Software Tools for Data Analysis
STA 9750
Michael Weylandt
Week 4

STA 9750 Week 4

Today:

  • Tuesday Section: 2025-09-16
  • Thursday Section: 2025-09-18

Lecture #04: Single Table dplyr Verbs

Mini-Project #00

Mini-Project #00 peer feedback assigned

  • Due 2025-09-22 2025-09-24
  • 4 peer feedbacks per student
    • Give 4 comments, get 4 comments
    • A few exceptions

Peer Feedback Instructions can be found online

Mini-Project #00

The helper functions can be used to make this process easier:

  1. Locate PF assignments: mp_feedback_locate
  2. Provide PF: mp_feedback_create
  3. Verify PF Submitted: mp_feedback_verify

Locate PF Assignment

Methods:

  1. Check your email
  2. Check https://github.com/notifications
  3. Use the course helper scripts:
source("https://michael-weylandt.com/STA9750/load_helpers.R")
mp_feedback_locate()

Provide PF

Methods:

  1. Manually copy and fill provided template
  2. Course helper scripts
source("https://michael-weylandt.com/STA9750/load_helpers.R")
mp_feedback_submit()

Confirm PF

Methods:

  1. Visually check template matched
  2. Course helper scripts
source("https://michael-weylandt.com/STA9750/load_helpers.R")
mp_feedback_verify()

MP PF Cycle

Aims of Mini-Project Peer Feedback:

  • Learn to read and evaluate code
  • In analysis, rarely right and wrong; definitely better and worse
  • Learn tricks to improve your own site

“Good artists copy; great artists steal.” – Steve Jobs

Most coding is reading - most reading is reading your own old code

Course Support

Asynchronous Support: Piazza

  • All registered now in Piazza!
  • 10 minute average time to response

Synchronous Support: Office Hours

  • Tuesdays and Thursdays at 5pm
  • Still waiting on CUNY HR before TA office hours begin

Pre-Assignments

Pre-Assignment #04

  • Ignore Brightspace’s Grading
    • Brightspace calls all short answers wrong
    • Gradebook shows complete/incomplete grading

Pre-Assignment #05 - Due 2025-09-29 at 11:59pm ET

  • Day before class at midnight each week
  • Available on course website + Brightspace after 9pm

No class on Tuesday Sep 23rd

Course Project

Roster due at 2025-09-30 by email to me.

All teammates need to agree, so takes a bit of time.

Once you set a team, start thinking about a team name!

Initial presentations on Tuesday Oct 07 and Thursday Oct 09

Next Week: Special presentation on identifying data sources

Today

Today

  • Single-Table Verbs
  • Introduction to MP#01
  • PA#04 FAQs
  • Wrap-Up

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

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 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 2009

data.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   male

Key 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 R for 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: Visualization
  • dplyr: SQL-like operations
  • tidyr: Reshaping and cleaning data
  • readr: Ingest tidy data into R
  • 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   400

Tidy! ✅

  • 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 rows

and

# 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

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

select and rename

How can we select certain columns?

select() will pick columns

penguins |> select(species, island, bill_dep)
      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     18.7

select and rename

Can also use to drop columns:

penguins |> select(-species, -island, -bill_dep)
    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 2009

select and rename

You shouldn’t mix select and drop - results non-intuitive

penguins |> select(species, -island, -bill_dep)
      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 Chinstrap

select and rename

To rename a column, pass a named argument to rename

penguins |> 
    select(species, island, bill_dep) |>
    rename(Species = species)
      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     18.7

tidyselect

dplyr has many more selection functions for getting groups of related columns

See tidyselect for details

filter Operations

While select is used to isolate columns, filter is used to isolate rows:

penguins |> filter(species == "Adelie")
    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

filter Operations

Pass multiple arguments to get the intersection

penguins |> filter(species == "Adelie", island=="Biscoe")
   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 2009

filter Operations

Can compute quantities inside of filter

To select heavier than average penguins:

penguins |> filter(body_mass > mean(body_mass, na.rm=TRUE))
      species    island bill_len bill_dep flipper_len body_mass    sex year
1      Adelie Torgersen     39.2     19.6         195      4675   male 2007
2      Adelie Torgersen     42.0     20.2         190      4250   <NA> 2007
3      Adelie Torgersen     34.6     21.1         198      4400   male 2007
4      Adelie Torgersen     42.5     20.7         197      4500   male 2007
5      Adelie     Dream     39.8     19.1         184      4650   male 2007
6      Adelie     Dream     44.1     19.7         196      4400   male 2007
7      Adelie     Dream     39.6     18.8         190      4600   male 2007
8      Adelie    Biscoe     40.1     18.9         188      4300   male 2008
9      Adelie    Biscoe     41.3     21.1         195      4400   male 2008
10     Adelie Torgersen     41.8     19.4         198      4450   male 2008
11     Adelie Torgersen     42.8     18.5         195      4250   male 2008
12     Adelie Torgersen     42.9     17.6         196      4700   male 2008
13     Adelie     Dream     41.1     18.1         205      4300   male 2008
14     Adelie     Dream     39.6     18.1         186      4450   male 2008
15     Adelie     Dream     40.8     18.9         208      4300   male 2008
16     Adelie     Dream     40.3     18.5         196      4350   male 2008
17     Adelie    Biscoe     41.0     20.0         203      4725   male 2009
18     Adelie    Biscoe     37.8     20.0         190      4250   male 2009
19     Adelie    Biscoe     43.2     19.0         197      4775   male 2009
20     Adelie    Biscoe     45.6     20.3         191      4600   male 2009
21     Adelie    Biscoe     42.2     19.5         197      4275   male 2009
22     Adelie Torgersen     41.5     18.3         195      4300   male 2009
23     Adelie     Dream     37.5     18.5         199      4475   male 2009
24     Adelie     Dream     39.7     17.9         193      4250   male 2009
25     Adelie     Dream     39.2     18.6         190      4250   male 2009
26     Gentoo    Biscoe     46.1     13.2         211      4500 female 2007
27     Gentoo    Biscoe     50.0     16.3         230      5700   male 2007
28     Gentoo    Biscoe     48.7     14.1         210      4450 female 2007
29     Gentoo    Biscoe     50.0     15.2         218      5700   male 2007
30     Gentoo    Biscoe     47.6     14.5         215      5400   male 2007
31     Gentoo    Biscoe     46.5     13.5         210      4550 female 2007
32     Gentoo    Biscoe     45.4     14.6         211      4800 female 2007
33     Gentoo    Biscoe     46.7     15.3         219      5200   male 2007
34     Gentoo    Biscoe     43.3     13.4         209      4400 female 2007
35     Gentoo    Biscoe     46.8     15.4         215      5150   male 2007
36     Gentoo    Biscoe     40.9     13.7         214      4650 female 2007
37     Gentoo    Biscoe     49.0     16.1         216      5550   male 2007
38     Gentoo    Biscoe     45.5     13.7         214      4650 female 2007
39     Gentoo    Biscoe     48.4     14.6         213      5850   male 2007
40     Gentoo    Biscoe     49.3     15.7         217      5850   male 2007
41     Gentoo    Biscoe     49.2     15.2         221      6300   male 2007
42     Gentoo    Biscoe     46.2     14.5         209      4800 female 2007
43     Gentoo    Biscoe     48.7     15.1         222      5350   male 2007
44     Gentoo    Biscoe     50.2     14.3         218      5700   male 2007
45     Gentoo    Biscoe     45.1     14.5         215      5000 female 2007
46     Gentoo    Biscoe     46.5     14.5         213      4400 female 2007
47     Gentoo    Biscoe     46.3     15.8         215      5050   male 2007
48     Gentoo    Biscoe     42.9     13.1         215      5000 female 2007
49     Gentoo    Biscoe     46.1     15.1         215      5100   male 2007
50     Gentoo    Biscoe     47.8     15.0         215      5650   male 2007
51     Gentoo    Biscoe     48.2     14.3         210      4600 female 2007
52     Gentoo    Biscoe     50.0     15.3         220      5550   male 2007
53     Gentoo    Biscoe     47.3     15.3         222      5250   male 2007
54     Gentoo    Biscoe     42.8     14.2         209      4700 female 2007
55     Gentoo    Biscoe     45.1     14.5         207      5050 female 2007
56     Gentoo    Biscoe     59.6     17.0         230      6050   male 2007
57     Gentoo    Biscoe     49.1     14.8         220      5150 female 2008
58     Gentoo    Biscoe     48.4     16.3         220      5400   male 2008
59     Gentoo    Biscoe     42.6     13.7         213      4950 female 2008
60     Gentoo    Biscoe     44.4     17.3         219      5250   male 2008
61     Gentoo    Biscoe     44.0     13.6         208      4350 female 2008
62     Gentoo    Biscoe     48.7     15.7         208      5350   male 2008
63     Gentoo    Biscoe     49.6     16.0         225      5700   male 2008
64     Gentoo    Biscoe     45.3     13.7         210      4300 female 2008
65     Gentoo    Biscoe     49.6     15.0         216      4750   male 2008
66     Gentoo    Biscoe     50.5     15.9         222      5550   male 2008
67     Gentoo    Biscoe     43.6     13.9         217      4900 female 2008
68     Gentoo    Biscoe     50.5     15.9         225      5400   male 2008
69     Gentoo    Biscoe     44.9     13.3         213      5100 female 2008
70     Gentoo    Biscoe     45.2     15.8         215      5300   male 2008
71     Gentoo    Biscoe     46.6     14.2         210      4850 female 2008
72     Gentoo    Biscoe     48.5     14.1         220      5300   male 2008
73     Gentoo    Biscoe     45.1     14.4         210      4400 female 2008
74     Gentoo    Biscoe     50.1     15.0         225      5000   male 2008
75     Gentoo    Biscoe     46.5     14.4         217      4900 female 2008
76     Gentoo    Biscoe     45.0     15.4         220      5050   male 2008
77     Gentoo    Biscoe     43.8     13.9         208      4300 female 2008
78     Gentoo    Biscoe     45.5     15.0         220      5000   male 2008
79     Gentoo    Biscoe     43.2     14.5         208      4450 female 2008
80     Gentoo    Biscoe     50.4     15.3         224      5550   male 2008
81     Gentoo    Biscoe     46.2     14.9         221      5300   male 2008
82     Gentoo    Biscoe     45.7     13.9         214      4400 female 2008
83     Gentoo    Biscoe     54.3     15.7         231      5650   male 2008
84     Gentoo    Biscoe     45.8     14.2         219      4700 female 2008
85     Gentoo    Biscoe     49.8     16.8         230      5700   male 2008
86     Gentoo    Biscoe     46.2     14.4         214      4650   <NA> 2008
87     Gentoo    Biscoe     49.5     16.2         229      5800   male 2008
88     Gentoo    Biscoe     43.5     14.2         220      4700 female 2008
89     Gentoo    Biscoe     50.7     15.0         223      5550   male 2008
90     Gentoo    Biscoe     47.7     15.0         216      4750 female 2008
91     Gentoo    Biscoe     46.4     15.6         221      5000   male 2008
92     Gentoo    Biscoe     48.2     15.6         221      5100   male 2008
93     Gentoo    Biscoe     46.5     14.8         217      5200 female 2008
94     Gentoo    Biscoe     46.4     15.0         216      4700 female 2008
95     Gentoo    Biscoe     48.6     16.0         230      5800   male 2008
96     Gentoo    Biscoe     47.5     14.2         209      4600 female 2008
97     Gentoo    Biscoe     51.1     16.3         220      6000   male 2008
98     Gentoo    Biscoe     45.2     13.8         215      4750 female 2008
99     Gentoo    Biscoe     45.2     16.4         223      5950   male 2008
100    Gentoo    Biscoe     49.1     14.5         212      4625 female 2009
101    Gentoo    Biscoe     52.5     15.6         221      5450   male 2009
102    Gentoo    Biscoe     47.4     14.6         212      4725 female 2009
103    Gentoo    Biscoe     50.0     15.9         224      5350   male 2009
104    Gentoo    Biscoe     44.9     13.8         212      4750 female 2009
105    Gentoo    Biscoe     50.8     17.3         228      5600   male 2009
106    Gentoo    Biscoe     43.4     14.4         218      4600 female 2009
107    Gentoo    Biscoe     51.3     14.2         218      5300   male 2009
108    Gentoo    Biscoe     47.5     14.0         212      4875 female 2009
109    Gentoo    Biscoe     52.1     17.0         230      5550   male 2009
110    Gentoo    Biscoe     47.5     15.0         218      4950 female 2009
111    Gentoo    Biscoe     52.2     17.1         228      5400   male 2009
112    Gentoo    Biscoe     45.5     14.5         212      4750 female 2009
113    Gentoo    Biscoe     49.5     16.1         224      5650   male 2009
114    Gentoo    Biscoe     44.5     14.7         214      4850 female 2009
115    Gentoo    Biscoe     50.8     15.7         226      5200   male 2009
116    Gentoo    Biscoe     49.4     15.8         216      4925   male 2009
117    Gentoo    Biscoe     46.9     14.6         222      4875 female 2009
118    Gentoo    Biscoe     48.4     14.4         203      4625 female 2009
119    Gentoo    Biscoe     51.1     16.5         225      5250   male 2009
120    Gentoo    Biscoe     48.5     15.0         219      4850 female 2009
121    Gentoo    Biscoe     55.9     17.0         228      5600   male 2009
122    Gentoo    Biscoe     47.2     15.5         215      4975 female 2009
123    Gentoo    Biscoe     49.1     15.0         228      5500   male 2009
124    Gentoo    Biscoe     47.3     13.8         216      4725   <NA> 2009
125    Gentoo    Biscoe     46.8     16.1         215      5500   male 2009
126    Gentoo    Biscoe     41.7     14.7         210      4700 female 2009
127    Gentoo    Biscoe     53.4     15.8         219      5500   male 2009
128    Gentoo    Biscoe     43.3     14.0         208      4575 female 2009
129    Gentoo    Biscoe     48.1     15.1         209      5500   male 2009
130    Gentoo    Biscoe     50.5     15.2         216      5000 female 2009
131    Gentoo    Biscoe     49.8     15.9         229      5950   male 2009
132    Gentoo    Biscoe     43.5     15.2         213      4650 female 2009
133    Gentoo    Biscoe     51.5     16.3         230      5500   male 2009
134    Gentoo    Biscoe     46.2     14.1         217      4375 female 2009
135    Gentoo    Biscoe     55.1     16.0         230      5850   male 2009
136    Gentoo    Biscoe     44.5     15.7         217      4875   <NA> 2009
137    Gentoo    Biscoe     48.8     16.2         222      6000   male 2009
138    Gentoo    Biscoe     47.2     13.7         214      4925 female 2009
139    Gentoo    Biscoe     46.8     14.3         215      4850 female 2009
140    Gentoo    Biscoe     50.4     15.7         222      5750   male 2009
141    Gentoo    Biscoe     45.2     14.8         212      5200 female 2009
142    Gentoo    Biscoe     49.9     16.1         213      5400   male 2009
143 Chinstrap     Dream     49.2     18.2         195      4400   male 2007
144 Chinstrap     Dream     52.8     20.0         205      4550   male 2008
145 Chinstrap     Dream     54.2     20.8         201      4300   male 2008
146 Chinstrap     Dream     52.0     20.7         210      4800   male 2008
147 Chinstrap     Dream     53.5     19.9         205      4500   male 2008
148 Chinstrap     Dream     50.8     18.5         201      4450   male 2009
149 Chinstrap     Dream     49.0     19.6         212      4300   male 2009

Grouped 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

Introduction to MP#01

MP#01

MP#01 due 2025-10-03 at 11:59pm ET:

Gourmet Cheeseburgers Across the Globe: Exploring the Most Popular Programming on Netflix

Instructions online

Not everything has a single right answer - be reasonable, justify, and document

MP#01 Analysis

Analysis:

  • Netflix Top10 Data
  • Steps:
    • Data Import and Preparation
    • Initial Exploration
    • Writing Press Releases
  • Practice dplyr single-table calculations

MP#01 Formatting

Formatting:

  • qmd document
  • “Press Release” + supporting analysis
    • Put press releases 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

Rubric online

  • 4 graded sections (out of 10)
  • 1 automatic 10 as long as you copy+paste my code

PA#04 FAQs

select(-)

data |> select(colname) keeps colname, dropping everything else

data |> select(-colname) drops colname, keeping everything else

Dropping is mainly useful for

  • Presentation (removing unwanted columns)
  • Advanced:
    • Operations across columns

filter vs group_by

group_by is an adverb. On its own, it does nothing; it changes the behavior of later functionality.

penguins |> drop_na() |> head(2)
  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
penguins |> drop_na() |> group_by(species) |> head(2)
# A tibble: 2 × 8
# Groups:   species [1]
  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

filter vs group_by

No group_by - full summarization:

penguins |> drop_na() |> summarize(mean(body_mass))
  mean(body_mass)
1        4207.057

With group_by - summary within groups.

penguins |> drop_na() |> group_by(species) |> summarize(mean(body_mass))
# A tibble: 3 × 2
  species   `mean(body_mass)`
  <fct>                 <dbl>
1 Adelie                3706.
2 Chinstrap             3733.
3 Gentoo                5092.

filter vs group_by

With multiple grouping - “cross-tabs” of results:

penguins |> drop_na() |> group_by(species, sex) |> summarize(mean(body_mass))
`summarise()` has grouped output by 'species'. You can override using the
`.groups` argument.
# A tibble: 6 × 3
# Groups:   species [3]
  species   sex    `mean(body_mass)`
  <fct>     <fct>              <dbl>
1 Adelie    female             3369.
2 Adelie    male               4043.
3 Chinstrap female             3527.
4 Chinstrap male               3939.
5 Gentoo    female             4680.
6 Gentoo    male               5485.

Note that result of multi-group_by is still grouped:

penguins |> drop_na() |> group_by(species, sex) |> summarize(mean(body_mass))
`summarise()` has grouped output by 'species'. You can override using the
`.groups` argument.
# A tibble: 6 × 3
# Groups:   species [3]
  species   sex    `mean(body_mass)`
  <fct>     <fct>              <dbl>
1 Adelie    female             3369.
2 Adelie    male               4043.
3 Chinstrap female             3527.
4 Chinstrap male               3939.
5 Gentoo    female             4680.
6 Gentoo    male               5485.

filter vs group_by

Changes next call to summarize:

penguins |> drop_na() |> group_by(species) |> 
    summarize(mbmg = mean(body_mass)) |> summarize(mean(mbmg))
# A tibble: 1 × 1
  `mean(mbmg)`
         <dbl>
1        4177.
penguins |> drop_na() |> group_by(species, sex) |> 
    summarize(mbmg = mean(body_mass)) |> summarize(mean(mbmg))
`summarise()` has grouped output by 'species'. You can override using the
`.groups` argument.
# A tibble: 3 × 2
  species   `mean(mbmg)`
  <fct>            <dbl>
1 Adelie           3706.
2 Chinstrap        3733.
3 Gentoo           5082.
penguins |> drop_na() |> group_by(sex, species) |> 
    summarize(mbmg = mean(body_mass)) |> summarize(mean(mbmg))
`summarise()` has grouped output by 'sex'. You can override using the `.groups`
argument.
# A tibble: 2 × 2
  sex    `mean(mbmg)`
  <fct>         <dbl>
1 female        3859.
2 male          4489.

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 mutate or filter

ungroup

  • Remove all grouping structure
  • Defensive to keep group structure from “propogating” unwantedly
sum_penguins <- penguins |> 
    group_by(sex, species) |> 
    summarize(mbmg = mean(body_mass))

... # Lots of code 

sum_penguins |> filter(mbmg == max(mbmg)) # Still grouped!!

Named Arguments

mutate and summarize create new columns:

  • mutate creates “one-to-one”
  • summarize creates “one-per-group”

If you want to name them (so you can use them later), use named argument

Named Arguments

Named Arguments:

penguins |> group_by(species) |> summarize(n())
# A tibble: 3 × 2
  species   `n()`
  <fct>     <int>
1 Adelie      152
2 Chinstrap    68
3 Gentoo      124

vs

penguins |> group_by(species) |> summarize(n_species = n())
# A tibble: 3 × 2
  species   n_species
  <fct>         <int>
1 Adelie          152
2 Chinstrap        68
3 Gentoo          124

Pipe Syntax

Pipe syntax (|>) is “syntactic sugar”

Just makes code easier to read:

penguins |> group_by(species) |> summarize(n_species = n())
# vs
summarize(group_by(penguins, species), n_species=n())

Exactly the same execution: improved UX

%>% is an older way of doing essentially the same thing

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 by dplyr

Performance

dplyr is fast, but advanced options:

  • dbplyr: translates dplyr syntax to SQL and executes in DB
  • dtplyr: uses alternate data.table back-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:

  1. You’re sure it’s right
  2. 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

Upcoming Work

Upcoming work from course calendar

Looking Ahead

  • MP#01
  • Course Project: Teams & Proposals

Life Tip of the Week

Making the most of Amazon

  1. Free Trial and Discounted Rate Amazon Prime for Students
  2. Amazon Prime Visa by Chase: No annual fee + 5% cash back (or more) on all Amazon/Whole Foods/Chase Travel + 2% on gas, restaurants, and transit
  3. Camel Camel Camel
    • Price history for all Amazon items (see if you’re getting a good deal)
    • Price drop alert emails (get custom messages when an item goes on sale)

Musical Treat


Live Video