- Load the R packages we will use
- Read the data in the file,
drug_cos.csvin to R and assign it todrug_cos
drug_cos <- read.csv("https://estanny.com/static/week5/drug_cos.csv")
Use glimse() to get a glimpse of your data.
glimpse(drug_cos)
Rows: 104
Columns: 9
$ ticker <chr> "ZTS", "ZTS", "ZTS", "ZTS", "ZTS", "ZTS", "Z...
$ name <chr> "Zoetis Inc", "Zoetis Inc", "Zoetis Inc", "Z...
$ location <chr> "New Jersey; U.S.A", "New Jersey; U.S.A", "N...
$ ebitdamargin <dbl> 0.149, 0.217, 0.222, 0.238, 0.182, 0.335, 0....
$ grossmargin <dbl> 0.610, 0.640, 0.634, 0.641, 0.635, 0.659, 0....
$ netmargin <dbl> 0.058, 0.101, 0.111, 0.122, 0.071, 0.168, 0....
$ ros <dbl> 0.101, 0.171, 0.176, 0.195, 0.140, 0.286, 0....
$ roe <dbl> 0.069, 0.113, 0.612, 0.465, 0.285, 0.587, 0....
$ year <int> 2011, 2012, 2013, 2014, 2015, 2016, 2017, 20...- Use
distinct()to subset distinct rows
drug_cos %>%
distinct(year)
year
1 2011
2 2012
3 2013
4 2014
5 2015
6 2016
7 2017
8 2018- Use
count()to count observations by group
drug_cos %>%
count(year)
year n
1 2011 13
2 2012 13
3 2013 13
4 2014 13
5 2015 13
6 2016 13
7 2017 13
8 2018 13drug_cos %>%
count(name)
name n
1 AbbVie Inc 8
2 Allergan plc 8
3 Amgen Inc 8
4 Biogen Inc 8
5 Bristol Myers Squibb Co 8
6 ELI LILLY & Co 8
7 Gilead Sciences Inc 8
8 Johnson & Johnson 8
9 Merck & Co Inc 8
10 Mylan NV 8
11 PERRIGO Co plc 8
12 Pfizer Inc 8
13 Zoetis Inc 8drug_cos %>%
count(ticker, name)
ticker name n
1 ABBV AbbVie Inc 8
2 AGN Allergan plc 8
3 AMGN Amgen Inc 8
4 BIIB Biogen Inc 8
5 BMY Bristol Myers Squibb Co 8
6 GILD Gilead Sciences Inc 8
7 JNJ Johnson & Johnson 8
8 LLY ELI LILLY & Co 8
9 MRK Merck & Co Inc 8
10 MYL Mylan NV 8
11 PFE Pfizer Inc 8
12 PRGO PERRIGO Co plc 8
13 ZTS Zoetis Inc 8- Extract rows in non-consectuive years
ticker name location ebitdamargin
1 ZTS Zoetis Inc New Jersey; U.S.A 0.222
2 ZTS Zoetis Inc New Jersey; U.S.A 0.379
3 PRGO PERRIGO Co plc Ireland 0.236
4 PRGO PERRIGO Co plc Ireland 0.178
5 PFE Pfizer Inc New York; U.S.A 0.634
6 PFE Pfizer Inc New York; U.S.A 0.340
7 MYL Mylan NV United Kingdom 0.228
8 MYL Mylan NV United Kingdom 0.258
9 MRK Merck & Co Inc New Jersey; U.S.A 0.282
10 MRK Merck & Co Inc New Jersey; U.S.A 0.313
11 LLY ELI LILLY & Co Indiana; U.S.A 0.317
12 LLY ELI LILLY & Co Indiana; U.S.A 0.220
13 JNJ Johnson & Johnson New Jersey; U.S.A 0.281
14 JNJ Johnson & Johnson New Jersey; U.S.A 0.318
15 GILD Gilead Sciences Inc California; U.S.A 0.435
16 GILD Gilead Sciences Inc California; U.S.A 0.465
17 BMY Bristol Myers Squibb Co New York; U.S.A 0.222
18 BMY Bristol Myers Squibb Co New York; U.S.A 0.292
19 BIIB Biogen Inc Massachusetts; U.S.A 0.432
20 BIIB Biogen Inc Massachusetts; U.S.A 0.511
21 AMGN Amgen Inc California; U.S.A 0.405
22 AMGN Amgen Inc California; U.S.A 0.543
23 AGN Allergan plc Ireland 0.146
24 AGN Allergan plc Ireland 0.050
25 ABBV AbbVie Inc Illinois; U.S.A 0.346
26 ABBV AbbVie Inc Illinois; U.S.A 0.247
grossmargin netmargin ros roe year
1 0.634 0.111 0.176 0.612 2013
2 0.672 0.245 0.326 0.694 2018
3 0.362 0.125 0.190 0.205 2013
4 0.387 0.028 0.088 0.022 2018
5 0.814 0.427 0.510 0.279 2013
6 0.790 0.208 0.221 0.162 2018
7 0.440 0.090 0.153 0.209 2013
8 0.350 0.031 0.074 0.028 2018
9 0.615 0.100 0.123 0.089 2013
10 0.681 0.147 0.206 0.199 2018
11 0.788 0.203 0.255 0.290 2013
12 0.738 0.132 0.155 0.264 2018
13 0.687 0.194 0.224 0.197 2013
14 0.668 0.188 0.233 0.244 2018
15 0.745 0.275 0.405 0.283 2013
16 0.781 0.247 0.401 0.252 2018
17 0.718 0.156 0.175 0.177 2013
18 0.710 0.218 0.263 0.373 2018
19 0.876 0.269 0.355 0.233 2013
20 0.865 0.329 0.435 0.334 2018
21 0.821 0.272 0.337 0.242 2013
22 0.827 0.353 0.461 0.585 2018
23 0.368 -0.288 -0.256 -0.147 2013
24 0.861 -0.326 -0.377 -0.074 2018
25 0.756 0.220 0.299 1.132 2013
26 0.764 0.174 0.194 -2.033 2018- Extract every other year from 2012 to 2018
ticker name location ebitdamargin
1 ZTS Zoetis Inc New Jersey; U.S.A 0.217
2 ZTS Zoetis Inc New Jersey; U.S.A 0.238
3 ZTS Zoetis Inc New Jersey; U.S.A 0.335
4 ZTS Zoetis Inc New Jersey; U.S.A 0.379
5 PRGO PERRIGO Co plc Ireland 0.226
6 PRGO PERRIGO Co plc Ireland 0.157
7 PRGO PERRIGO Co plc Ireland -0.791
8 PRGO PERRIGO Co plc Ireland 0.178
9 PFE Pfizer Inc New York; U.S.A 0.447
10 PFE Pfizer Inc New York; U.S.A 0.359
11 PFE Pfizer Inc New York; U.S.A 0.267
12 PFE Pfizer Inc New York; U.S.A 0.340
13 MYL Mylan NV United Kingdom 0.244
14 MYL Mylan NV United Kingdom 0.242
15 MYL Mylan NV United Kingdom 0.190
16 MYL Mylan NV United Kingdom 0.258
17 MRK Merck & Co Inc New Jersey; U.S.A 0.330
18 MRK Merck & Co Inc New Jersey; U.S.A 0.567
19 MRK Merck & Co Inc New Jersey; U.S.A 0.254
20 MRK Merck & Co Inc New Jersey; U.S.A 0.313
21 LLY ELI LILLY & Co Indiana; U.S.A 0.304
22 LLY ELI LILLY & Co Indiana; U.S.A 0.223
23 LLY ELI LILLY & Co Indiana; U.S.A 0.230
24 LLY ELI LILLY & Co Indiana; U.S.A 0.220
25 JNJ Johnson & Johnson New Jersey; U.S.A 0.272
26 JNJ Johnson & Johnson New Jersey; U.S.A 0.336
27 JNJ Johnson & Johnson New Jersey; U.S.A 0.338
28 JNJ Johnson & Johnson New Jersey; U.S.A 0.318
29 GILD Gilead Sciences Inc California; U.S.A 0.440
30 GILD Gilead Sciences Inc California; U.S.A 0.657
31 GILD Gilead Sciences Inc California; U.S.A 0.633
32 GILD Gilead Sciences Inc California; U.S.A 0.465
33 BMY Bristol Myers Squibb Co New York; U.S.A 0.141
34 BMY Bristol Myers Squibb Co New York; U.S.A 0.178
35 BMY Bristol Myers Squibb Co New York; U.S.A 0.322
36 BMY Bristol Myers Squibb Co New York; U.S.A 0.292
37 BIIB Biogen Inc Massachusetts; U.S.A 0.402
38 BIIB Biogen Inc Massachusetts; U.S.A 0.475
39 BIIB Biogen Inc Massachusetts; U.S.A 0.491
40 BIIB Biogen Inc Massachusetts; U.S.A 0.511
41 AMGN Amgen Inc California; U.S.A 0.414
42 AMGN Amgen Inc California; U.S.A 0.436
43 AMGN Amgen Inc California; U.S.A 0.545
44 AMGN Amgen Inc California; U.S.A 0.543
45 AGN Allergan plc Ireland 0.158
46 AGN Allergan plc Ireland 0.234
47 AGN Allergan plc Ireland 1.441
48 AGN Allergan plc Ireland 0.050
49 ABBV AbbVie Inc Illinois; U.S.A 0.379
50 ABBV AbbVie Inc Illinois; U.S.A 0.178
51 ABBV AbbVie Inc Illinois; U.S.A 0.392
52 ABBV AbbVie Inc Illinois; U.S.A 0.247
grossmargin netmargin ros roe year
1 0.640 0.101 0.171 0.113 2012
2 0.641 0.122 0.195 0.465 2014
3 0.659 0.168 0.286 0.587 2016
4 0.672 0.245 0.326 0.694 2018
5 0.345 0.127 0.183 0.236 2012
6 0.371 0.059 0.104 0.033 2014
7 0.389 -0.760 -0.877 -0.498 2016
8 0.387 0.028 0.088 0.022 2018
9 0.820 0.267 0.307 0.179 2012
10 0.807 0.184 0.247 0.120 2014
11 0.767 0.137 0.158 0.116 2016
12 0.790 0.208 0.221 0.162 2018
13 0.428 0.094 0.163 0.184 2012
14 0.457 0.120 0.169 0.283 2014
15 0.424 0.043 0.052 0.044 2016
16 0.350 0.031 0.074 0.028 2018
17 0.652 0.130 0.182 0.113 2012
18 0.603 0.282 0.409 0.248 2014
19 0.648 0.098 0.117 0.092 2016
20 0.681 0.147 0.206 0.199 2018
21 0.788 0.181 0.239 0.273 2012
22 0.749 0.122 0.153 0.138 2014
23 0.731 0.129 0.159 0.185 2016
24 0.738 0.132 0.155 0.264 2018
25 0.678 0.161 0.218 0.173 2012
26 0.694 0.220 0.284 0.217 2014
27 0.697 0.230 0.286 0.229 2016
28 0.668 0.188 0.233 0.244 2018
29 0.745 0.267 0.411 0.312 2012
30 0.848 0.486 0.615 0.828 2014
31 0.860 0.444 0.595 0.835 2016
32 0.781 0.247 0.401 0.252 2018
33 0.738 0.111 0.102 0.131 2012
34 0.752 0.126 0.148 0.132 2014
35 0.744 0.229 0.302 0.292 2016
36 0.710 0.218 0.263 0.373 2018
37 0.901 0.250 0.335 0.211 2012
38 0.879 0.302 0.404 0.294 2014
39 0.871 0.323 0.431 0.322 2016
40 0.865 0.329 0.435 0.334 2018
41 0.815 0.252 0.351 0.225 2012
42 0.780 0.257 0.332 0.210 2014
43 0.819 0.336 0.453 0.259 2016
44 0.827 0.353 0.461 0.585 2018
45 0.426 0.016 0.060 0.026 2012
46 0.635 -0.349 -0.370 -0.085 2014
47 0.872 1.009 0.986 0.184 2016
48 0.861 -0.326 -0.377 -0.074 2018
49 0.755 0.287 0.316 0.690 2012
50 0.778 0.089 0.138 0.435 2014
51 0.773 0.232 0.345 1.113 2016
52 0.764 0.174 0.194 -2.033 2018- Extract the tickets “PFE and”MYL"
ticker name location ebitdamargin grossmargin
1 PFE Pfizer Inc New York; U.S.A 0.371 0.795
2 PFE Pfizer Inc New York; U.S.A 0.447 0.820
3 PFE Pfizer Inc New York; U.S.A 0.634 0.814
4 PFE Pfizer Inc New York; U.S.A 0.359 0.807
5 PFE Pfizer Inc New York; U.S.A 0.289 0.803
6 PFE Pfizer Inc New York; U.S.A 0.267 0.767
7 PFE Pfizer Inc New York; U.S.A 0.353 0.786
8 PFE Pfizer Inc New York; U.S.A 0.340 0.790
9 MYL Mylan NV United Kingdom 0.245 0.418
10 MYL Mylan NV United Kingdom 0.244 0.428
11 MYL Mylan NV United Kingdom 0.228 0.440
12 MYL Mylan NV United Kingdom 0.242 0.457
13 MYL Mylan NV United Kingdom 0.243 0.447
14 MYL Mylan NV United Kingdom 0.190 0.424
15 MYL Mylan NV United Kingdom 0.272 0.402
16 MYL Mylan NV United Kingdom 0.258 0.350
netmargin ros roe year
1 0.164 0.223 0.114 2011
2 0.267 0.307 0.179 2012
3 0.427 0.510 0.279 2013
4 0.184 0.247 0.120 2014
5 0.142 0.183 0.105 2015
6 0.137 0.158 0.116 2016
7 0.406 0.233 0.342 2017
8 0.208 0.221 0.162 2018
9 0.088 0.161 0.146 2011
10 0.094 0.163 0.184 2012
11 0.090 0.153 0.209 2013
12 0.120 0.169 0.283 2014
13 0.090 0.133 0.089 2015
14 0.043 0.052 0.044 2016
15 0.058 0.121 0.054 2017
16 0.031 0.074 0.028 2018Use select() to select, rename and reorder columns
- Select columns
ticker,nameandros
drug_cos %>%
select(ticker,name, ros)
ticker name ros
1 ZTS Zoetis Inc 0.101
2 ZTS Zoetis Inc 0.171
3 ZTS Zoetis Inc 0.176
4 ZTS Zoetis Inc 0.195
5 ZTS Zoetis Inc 0.140
6 ZTS Zoetis Inc 0.286
7 ZTS Zoetis Inc 0.321
8 ZTS Zoetis Inc 0.326
9 PRGO PERRIGO Co plc 0.178
10 PRGO PERRIGO Co plc 0.183
11 PRGO PERRIGO Co plc 0.190
12 PRGO PERRIGO Co plc 0.104
13 PRGO PERRIGO Co plc 0.096
14 PRGO PERRIGO Co plc -0.877
15 PRGO PERRIGO Co plc 0.091
16 PRGO PERRIGO Co plc 0.088
17 PFE Pfizer Inc 0.223
18 PFE Pfizer Inc 0.307
19 PFE Pfizer Inc 0.510
20 PFE Pfizer Inc 0.247
21 PFE Pfizer Inc 0.183
22 PFE Pfizer Inc 0.158
23 PFE Pfizer Inc 0.233
24 PFE Pfizer Inc 0.221
25 MYL Mylan NV 0.161
26 MYL Mylan NV 0.163
27 MYL Mylan NV 0.153
28 MYL Mylan NV 0.169
29 MYL Mylan NV 0.133
30 MYL Mylan NV 0.052
31 MYL Mylan NV 0.121
32 MYL Mylan NV 0.074
33 MRK Merck & Co Inc 0.150
34 MRK Merck & Co Inc 0.182
35 MRK Merck & Co Inc 0.123
36 MRK Merck & Co Inc 0.409
37 MRK Merck & Co Inc 0.136
38 MRK Merck & Co Inc 0.117
39 MRK Merck & Co Inc 0.162
40 MRK Merck & Co Inc 0.206
41 LLY ELI LILLY & Co 0.220
42 LLY ELI LILLY & Co 0.239
43 LLY ELI LILLY & Co 0.255
44 LLY ELI LILLY & Co 0.153
45 LLY ELI LILLY & Co 0.140
46 LLY ELI LILLY & Co 0.159
47 LLY ELI LILLY & Co 0.096
48 LLY ELI LILLY & Co 0.155
49 JNJ Johnson & Johnson 0.199
50 JNJ Johnson & Johnson 0.218
51 JNJ Johnson & Johnson 0.224
52 JNJ Johnson & Johnson 0.284
53 JNJ Johnson & Johnson 0.282
54 JNJ Johnson & Johnson 0.286
55 JNJ Johnson & Johnson 0.243
56 JNJ Johnson & Johnson 0.233
57 GILD Gilead Sciences Inc 0.462
58 GILD Gilead Sciences Inc 0.411
59 GILD Gilead Sciences Inc 0.405
60 GILD Gilead Sciences Inc 0.615
61 GILD Gilead Sciences Inc 0.685
62 GILD Gilead Sciences Inc 0.595
63 GILD Gilead Sciences Inc 0.560
64 GILD Gilead Sciences Inc 0.401
65 BMY Bristol Myers Squibb Co 0.256
66 BMY Bristol Myers Squibb Co 0.102
67 BMY Bristol Myers Squibb Co 0.175
68 BMY Bristol Myers Squibb Co 0.148
69 BMY Bristol Myers Squibb Co 0.121
70 BMY Bristol Myers Squibb Co 0.302
71 BMY Bristol Myers Squibb Co 0.249
72 BMY Bristol Myers Squibb Co 0.263
73 BIIB Biogen Inc 0.333
74 BIIB Biogen Inc 0.335
75 BIIB Biogen Inc 0.355
76 BIIB Biogen Inc 0.404
77 BIIB Biogen Inc 0.437
78 BIIB Biogen Inc 0.431
79 BIIB Biogen Inc 0.407
80 BIIB Biogen Inc 0.435
81 AMGN Amgen Inc 0.305
82 AMGN Amgen Inc 0.351
83 AMGN Amgen Inc 0.337
84 AMGN Amgen Inc 0.332
85 AMGN Amgen Inc 0.419
86 AMGN Amgen Inc 0.453
87 AMGN Amgen Inc 0.477
88 AMGN Amgen Inc 0.461
89 AGN Allergan plc 0.115
90 AGN Allergan plc 0.060
91 AGN Allergan plc -0.256
92 AGN Allergan plc -0.370
93 AGN Allergan plc 0.276
94 AGN Allergan plc 0.986
95 AGN Allergan plc -0.609
96 AGN Allergan plc -0.377
97 ABBV AbbVie Inc 0.209
98 ABBV AbbVie Inc 0.316
99 ABBV AbbVie Inc 0.299
100 ABBV AbbVie Inc 0.138
101 ABBV AbbVie Inc 0.321
102 ABBV AbbVie Inc 0.345
103 ABBV AbbVie Inc 0.309
104 ABBV AbbVie Inc 0.194- Use
selectto exclude columnsticker,nameandros
drug_cos %>%
select(-ticker,-name, -ros)
location ebitdamargin grossmargin netmargin roe
1 New Jersey; U.S.A 0.149 0.610 0.058 0.069
2 New Jersey; U.S.A 0.217 0.640 0.101 0.113
3 New Jersey; U.S.A 0.222 0.634 0.111 0.612
4 New Jersey; U.S.A 0.238 0.641 0.122 0.465
5 New Jersey; U.S.A 0.182 0.635 0.071 0.285
6 New Jersey; U.S.A 0.335 0.659 0.168 0.587
7 New Jersey; U.S.A 0.366 0.666 0.163 0.488
8 New Jersey; U.S.A 0.379 0.672 0.245 0.694
9 Ireland 0.216 0.343 0.123 0.248
10 Ireland 0.226 0.345 0.127 0.236
11 Ireland 0.236 0.362 0.125 0.205
12 Ireland 0.157 0.371 0.059 0.033
13 Ireland 0.157 0.389 0.032 0.014
14 Ireland -0.791 0.389 -0.760 -0.498
15 Ireland 0.181 0.400 0.024 0.020
16 Ireland 0.178 0.387 0.028 0.022
17 New York; U.S.A 0.371 0.795 0.164 0.114
18 New York; U.S.A 0.447 0.820 0.267 0.179
19 New York; U.S.A 0.634 0.814 0.427 0.279
20 New York; U.S.A 0.359 0.807 0.184 0.120
21 New York; U.S.A 0.289 0.803 0.142 0.105
22 New York; U.S.A 0.267 0.767 0.137 0.116
23 New York; U.S.A 0.353 0.786 0.406 0.342
24 New York; U.S.A 0.340 0.790 0.208 0.162
25 United Kingdom 0.245 0.418 0.088 0.146
26 United Kingdom 0.244 0.428 0.094 0.184
27 United Kingdom 0.228 0.440 0.090 0.209
28 United Kingdom 0.242 0.457 0.120 0.283
29 United Kingdom 0.243 0.447 0.090 0.089
30 United Kingdom 0.190 0.424 0.043 0.044
31 United Kingdom 0.272 0.402 0.058 0.054
32 United Kingdom 0.258 0.350 0.031 0.028
33 New Jersey; U.S.A 0.305 0.649 0.131 0.114
34 New Jersey; U.S.A 0.330 0.652 0.130 0.113
35 New Jersey; U.S.A 0.282 0.615 0.100 0.089
36 New Jersey; U.S.A 0.567 0.603 0.282 0.248
37 New Jersey; U.S.A 0.298 0.622 0.112 0.096
38 New Jersey; U.S.A 0.254 0.648 0.098 0.092
39 New Jersey; U.S.A 0.278 0.678 0.060 0.063
40 New Jersey; U.S.A 0.313 0.681 0.147 0.199
41 Indiana; U.S.A 0.277 0.791 0.179 0.306
42 Indiana; U.S.A 0.304 0.788 0.181 0.273
43 Indiana; U.S.A 0.317 0.788 0.203 0.290
44 Indiana; U.S.A 0.223 0.749 0.122 0.138
45 Indiana; U.S.A 0.211 0.748 0.121 0.162
46 Indiana; U.S.A 0.230 0.731 0.129 0.185
47 Indiana; U.S.A 0.165 0.731 -0.009 -0.015
48 Indiana; U.S.A 0.220 0.738 0.132 0.264
49 New Jersey; U.S.A 0.247 0.687 0.149 0.161
50 New Jersey; U.S.A 0.272 0.678 0.161 0.173
51 New Jersey; U.S.A 0.281 0.687 0.194 0.197
52 New Jersey; U.S.A 0.336 0.694 0.220 0.217
53 New Jersey; U.S.A 0.335 0.693 0.220 0.219
54 New Jersey; U.S.A 0.338 0.697 0.230 0.229
55 New Jersey; U.S.A 0.317 0.667 0.017 0.019
56 New Jersey; U.S.A 0.318 0.668 0.188 0.244
57 California; U.S.A 0.498 0.747 0.334 0.451
58 California; U.S.A 0.440 0.745 0.267 0.312
59 California; U.S.A 0.435 0.745 0.275 0.283
60 California; U.S.A 0.657 0.848 0.486 0.828
61 California; U.S.A 0.718 0.877 0.555 1.043
62 California; U.S.A 0.633 0.860 0.444 0.835
63 California; U.S.A 0.610 0.833 0.177 0.209
64 California; U.S.A 0.465 0.781 0.247 0.252
65 New York; U.S.A 0.285 0.736 0.175 0.229
66 New York; U.S.A 0.141 0.738 0.111 0.131
67 New York; U.S.A 0.222 0.718 0.156 0.177
68 New York; U.S.A 0.178 0.752 0.126 0.132
69 New York; U.S.A 0.144 0.764 0.095 0.104
70 New York; U.S.A 0.322 0.744 0.229 0.292
71 New York; U.S.A 0.286 0.707 0.048 0.072
72 New York; U.S.A 0.292 0.710 0.218 0.373
73 Massachusetts; U.S.A 0.404 0.908 0.245 0.204
74 Massachusetts; U.S.A 0.402 0.901 0.250 0.211
75 Massachusetts; U.S.A 0.432 0.876 0.269 0.233
76 Massachusetts; U.S.A 0.475 0.879 0.302 0.294
77 Massachusetts; U.S.A 0.493 0.885 0.330 0.321
78 Massachusetts; U.S.A 0.491 0.871 0.323 0.322
79 Massachusetts; U.S.A 0.495 0.867 0.207 0.209
80 Massachusetts; U.S.A 0.511 0.865 0.329 0.334
81 California; U.S.A 0.374 0.826 0.236 0.158
82 California; U.S.A 0.414 0.815 0.252 0.225
83 California; U.S.A 0.405 0.821 0.272 0.242
84 California; U.S.A 0.436 0.780 0.257 0.210
85 California; U.S.A 0.516 0.805 0.320 0.252
86 California; U.S.A 0.545 0.819 0.336 0.259
87 California; U.S.A 0.563 0.822 0.087 0.066
88 California; U.S.A 0.543 0.827 0.353 0.585
89 Ireland 0.213 0.440 0.057 0.075
90 Ireland 0.158 0.426 0.016 0.026
91 Ireland 0.146 0.368 -0.288 -0.147
92 Ireland 0.234 0.635 -0.349 -0.085
93 Ireland 0.749 0.783 0.290 0.050
94 Ireland 1.441 0.872 1.009 0.184
95 Ireland -0.146 0.864 -0.276 -0.060
96 Ireland 0.050 0.861 -0.326 -0.074
97 Illinois; U.S.A 0.282 0.734 0.197 0.248
98 Illinois; U.S.A 0.379 0.755 0.287 0.690
99 Illinois; U.S.A 0.346 0.756 0.220 1.132
100 Illinois; U.S.A 0.178 0.778 0.089 0.435
101 Illinois; U.S.A 0.357 0.803 0.225 1.311
102 Illinois; U.S.A 0.392 0.773 0.232 1.113
103 Illinois; U.S.A 0.363 0.750 0.188 0.932
104 Illinois; U.S.A 0.247 0.764 0.174 -2.033
year
1 2011
2 2012
3 2013
4 2014
5 2015
6 2016
7 2017
8 2018
9 2011
10 2012
11 2013
12 2014
13 2015
14 2016
15 2017
16 2018
17 2011
18 2012
19 2013
20 2014
21 2015
22 2016
23 2017
24 2018
25 2011
26 2012
27 2013
28 2014
29 2015
30 2016
31 2017
32 2018
33 2011
34 2012
35 2013
36 2014
37 2015
38 2016
39 2017
40 2018
41 2011
42 2012
43 2013
44 2014
45 2015
46 2016
47 2017
48 2018
49 2011
50 2012
51 2013
52 2014
53 2015
54 2016
55 2017
56 2018
57 2011
58 2012
59 2013
60 2014
61 2015
62 2016
63 2017
64 2018
65 2011
66 2012
67 2013
68 2014
69 2015
70 2016
71 2017
72 2018
73 2011
74 2012
75 2013
76 2014
77 2015
78 2016
79 2017
80 2018
81 2011
82 2012
83 2013
84 2014
85 2015
86 2016
87 2017
88 2018
89 2011
90 2012
91 2013
92 2014
93 2015
94 2016
95 2017
96 2018
97 2011
98 2012
99 2013
100 2014
101 2015
102 2016
103 2017
104 2018- Rename and reorder columns with
select
start with drug_cos THEN
change the name of location to headquarter
put the columns in this order year, ticker, headquarter, netmargin, roe
drug_cos %>%
select(year, ticker, headquarter = location, netmargin, roe)
year ticker headquarter netmargin roe
1 2011 ZTS New Jersey; U.S.A 0.058 0.069
2 2012 ZTS New Jersey; U.S.A 0.101 0.113
3 2013 ZTS New Jersey; U.S.A 0.111 0.612
4 2014 ZTS New Jersey; U.S.A 0.122 0.465
5 2015 ZTS New Jersey; U.S.A 0.071 0.285
6 2016 ZTS New Jersey; U.S.A 0.168 0.587
7 2017 ZTS New Jersey; U.S.A 0.163 0.488
8 2018 ZTS New Jersey; U.S.A 0.245 0.694
9 2011 PRGO Ireland 0.123 0.248
10 2012 PRGO Ireland 0.127 0.236
11 2013 PRGO Ireland 0.125 0.205
12 2014 PRGO Ireland 0.059 0.033
13 2015 PRGO Ireland 0.032 0.014
14 2016 PRGO Ireland -0.760 -0.498
15 2017 PRGO Ireland 0.024 0.020
16 2018 PRGO Ireland 0.028 0.022
17 2011 PFE New York; U.S.A 0.164 0.114
18 2012 PFE New York; U.S.A 0.267 0.179
19 2013 PFE New York; U.S.A 0.427 0.279
20 2014 PFE New York; U.S.A 0.184 0.120
21 2015 PFE New York; U.S.A 0.142 0.105
22 2016 PFE New York; U.S.A 0.137 0.116
23 2017 PFE New York; U.S.A 0.406 0.342
24 2018 PFE New York; U.S.A 0.208 0.162
25 2011 MYL United Kingdom 0.088 0.146
26 2012 MYL United Kingdom 0.094 0.184
27 2013 MYL United Kingdom 0.090 0.209
28 2014 MYL United Kingdom 0.120 0.283
29 2015 MYL United Kingdom 0.090 0.089
30 2016 MYL United Kingdom 0.043 0.044
31 2017 MYL United Kingdom 0.058 0.054
32 2018 MYL United Kingdom 0.031 0.028
33 2011 MRK New Jersey; U.S.A 0.131 0.114
34 2012 MRK New Jersey; U.S.A 0.130 0.113
35 2013 MRK New Jersey; U.S.A 0.100 0.089
36 2014 MRK New Jersey; U.S.A 0.282 0.248
37 2015 MRK New Jersey; U.S.A 0.112 0.096
38 2016 MRK New Jersey; U.S.A 0.098 0.092
39 2017 MRK New Jersey; U.S.A 0.060 0.063
40 2018 MRK New Jersey; U.S.A 0.147 0.199
41 2011 LLY Indiana; U.S.A 0.179 0.306
42 2012 LLY Indiana; U.S.A 0.181 0.273
43 2013 LLY Indiana; U.S.A 0.203 0.290
44 2014 LLY Indiana; U.S.A 0.122 0.138
45 2015 LLY Indiana; U.S.A 0.121 0.162
46 2016 LLY Indiana; U.S.A 0.129 0.185
47 2017 LLY Indiana; U.S.A -0.009 -0.015
48 2018 LLY Indiana; U.S.A 0.132 0.264
49 2011 JNJ New Jersey; U.S.A 0.149 0.161
50 2012 JNJ New Jersey; U.S.A 0.161 0.173
51 2013 JNJ New Jersey; U.S.A 0.194 0.197
52 2014 JNJ New Jersey; U.S.A 0.220 0.217
53 2015 JNJ New Jersey; U.S.A 0.220 0.219
54 2016 JNJ New Jersey; U.S.A 0.230 0.229
55 2017 JNJ New Jersey; U.S.A 0.017 0.019
56 2018 JNJ New Jersey; U.S.A 0.188 0.244
57 2011 GILD California; U.S.A 0.334 0.451
58 2012 GILD California; U.S.A 0.267 0.312
59 2013 GILD California; U.S.A 0.275 0.283
60 2014 GILD California; U.S.A 0.486 0.828
61 2015 GILD California; U.S.A 0.555 1.043
62 2016 GILD California; U.S.A 0.444 0.835
63 2017 GILD California; U.S.A 0.177 0.209
64 2018 GILD California; U.S.A 0.247 0.252
65 2011 BMY New York; U.S.A 0.175 0.229
66 2012 BMY New York; U.S.A 0.111 0.131
67 2013 BMY New York; U.S.A 0.156 0.177
68 2014 BMY New York; U.S.A 0.126 0.132
69 2015 BMY New York; U.S.A 0.095 0.104
70 2016 BMY New York; U.S.A 0.229 0.292
71 2017 BMY New York; U.S.A 0.048 0.072
72 2018 BMY New York; U.S.A 0.218 0.373
73 2011 BIIB Massachusetts; U.S.A 0.245 0.204
74 2012 BIIB Massachusetts; U.S.A 0.250 0.211
75 2013 BIIB Massachusetts; U.S.A 0.269 0.233
76 2014 BIIB Massachusetts; U.S.A 0.302 0.294
77 2015 BIIB Massachusetts; U.S.A 0.330 0.321
78 2016 BIIB Massachusetts; U.S.A 0.323 0.322
79 2017 BIIB Massachusetts; U.S.A 0.207 0.209
80 2018 BIIB Massachusetts; U.S.A 0.329 0.334
81 2011 AMGN California; U.S.A 0.236 0.158
82 2012 AMGN California; U.S.A 0.252 0.225
83 2013 AMGN California; U.S.A 0.272 0.242
84 2014 AMGN California; U.S.A 0.257 0.210
85 2015 AMGN California; U.S.A 0.320 0.252
86 2016 AMGN California; U.S.A 0.336 0.259
87 2017 AMGN California; U.S.A 0.087 0.066
88 2018 AMGN California; U.S.A 0.353 0.585
89 2011 AGN Ireland 0.057 0.075
90 2012 AGN Ireland 0.016 0.026
91 2013 AGN Ireland -0.288 -0.147
92 2014 AGN Ireland -0.349 -0.085
93 2015 AGN Ireland 0.290 0.050
94 2016 AGN Ireland 1.009 0.184
95 2017 AGN Ireland -0.276 -0.060
96 2018 AGN Ireland -0.326 -0.074
97 2011 ABBV Illinois; U.S.A 0.197 0.248
98 2012 ABBV Illinois; U.S.A 0.287 0.690
99 2013 ABBV Illinois; U.S.A 0.220 1.132
100 2014 ABBV Illinois; U.S.A 0.089 0.435
101 2015 ABBV Illinois; U.S.A 0.225 1.311
102 2016 ABBV Illinois; U.S.A 0.232 1.113
103 2017 ABBV Illinois; U.S.A 0.188 0.932
104 2018 ABBV Illinois; U.S.A 0.174 -2.033Question: filter and select
Use inputs from your quiz questions filter and select and replace SEE QUIZ THEN select the variables ticker, year and SEE QUIZ
ticker year ros
1 PRGO 2011 0.178
2 PRGO 2012 0.183
3 PRGO 2013 0.190
4 PRGO 2014 0.104
5 PRGO 2015 0.096
6 PRGO 2016 -0.877
7 PRGO 2017 0.091
8 PRGO 2018 0.088
9 PFE 2011 0.223
10 PFE 2012 0.307
11 PFE 2013 0.510
12 PFE 2014 0.247
13 PFE 2015 0.183
14 PFE 2016 0.158
15 PFE 2017 0.233
16 PFE 2018 0.221
17 BMY 2011 0.256
18 BMY 2012 0.102
19 BMY 2013 0.175
20 BMY 2014 0.148
21 BMY 2015 0.121
22 BMY 2016 0.302
23 BMY 2017 0.249
24 BMY 2018 0.263Question: rename
start with drug_cos THEN extract information for the tickers SEE QUiz THEN select the variable ticker, SEE QUIZ and roe, Change the name of roe to return_on_equity
drug_cos %>%
filter(ticker %in% c("ABBV","BMY")) %>%
select(ticker, netmargin, return_on_equity = roe)
ticker netmargin return_on_equity
1 BMY 0.175 0.229
2 BMY 0.111 0.131
3 BMY 0.156 0.177
4 BMY 0.126 0.132
5 BMY 0.095 0.104
6 BMY 0.229 0.292
7 BMY 0.048 0.072
8 BMY 0.218 0.373
9 ABBV 0.197 0.248
10 ABBV 0.287 0.690
11 ABBV 0.220 1.132
12 ABBV 0.089 0.435
13 ABBV 0.225 1.311
14 ABBV 0.232 1.113
15 ABBV 0.188 0.932
16 ABBV 0.174 -2.033selectranges of columns
by name
drug_cos %>%
select(ebitdamargin:netmargin)
ebitdamargin grossmargin netmargin
1 0.149 0.610 0.058
2 0.217 0.640 0.101
3 0.222 0.634 0.111
4 0.238 0.641 0.122
5 0.182 0.635 0.071
6 0.335 0.659 0.168
7 0.366 0.666 0.163
8 0.379 0.672 0.245
9 0.216 0.343 0.123
10 0.226 0.345 0.127
11 0.236 0.362 0.125
12 0.157 0.371 0.059
13 0.157 0.389 0.032
14 -0.791 0.389 -0.760
15 0.181 0.400 0.024
16 0.178 0.387 0.028
17 0.371 0.795 0.164
18 0.447 0.820 0.267
19 0.634 0.814 0.427
20 0.359 0.807 0.184
21 0.289 0.803 0.142
22 0.267 0.767 0.137
23 0.353 0.786 0.406
24 0.340 0.790 0.208
25 0.245 0.418 0.088
26 0.244 0.428 0.094
27 0.228 0.440 0.090
28 0.242 0.457 0.120
29 0.243 0.447 0.090
30 0.190 0.424 0.043
31 0.272 0.402 0.058
32 0.258 0.350 0.031
33 0.305 0.649 0.131
34 0.330 0.652 0.130
35 0.282 0.615 0.100
36 0.567 0.603 0.282
37 0.298 0.622 0.112
38 0.254 0.648 0.098
39 0.278 0.678 0.060
40 0.313 0.681 0.147
41 0.277 0.791 0.179
42 0.304 0.788 0.181
43 0.317 0.788 0.203
44 0.223 0.749 0.122
45 0.211 0.748 0.121
46 0.230 0.731 0.129
47 0.165 0.731 -0.009
48 0.220 0.738 0.132
49 0.247 0.687 0.149
50 0.272 0.678 0.161
51 0.281 0.687 0.194
52 0.336 0.694 0.220
53 0.335 0.693 0.220
54 0.338 0.697 0.230
55 0.317 0.667 0.017
56 0.318 0.668 0.188
57 0.498 0.747 0.334
58 0.440 0.745 0.267
59 0.435 0.745 0.275
60 0.657 0.848 0.486
61 0.718 0.877 0.555
62 0.633 0.860 0.444
63 0.610 0.833 0.177
64 0.465 0.781 0.247
65 0.285 0.736 0.175
66 0.141 0.738 0.111
67 0.222 0.718 0.156
68 0.178 0.752 0.126
69 0.144 0.764 0.095
70 0.322 0.744 0.229
71 0.286 0.707 0.048
72 0.292 0.710 0.218
73 0.404 0.908 0.245
74 0.402 0.901 0.250
75 0.432 0.876 0.269
76 0.475 0.879 0.302
77 0.493 0.885 0.330
78 0.491 0.871 0.323
79 0.495 0.867 0.207
80 0.511 0.865 0.329
81 0.374 0.826 0.236
82 0.414 0.815 0.252
83 0.405 0.821 0.272
84 0.436 0.780 0.257
85 0.516 0.805 0.320
86 0.545 0.819 0.336
87 0.563 0.822 0.087
88 0.543 0.827 0.353
89 0.213 0.440 0.057
90 0.158 0.426 0.016
91 0.146 0.368 -0.288
92 0.234 0.635 -0.349
93 0.749 0.783 0.290
94 1.441 0.872 1.009
95 -0.146 0.864 -0.276
96 0.050 0.861 -0.326
97 0.282 0.734 0.197
98 0.379 0.755 0.287
99 0.346 0.756 0.220
100 0.178 0.778 0.089
101 0.357 0.803 0.225
102 0.392 0.773 0.232
103 0.363 0.750 0.188
104 0.247 0.764 0.174by position
drug_cos %>%
select(4:6)
ebitdamargin grossmargin netmargin
1 0.149 0.610 0.058
2 0.217 0.640 0.101
3 0.222 0.634 0.111
4 0.238 0.641 0.122
5 0.182 0.635 0.071
6 0.335 0.659 0.168
7 0.366 0.666 0.163
8 0.379 0.672 0.245
9 0.216 0.343 0.123
10 0.226 0.345 0.127
11 0.236 0.362 0.125
12 0.157 0.371 0.059
13 0.157 0.389 0.032
14 -0.791 0.389 -0.760
15 0.181 0.400 0.024
16 0.178 0.387 0.028
17 0.371 0.795 0.164
18 0.447 0.820 0.267
19 0.634 0.814 0.427
20 0.359 0.807 0.184
21 0.289 0.803 0.142
22 0.267 0.767 0.137
23 0.353 0.786 0.406
24 0.340 0.790 0.208
25 0.245 0.418 0.088
26 0.244 0.428 0.094
27 0.228 0.440 0.090
28 0.242 0.457 0.120
29 0.243 0.447 0.090
30 0.190 0.424 0.043
31 0.272 0.402 0.058
32 0.258 0.350 0.031
33 0.305 0.649 0.131
34 0.330 0.652 0.130
35 0.282 0.615 0.100
36 0.567 0.603 0.282
37 0.298 0.622 0.112
38 0.254 0.648 0.098
39 0.278 0.678 0.060
40 0.313 0.681 0.147
41 0.277 0.791 0.179
42 0.304 0.788 0.181
43 0.317 0.788 0.203
44 0.223 0.749 0.122
45 0.211 0.748 0.121
46 0.230 0.731 0.129
47 0.165 0.731 -0.009
48 0.220 0.738 0.132
49 0.247 0.687 0.149
50 0.272 0.678 0.161
51 0.281 0.687 0.194
52 0.336 0.694 0.220
53 0.335 0.693 0.220
54 0.338 0.697 0.230
55 0.317 0.667 0.017
56 0.318 0.668 0.188
57 0.498 0.747 0.334
58 0.440 0.745 0.267
59 0.435 0.745 0.275
60 0.657 0.848 0.486
61 0.718 0.877 0.555
62 0.633 0.860 0.444
63 0.610 0.833 0.177
64 0.465 0.781 0.247
65 0.285 0.736 0.175
66 0.141 0.738 0.111
67 0.222 0.718 0.156
68 0.178 0.752 0.126
69 0.144 0.764 0.095
70 0.322 0.744 0.229
71 0.286 0.707 0.048
72 0.292 0.710 0.218
73 0.404 0.908 0.245
74 0.402 0.901 0.250
75 0.432 0.876 0.269
76 0.475 0.879 0.302
77 0.493 0.885 0.330
78 0.491 0.871 0.323
79 0.495 0.867 0.207
80 0.511 0.865 0.329
81 0.374 0.826 0.236
82 0.414 0.815 0.252
83 0.405 0.821 0.272
84 0.436 0.780 0.257
85 0.516 0.805 0.320
86 0.545 0.819 0.336
87 0.563 0.822 0.087
88 0.543 0.827 0.353
89 0.213 0.440 0.057
90 0.158 0.426 0.016
91 0.146 0.368 -0.288
92 0.234 0.635 -0.349
93 0.749 0.783 0.290
94 1.441 0.872 1.009
95 -0.146 0.864 -0.276
96 0.050 0.861 -0.326
97 0.282 0.734 0.197
98 0.379 0.755 0.287
99 0.346 0.756 0.220
100 0.178 0.778 0.089
101 0.357 0.803 0.225
102 0.392 0.773 0.232
103 0.363 0.750 0.188
104 0.247 0.764 0.174selecthelper functions
starts_with("abc) matches columns with “abc”
ends_with("abc) matches columns with “abc”
contains_with("abc) matches columns with “abc”
drug_cos %>%
select(ticker, contains("locat"))
ticker location
1 ZTS New Jersey; U.S.A
2 ZTS New Jersey; U.S.A
3 ZTS New Jersey; U.S.A
4 ZTS New Jersey; U.S.A
5 ZTS New Jersey; U.S.A
6 ZTS New Jersey; U.S.A
7 ZTS New Jersey; U.S.A
8 ZTS New Jersey; U.S.A
9 PRGO Ireland
10 PRGO Ireland
11 PRGO Ireland
12 PRGO Ireland
13 PRGO Ireland
14 PRGO Ireland
15 PRGO Ireland
16 PRGO Ireland
17 PFE New York; U.S.A
18 PFE New York; U.S.A
19 PFE New York; U.S.A
20 PFE New York; U.S.A
21 PFE New York; U.S.A
22 PFE New York; U.S.A
23 PFE New York; U.S.A
24 PFE New York; U.S.A
25 MYL United Kingdom
26 MYL United Kingdom
27 MYL United Kingdom
28 MYL United Kingdom
29 MYL United Kingdom
30 MYL United Kingdom
31 MYL United Kingdom
32 MYL United Kingdom
33 MRK New Jersey; U.S.A
34 MRK New Jersey; U.S.A
35 MRK New Jersey; U.S.A
36 MRK New Jersey; U.S.A
37 MRK New Jersey; U.S.A
38 MRK New Jersey; U.S.A
39 MRK New Jersey; U.S.A
40 MRK New Jersey; U.S.A
41 LLY Indiana; U.S.A
42 LLY Indiana; U.S.A
43 LLY Indiana; U.S.A
44 LLY Indiana; U.S.A
45 LLY Indiana; U.S.A
46 LLY Indiana; U.S.A
47 LLY Indiana; U.S.A
48 LLY Indiana; U.S.A
49 JNJ New Jersey; U.S.A
50 JNJ New Jersey; U.S.A
51 JNJ New Jersey; U.S.A
52 JNJ New Jersey; U.S.A
53 JNJ New Jersey; U.S.A
54 JNJ New Jersey; U.S.A
55 JNJ New Jersey; U.S.A
56 JNJ New Jersey; U.S.A
57 GILD California; U.S.A
58 GILD California; U.S.A
59 GILD California; U.S.A
60 GILD California; U.S.A
61 GILD California; U.S.A
62 GILD California; U.S.A
63 GILD California; U.S.A
64 GILD California; U.S.A
65 BMY New York; U.S.A
66 BMY New York; U.S.A
67 BMY New York; U.S.A
68 BMY New York; U.S.A
69 BMY New York; U.S.A
70 BMY New York; U.S.A
71 BMY New York; U.S.A
72 BMY New York; U.S.A
73 BIIB Massachusetts; U.S.A
74 BIIB Massachusetts; U.S.A
75 BIIB Massachusetts; U.S.A
76 BIIB Massachusetts; U.S.A
77 BIIB Massachusetts; U.S.A
78 BIIB Massachusetts; U.S.A
79 BIIB Massachusetts; U.S.A
80 BIIB Massachusetts; U.S.A
81 AMGN California; U.S.A
82 AMGN California; U.S.A
83 AMGN California; U.S.A
84 AMGN California; U.S.A
85 AMGN California; U.S.A
86 AMGN California; U.S.A
87 AMGN California; U.S.A
88 AMGN California; U.S.A
89 AGN Ireland
90 AGN Ireland
91 AGN Ireland
92 AGN Ireland
93 AGN Ireland
94 AGN Ireland
95 AGN Ireland
96 AGN Ireland
97 ABBV Illinois; U.S.A
98 ABBV Illinois; U.S.A
99 ABBV Illinois; U.S.A
100 ABBV Illinois; U.S.A
101 ABBV Illinois; U.S.A
102 ABBV Illinois; U.S.A
103 ABBV Illinois; U.S.A
104 ABBV Illinois; U.S.Adrug_cos %>%
select(ticker, starts_with("r"))
ticker ros roe
1 ZTS 0.101 0.069
2 ZTS 0.171 0.113
3 ZTS 0.176 0.612
4 ZTS 0.195 0.465
5 ZTS 0.140 0.285
6 ZTS 0.286 0.587
7 ZTS 0.321 0.488
8 ZTS 0.326 0.694
9 PRGO 0.178 0.248
10 PRGO 0.183 0.236
11 PRGO 0.190 0.205
12 PRGO 0.104 0.033
13 PRGO 0.096 0.014
14 PRGO -0.877 -0.498
15 PRGO 0.091 0.020
16 PRGO 0.088 0.022
17 PFE 0.223 0.114
18 PFE 0.307 0.179
19 PFE 0.510 0.279
20 PFE 0.247 0.120
21 PFE 0.183 0.105
22 PFE 0.158 0.116
23 PFE 0.233 0.342
24 PFE 0.221 0.162
25 MYL 0.161 0.146
26 MYL 0.163 0.184
27 MYL 0.153 0.209
28 MYL 0.169 0.283
29 MYL 0.133 0.089
30 MYL 0.052 0.044
31 MYL 0.121 0.054
32 MYL 0.074 0.028
33 MRK 0.150 0.114
34 MRK 0.182 0.113
35 MRK 0.123 0.089
36 MRK 0.409 0.248
37 MRK 0.136 0.096
38 MRK 0.117 0.092
39 MRK 0.162 0.063
40 MRK 0.206 0.199
41 LLY 0.220 0.306
42 LLY 0.239 0.273
43 LLY 0.255 0.290
44 LLY 0.153 0.138
45 LLY 0.140 0.162
46 LLY 0.159 0.185
47 LLY 0.096 -0.015
48 LLY 0.155 0.264
49 JNJ 0.199 0.161
50 JNJ 0.218 0.173
51 JNJ 0.224 0.197
52 JNJ 0.284 0.217
53 JNJ 0.282 0.219
54 JNJ 0.286 0.229
55 JNJ 0.243 0.019
56 JNJ 0.233 0.244
57 GILD 0.462 0.451
58 GILD 0.411 0.312
59 GILD 0.405 0.283
60 GILD 0.615 0.828
61 GILD 0.685 1.043
62 GILD 0.595 0.835
63 GILD 0.560 0.209
64 GILD 0.401 0.252
65 BMY 0.256 0.229
66 BMY 0.102 0.131
67 BMY 0.175 0.177
68 BMY 0.148 0.132
69 BMY 0.121 0.104
70 BMY 0.302 0.292
71 BMY 0.249 0.072
72 BMY 0.263 0.373
73 BIIB 0.333 0.204
74 BIIB 0.335 0.211
75 BIIB 0.355 0.233
76 BIIB 0.404 0.294
77 BIIB 0.437 0.321
78 BIIB 0.431 0.322
79 BIIB 0.407 0.209
80 BIIB 0.435 0.334
81 AMGN 0.305 0.158
82 AMGN 0.351 0.225
83 AMGN 0.337 0.242
84 AMGN 0.332 0.210
85 AMGN 0.419 0.252
86 AMGN 0.453 0.259
87 AMGN 0.477 0.066
88 AMGN 0.461 0.585
89 AGN 0.115 0.075
90 AGN 0.060 0.026
91 AGN -0.256 -0.147
92 AGN -0.370 -0.085
93 AGN 0.276 0.050
94 AGN 0.986 0.184
95 AGN -0.609 -0.060
96 AGN -0.377 -0.074
97 ABBV 0.209 0.248
98 ABBV 0.316 0.690
99 ABBV 0.299 1.132
100 ABBV 0.138 0.435
101 ABBV 0.321 1.311
102 ABBV 0.345 1.113
103 ABBV 0.309 0.932
104 ABBV 0.194 -2.033drug_cos %>%
select(year, ends_with("margin"))
year ebitdamargin grossmargin netmargin
1 2011 0.149 0.610 0.058
2 2012 0.217 0.640 0.101
3 2013 0.222 0.634 0.111
4 2014 0.238 0.641 0.122
5 2015 0.182 0.635 0.071
6 2016 0.335 0.659 0.168
7 2017 0.366 0.666 0.163
8 2018 0.379 0.672 0.245
9 2011 0.216 0.343 0.123
10 2012 0.226 0.345 0.127
11 2013 0.236 0.362 0.125
12 2014 0.157 0.371 0.059
13 2015 0.157 0.389 0.032
14 2016 -0.791 0.389 -0.760
15 2017 0.181 0.400 0.024
16 2018 0.178 0.387 0.028
17 2011 0.371 0.795 0.164
18 2012 0.447 0.820 0.267
19 2013 0.634 0.814 0.427
20 2014 0.359 0.807 0.184
21 2015 0.289 0.803 0.142
22 2016 0.267 0.767 0.137
23 2017 0.353 0.786 0.406
24 2018 0.340 0.790 0.208
25 2011 0.245 0.418 0.088
26 2012 0.244 0.428 0.094
27 2013 0.228 0.440 0.090
28 2014 0.242 0.457 0.120
29 2015 0.243 0.447 0.090
30 2016 0.190 0.424 0.043
31 2017 0.272 0.402 0.058
32 2018 0.258 0.350 0.031
33 2011 0.305 0.649 0.131
34 2012 0.330 0.652 0.130
35 2013 0.282 0.615 0.100
36 2014 0.567 0.603 0.282
37 2015 0.298 0.622 0.112
38 2016 0.254 0.648 0.098
39 2017 0.278 0.678 0.060
40 2018 0.313 0.681 0.147
41 2011 0.277 0.791 0.179
42 2012 0.304 0.788 0.181
43 2013 0.317 0.788 0.203
44 2014 0.223 0.749 0.122
45 2015 0.211 0.748 0.121
46 2016 0.230 0.731 0.129
47 2017 0.165 0.731 -0.009
48 2018 0.220 0.738 0.132
49 2011 0.247 0.687 0.149
50 2012 0.272 0.678 0.161
51 2013 0.281 0.687 0.194
52 2014 0.336 0.694 0.220
53 2015 0.335 0.693 0.220
54 2016 0.338 0.697 0.230
55 2017 0.317 0.667 0.017
56 2018 0.318 0.668 0.188
57 2011 0.498 0.747 0.334
58 2012 0.440 0.745 0.267
59 2013 0.435 0.745 0.275
60 2014 0.657 0.848 0.486
61 2015 0.718 0.877 0.555
62 2016 0.633 0.860 0.444
63 2017 0.610 0.833 0.177
64 2018 0.465 0.781 0.247
65 2011 0.285 0.736 0.175
66 2012 0.141 0.738 0.111
67 2013 0.222 0.718 0.156
68 2014 0.178 0.752 0.126
69 2015 0.144 0.764 0.095
70 2016 0.322 0.744 0.229
71 2017 0.286 0.707 0.048
72 2018 0.292 0.710 0.218
73 2011 0.404 0.908 0.245
74 2012 0.402 0.901 0.250
75 2013 0.432 0.876 0.269
76 2014 0.475 0.879 0.302
77 2015 0.493 0.885 0.330
78 2016 0.491 0.871 0.323
79 2017 0.495 0.867 0.207
80 2018 0.511 0.865 0.329
81 2011 0.374 0.826 0.236
82 2012 0.414 0.815 0.252
83 2013 0.405 0.821 0.272
84 2014 0.436 0.780 0.257
85 2015 0.516 0.805 0.320
86 2016 0.545 0.819 0.336
87 2017 0.563 0.822 0.087
88 2018 0.543 0.827 0.353
89 2011 0.213 0.440 0.057
90 2012 0.158 0.426 0.016
91 2013 0.146 0.368 -0.288
92 2014 0.234 0.635 -0.349
93 2015 0.749 0.783 0.290
94 2016 1.441 0.872 1.009
95 2017 -0.146 0.864 -0.276
96 2018 0.050 0.861 -0.326
97 2011 0.282 0.734 0.197
98 2012 0.379 0.755 0.287
99 2013 0.346 0.756 0.220
100 2014 0.178 0.778 0.089
101 2015 0.357 0.803 0.225
102 2016 0.392 0.773 0.232
103 2017 0.363 0.750 0.188
104 2018 0.247 0.764 0.174Use group_by to set up data for operations by group
group_by
drug_cos %>%
group_by(ticker)
# A tibble: 104 x 9
# Groups: ticker [13]
ticker name location ebitdamargin grossmargin netmargin ros
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 ZTS Zoet~ New Jer~ 0.149 0.61 0.058 0.101
2 ZTS Zoet~ New Jer~ 0.217 0.64 0.101 0.171
3 ZTS Zoet~ New Jer~ 0.222 0.634 0.111 0.176
4 ZTS Zoet~ New Jer~ 0.238 0.641 0.122 0.195
5 ZTS Zoet~ New Jer~ 0.182 0.635 0.071 0.14
6 ZTS Zoet~ New Jer~ 0.335 0.659 0.168 0.286
7 ZTS Zoet~ New Jer~ 0.366 0.666 0.163 0.321
8 ZTS Zoet~ New Jer~ 0.379 0.672 0.245 0.326
9 PRGO PERR~ Ireland 0.216 0.343 0.123 0.178
10 PRGO PERR~ Ireland 0.226 0.345 0.127 0.183
# ... with 94 more rows, and 2 more variables: roe <dbl>, year <int>drug_cos %>%
group_by(year)
# A tibble: 104 x 9
# Groups: year [8]
ticker name location ebitdamargin grossmargin netmargin ros
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 ZTS Zoet~ New Jer~ 0.149 0.61 0.058 0.101
2 ZTS Zoet~ New Jer~ 0.217 0.64 0.101 0.171
3 ZTS Zoet~ New Jer~ 0.222 0.634 0.111 0.176
4 ZTS Zoet~ New Jer~ 0.238 0.641 0.122 0.195
5 ZTS Zoet~ New Jer~ 0.182 0.635 0.071 0.14
6 ZTS Zoet~ New Jer~ 0.335 0.659 0.168 0.286
7 ZTS Zoet~ New Jer~ 0.366 0.666 0.163 0.321
8 ZTS Zoet~ New Jer~ 0.379 0.672 0.245 0.326
9 PRGO PERR~ Ireland 0.216 0.343 0.123 0.178
10 PRGO PERR~ Ireland 0.226 0.345 0.127 0.183
# ... with 94 more rows, and 2 more variables: roe <dbl>, year <int>Use `summarize to calculate summary statistics
- Maximum
roeto all companies
drug_cos %>%
summarize(max_roe = max(roe))
max_roe
1 1.311maximum roe for each year
drug_cos %>%
group_by(year) %>%
summarize(max_roe = max(roe))
# A tibble: 8 x 2
year max_roe
* <int> <dbl>
1 2011 0.451
2 2012 0.69
3 2013 1.13
4 2014 0.828
5 2015 1.31
6 2016 1.11
7 2017 0.932
8 2018 0.694maximum roe for each ticker
drug_cos %>%
group_by(ticker) %>%
summarize(max_roe = max(roe))
# A tibble: 13 x 2
ticker max_roe
* <chr> <dbl>
1 ABBV 1.31
2 AGN 0.184
3 AMGN 0.585
4 BIIB 0.334
5 BMY 0.373
6 GILD 1.04
7 JNJ 0.244
8 LLY 0.306
9 MRK 0.248
10 MYL 0.283
11 PFE 0.342
12 PRGO 0.248
13 ZTS 0.694Question: summarize
Mean for year
*Find the mean SEE QUIZ for each year to call the variable mean_SEE QUIZ
*Extract the mean for SEE QUIZ
drug_cos %>%
group_by(ticker) %>%
summarize(mean_grossmargin = mean(grossmargin))
# A tibble: 13 x 2
ticker mean_grossmargin
* <chr> <dbl>
1 ABBV 0.764
2 AGN 0.656
3 AMGN 0.814
4 BIIB 0.882
5 BMY 0.734
6 GILD 0.804
7 JNJ 0.684
8 LLY 0.758
9 MRK 0.644
10 MYL 0.421
11 PFE 0.798
12 PRGO 0.373
13 ZTS 0.645*The mean SEE QUIZ for SEE QUIZ is ??? or ???%
Median for year
- Find the median SEE QUIZ for each
yearand call the variable median_SEE QUIZ*
Extract the median for SEE QUIZ*
- Pick a ratio and a year and compare the companies.
drug_cos %>%
filter(year == 2018) %>%
ggplot(aes(x = netmargin, y = reorder(name, netmargin))) +
geom_col() +
scale_x_continuous(labels = scales::percent) +
labs(title = "Comparison of net margin",
subtitle = "for drug companies during 2018",
x = NULL, y = NULL) +
theme_classic()
- Pick a company and a ratio and compare the ratio over time
drug_cos %>%
filter(ticker == "PFE") %>%
ggplot(aes(x = year, y =netmargin)) +
geom_col() +
scale_y_continuous(labels = scales::percent)
labs(title = "Comparison of net margin",
subtitle = "for Pzizer from 2011 to 2018",
x = NULL, y = NULL) +
theme_classic()
NULL ggsave(filename = "preview.png",
path = here::here("_posts", "2021-03-09-data-manipulation"))