5300
323 Gentoo Biscoe male 5550
324 Gentoo Biscoe male 5400
325 Gentoo Biscoe male 5650
326 Gentoo Biscoe male 5200
327 Gentoo Biscoe male 4925
328 Gentoo Biscoe male 5250
329 Gentoo Biscoe male 5600
330 Gentoo Biscoe male 5500
331 Gentoo Biscoe male 5500
332 Gentoo Biscoe male 5500
333 Gentoo Biscoe male 5500
334 Gentoo Biscoe male 5950
335 Gentoo Biscoe male 5500
336 Gentoo Biscoe male 5850
337 Gentoo Biscoe male 6000
338 Gentoo Biscoe male 5750
339 Gentoo Biscoe male 5400
340 Gentoo Biscoe <NA> 4100
341 Gentoo Biscoe <NA> 4650
342 Gentoo Biscoe <NA> 4725
343 Gentoo Biscoe <NA> 4875
344 Gentoo Biscoe <NA> NAGrouped Operations
So far, we have operated on the whole data set - what if there is meaningful substructure?
(In statistics-speak, non “IID”)
Exercise: Lab #04
Data Set: nycflights13
Breakout Rooms
| Breakout | Team |
|---|---|
| 1 | JE+JABB+MTP+JA+AS |
| 2 | XC+ML+ER+RJSN |
| 3 | MUO+KN+CM+ID+KM |
| 4 | HHS+KK+FC+DN |
| 5 | LR+MOG+APTL+TN |
Adding Group Structure
group_by is an adverb. On its own, it does nothing; it changes the behavior of later functionality.
Compare to:
# A tibble: 6 × 8
# Groups: species [3]
species island bill_len bill_dep flipper_len body_mass sex year
<fct> <fct> <dbl> <dbl> <int> <int> <fct> <int>
1 Adelie Torgersen 39.1 18.7 181 3750 male 2007
2 Adelie Torgersen 39.5 17.4 186 3800 female 2007
3 Chinstrap Dream 46.5 17.9 192 3500 female 2007
4 Chinstrap Dream 50 19.5 196 3900 male 2007
5 Gentoo Biscoe 46.1 13.2 211 4500 female 2007
6 Gentoo Biscoe 50 16.3 230 5700 male 20072 per group
Group Summaries
No group_by - full summarization:
Group Summaries
With multiple grouping - “cross-tabs” of results:
Note that result of multi-group_by is still grouped
Multiple Groups
Persistent multiple groupings change subsequent call to summarize:
Order of group_by
- No change to first “grouped” operations
- Change in grouping structure of result
- Last group “removed” by
summarize - No impact on grouped operations performed by
mutateorfilter
Note: group_by impacts filter and mutate if “implicit” summarization is used: filter(x > mean(x)) will use a groupwise mean
ungroup
ungroup() function:
- Remove all grouping structure
- Defensive to keep group structure from “propogating” unwantedly
ungroup
Alternatively, use .by and .groups argument to summarize:
penguins |>
group_by(sex, species) |>
summarize(mbmg = mean(body_mass),
.groups="drop") # Drop all groups# A tibble: 8 × 3
sex species mbmg
<fct> <fct> <dbl>
1 female Adelie 3369.
2 female Chinstrap 3527.
3 female Gentoo 4680.
4 male Adelie 4043.
5 male Chinstrap 3939.
6 male Gentoo 5485.
7 <NA> Adelie NA
8 <NA> Gentoo NA penguins |>
summarize(mbmg = mean(body_mass), # Groups summarize() _only_,
.by=c(sex, species)) # Not earlier or later funcs sex species mbmg
1 male Adelie 4043.493
2 female Adelie 3368.836
3 <NA> Adelie NA
4 female Gentoo 4679.741
5 male Gentoo 5484.836
6 <NA> Gentoo NA
7 female Chinstrap 3527.206
8 male Chinstrap 3938.971FAQs / Advanced Topics
Assignment of Pipelines
When to start a pipeline with NAME <-?
Creating a new variable:
- Data you intend to reuse
- Assignment operator ‘up front’ indicates important
- My rules of thumb for names:
- New names for “new complete thoughts” - whole summary in one pipeline
- Overwrite existing names for “like-for-like improvements” (
USAGE <- USAGE |> code(...))- Recoding variable names, fixing typos, etc.
- Use name repeatedly so downstream code picks up effects ‘for free’
Comp to SQL and Pandas
dplyr is heavily inspired by SQL (standard query language for data bases)
- MW (2014): “Why bother? Can’t folks just use SQL”
pandas (in Python) inspired by R data.frame and SQL:
- A bit older than
dplyr(cousins?) - “New hotness” (
polars) directly inspired bydplyr
Performance
dplyr is fast, but advanced options:
dbplyr: translatesdplyrsyntax to SQL and executes in DBdtplyr: uses alternatedata.tableback-end (HFT)
Hard to have bad performance in single-table analysis
- Danger of accidentally creating ‘extra’ data in multi-table context
- Will discuss more next week
Performance
Tools for slow code:
Don’t worry about improving code performance until:
- You’re sure it’s right
- You’re sure it’s slow
Incorrect code is infinitely slow.
Wrap-Up
Review
Introduction to dplyr:
- Data Frames
- Selecting Columns and Rows
- Creating New Columns
- Groupwise Analysis
Life Tip of the Week
Easy Duplicate Emails with Gmail
If you have a gmail account, you actually have infinite accounts:
email+tag@gmail.com gets forwarded to email@gmail.com
for any (reasonable) tag
Duplicate Emails with Gmail
Use this to:
- Track who is reselling your email
- Get access to ‘new account sales’ / ‘signup promotions’
- Typically based on new email
- Quickly sort and organize emails