Tugas Akhir Mandarel
Engine SQL
Database yang digunakan pada publikasi ini berasal dari sampel chinook . Supaya dapat mengakses dan mengolah database ini adapun packages yang akan digunakan yaitu DBI dan RSQLite.
install.packages(c("RSQLite", "DBI"), dependencies = TRUE)Selanjutnya package tidyverse yang mencakup beberapa package diretrieve. Fungsi dalam suatu package dapat juga dipanggil tanpa perintah library() atau require() jika sintaks yang ditulis menyertakan nama package tempat fungsi tersebut berasal. Penyertaan ini dengan menggunakan tanda ::.
library(tidyverse)
library(RSQLite)
library(DBI)Secara umum, koneksi terhadap database pada R dapat menggunakan sintaks berikut: DBI::dbConnect(RSQLite::SQLite(), path = ":dbname:")
chinook<-DBI::dbConnect(RSQLite::SQLite(), "C:/sqlite/chinook.db")
RSQLite::dbListTables(chinook)## [1] "albums" "artists" "customers" "employees"
## [5] "genres" "invoice_items" "invoices" "media_types"
## [9] "playlist_track" "playlists" "sqlite_sequence" "sqlite_stat1"
## [13] "tracks"Setelah melakukan dbConnect() kita dapat melakukan perintah SQL.
SELECT
*
FROM
invoices;| InvoiceId | CustomerId | InvoiceDate | BillingAddress | BillingCity | BillingState | BillingCountry | BillingPostalCode | Total |
|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 2009-01-01 00:00:00 | Theodor-Heuss-Straße 34 | Stuttgart | NA | Germany | 70174 | 1.98 |
| 2 | 4 | 2009-01-02 00:00:00 | Ullevålsveien 14 | Oslo | NA | Norway | 0171 | 3.96 |
| 3 | 8 | 2009-01-03 00:00:00 | Grétrystraat 63 | Brussels | NA | Belgium | 1000 | 5.94 |
| 4 | 14 | 2009-01-06 00:00:00 | 8210 111 ST NW | Edmonton | AB | Canada | T6G 2C7 | 8.91 |
| 5 | 23 | 2009-01-11 00:00:00 | 69 Salem Street | Boston | MA | USA | 2113 | 13.86 |
| 6 | 37 | 2009-01-19 00:00:00 | Berger Straße 10 | Frankfurt | NA | Germany | 60316 | 0.99 |
| 7 | 38 | 2009-02-01 00:00:00 | Barbarossastraße 19 | Berlin | NA | Germany | 10779 | 1.98 |
| 8 | 40 | 2009-02-01 00:00:00 | 8, Rue Hanovre | Paris | NA | France | 75002 | 1.98 |
| 9 | 42 | 2009-02-02 00:00:00 | 9, Place Louis Barthou | Bordeaux | NA | France | 33000 | 3.96 |
| 10 | 46 | 2009-02-03 00:00:00 | 3 Chatham Street | Dublin | Dublin | Ireland | NA | 5.94 |
Setelah selesai mengolah database tersebut, saat akan memutuskan hubungan dapat menggunakan fungsi dbDisconnect() dan ketika akan menyambungkan kembali cukup menggunakan kembali dbConnect()
dbDisconnect(chinook)Menggunakan DPLYR
chinook<-DBI::dbConnect(RSQLite::SQLite(), "C:/sqlite/chinook.db")
RSQLite::dbListTables(chinook)## [1] "albums" "artists" "customers" "employees"
## [5] "genres" "invoice_items" "invoices" "media_types"
## [9] "playlist_track" "playlists" "sqlite_sequence" "sqlite_stat1"
## [13] "tracks"dplyr::tbl(chinook,"invoices")## # Source: table<invoices> [?? x 9]
## # Database: sqlite 3.37.0 [C:\sqlite\chinook.db]
## InvoiceId CustomerId InvoiceDate BillingAddress BillingCity BillingState
## <int> <int> <chr> <chr> <chr> <chr>
## 1 1 2 2009-01-01 00~ Theodor-Heuss-S~ Stuttgart <NA>
## 2 2 4 2009-01-02 00~ Ullevålsveien 14 Oslo <NA>
## 3 3 8 2009-01-03 00~ Grétrystraat 63 Brussels <NA>
## 4 4 14 2009-01-06 00~ 8210 111 ST NW Edmonton AB
## 5 5 23 2009-01-11 00~ 69 Salem Street Boston MA
## 6 6 37 2009-01-19 00~ Berger Straße 10 Frankfurt <NA>
## 7 7 38 2009-02-01 00~ Barbarossastraß~ Berlin <NA>
## 8 8 40 2009-02-01 00~ 8, Rue Hanovre Paris <NA>
## 9 9 42 2009-02-02 00~ 9, Place Louis ~ Bordeaux <NA>
## 10 10 46 2009-02-03 00~ 3 Chatham Street Dublin Dublin
## # ... with more rows, and 3 more variables: BillingCountry <chr>,
## # BillingPostalCode <chr>, Total <dbl>invoices <- dplyr::tbl(chinook,"invoices")
class(invoices)## [1] "tbl_SQLiteConnection" "tbl_dbi" "tbl_sql"
## [4] "tbl_lazy" "tbl"invoices## # Source: table<invoices> [?? x 9]
## # Database: sqlite 3.37.0 [C:\sqlite\chinook.db]
## InvoiceId CustomerId InvoiceDate BillingAddress BillingCity BillingState
## <int> <int> <chr> <chr> <chr> <chr>
## 1 1 2 2009-01-01 00~ Theodor-Heuss-S~ Stuttgart <NA>
## 2 2 4 2009-01-02 00~ Ullevålsveien 14 Oslo <NA>
## 3 3 8 2009-01-03 00~ Grétrystraat 63 Brussels <NA>
## 4 4 14 2009-01-06 00~ 8210 111 ST NW Edmonton AB
## 5 5 23 2009-01-11 00~ 69 Salem Street Boston MA
## 6 6 37 2009-01-19 00~ Berger Straße 10 Frankfurt <NA>
## 7 7 38 2009-02-01 00~ Barbarossastraß~ Berlin <NA>
## 8 8 40 2009-02-01 00~ 8, Rue Hanovre Paris <NA>
## 9 9 42 2009-02-02 00~ 9, Place Louis ~ Bordeaux <NA>
## 10 10 46 2009-02-03 00~ 3 Chatham Street Dublin Dublin
## # ... with more rows, and 3 more variables: BillingCountry <chr>,
## # BillingPostalCode <chr>, Total <dbl>query <- invoices %>% select(-InvoiceDate)
query## # Source: lazy query [?? x 8]
## # Database: sqlite 3.37.0 [C:\sqlite\chinook.db]
## InvoiceId CustomerId BillingAddress BillingCity BillingState BillingCountry
## <int> <int> <chr> <chr> <chr> <chr>
## 1 1 2 Theodor-Heuss-S~ Stuttgart <NA> Germany
## 2 2 4 Ullevålsveien 14 Oslo <NA> Norway
## 3 3 8 Grétrystraat 63 Brussels <NA> Belgium
## 4 4 14 8210 111 ST NW Edmonton AB Canada
## 5 5 23 69 Salem Street Boston MA USA
## 6 6 37 Berger Straße 10 Frankfurt <NA> Germany
## 7 7 38 Barbarossastraß~ Berlin <NA> Germany
## 8 8 40 8, Rue Hanovre Paris <NA> France
## 9 9 42 9, Place Louis ~ Bordeaux <NA> France
## 10 10 46 3 Chatham Street Dublin Dublin Ireland
## # ... with more rows, and 2 more variables: BillingPostalCode <chr>,
## # Total <dbl>dplyr::show_query(query)## <SQL>
## SELECT `InvoiceId`, `CustomerId`, `BillingAddress`, `BillingCity`, `BillingState`, `BillingCountry`, `BillingPostalCode`, `Total`
## FROM `invoices`Data Wrangling
Dataset yang digunakan adalah storms yang tersedia pada package default R datasets.
library(datasets)
library(help = "datasets")
Theoph ## Subject Wt Dose Time conc
## 1 1 79.6 4.02 0.00 0.74
## 2 1 79.6 4.02 0.25 2.84
## 3 1 79.6 4.02 0.57 6.57
## 4 1 79.6 4.02 1.12 10.50
## 5 1 79.6 4.02 2.02 9.66
## 6 1 79.6 4.02 3.82 8.58
## 7 1 79.6 4.02 5.10 8.36
## 8 1 79.6 4.02 7.03 7.47
## 9 1 79.6 4.02 9.05 6.89
## 10 1 79.6 4.02 12.12 5.94
## 11 1 79.6 4.02 24.37 3.28
## 12 2 72.4 4.40 0.00 0.00
## 13 2 72.4 4.40 0.27 1.72
## 14 2 72.4 4.40 0.52 7.91
## 15 2 72.4 4.40 1.00 8.31
## 16 2 72.4 4.40 1.92 8.33
## 17 2 72.4 4.40 3.50 6.85
## 18 2 72.4 4.40 5.02 6.08
## 19 2 72.4 4.40 7.03 5.40
## 20 2 72.4 4.40 9.00 4.55
## 21 2 72.4 4.40 12.00 3.01
## 22 2 72.4 4.40 24.30 0.90
## 23 3 70.5 4.53 0.00 0.00
## 24 3 70.5 4.53 0.27 4.40
## 25 3 70.5 4.53 0.58 6.90
## 26 3 70.5 4.53 1.02 8.20
## 27 3 70.5 4.53 2.02 7.80
## 28 3 70.5 4.53 3.62 7.50
## 29 3 70.5 4.53 5.08 6.20
## 30 3 70.5 4.53 7.07 5.30
## 31 3 70.5 4.53 9.00 4.90
## 32 3 70.5 4.53 12.15 3.70
## 33 3 70.5 4.53 24.17 1.05
## 34 4 72.7 4.40 0.00 0.00
## 35 4 72.7 4.40 0.35 1.89
## 36 4 72.7 4.40 0.60 4.60
## 37 4 72.7 4.40 1.07 8.60
## 38 4 72.7 4.40 2.13 8.38
## 39 4 72.7 4.40 3.50 7.54
## 40 4 72.7 4.40 5.02 6.88
## 41 4 72.7 4.40 7.02 5.78
## 42 4 72.7 4.40 9.02 5.33
## 43 4 72.7 4.40 11.98 4.19
## 44 4 72.7 4.40 24.65 1.15
## 45 5 54.6 5.86 0.00 0.00
## 46 5 54.6 5.86 0.30 2.02
## 47 5 54.6 5.86 0.52 5.63
## 48 5 54.6 5.86 1.00 11.40
## 49 5 54.6 5.86 2.02 9.33
## 50 5 54.6 5.86 3.50 8.74
## 51 5 54.6 5.86 5.02 7.56
## 52 5 54.6 5.86 7.02 7.09
## 53 5 54.6 5.86 9.10 5.90
## 54 5 54.6 5.86 12.00 4.37
## 55 5 54.6 5.86 24.35 1.57
## 56 6 80.0 4.00 0.00 0.00
## 57 6 80.0 4.00 0.27 1.29
## 58 6 80.0 4.00 0.58 3.08
## 59 6 80.0 4.00 1.15 6.44
## 60 6 80.0 4.00 2.03 6.32
## 61 6 80.0 4.00 3.57 5.53
## 62 6 80.0 4.00 5.00 4.94
## 63 6 80.0 4.00 7.00 4.02
## 64 6 80.0 4.00 9.22 3.46
## 65 6 80.0 4.00 12.10 2.78
## 66 6 80.0 4.00 23.85 0.92
## 67 7 64.6 4.95 0.00 0.15
## 68 7 64.6 4.95 0.25 0.85
## 69 7 64.6 4.95 0.50 2.35
## 70 7 64.6 4.95 1.02 5.02
## 71 7 64.6 4.95 2.02 6.58
## 72 7 64.6 4.95 3.48 7.09
## 73 7 64.6 4.95 5.00 6.66
## 74 7 64.6 4.95 6.98 5.25
## 75 7 64.6 4.95 9.00 4.39
## 76 7 64.6 4.95 12.05 3.53
## 77 7 64.6 4.95 24.22 1.15
## 78 8 70.5 4.53 0.00 0.00
## 79 8 70.5 4.53 0.25 3.05
## 80 8 70.5 4.53 0.52 3.05
## 81 8 70.5 4.53 0.98 7.31
## 82 8 70.5 4.53 2.02 7.56
## 83 8 70.5 4.53 3.53 6.59
## 84 8 70.5 4.53 5.05 5.88
## 85 8 70.5 4.53 7.15 4.73
## 86 8 70.5 4.53 9.07 4.57
## 87 8 70.5 4.53 12.10 3.00
## 88 8 70.5 4.53 24.12 1.25
## 89 9 86.4 3.10 0.00 0.00
## 90 9 86.4 3.10 0.30 7.37
## 91 9 86.4 3.10 0.63 9.03
## 92 9 86.4 3.10 1.05 7.14
## 93 9 86.4 3.10 2.02 6.33
## 94 9 86.4 3.10 3.53 5.66
## 95 9 86.4 3.10 5.02 5.67
## 96 9 86.4 3.10 7.17 4.24
## 97 9 86.4 3.10 8.80 4.11
## 98 9 86.4 3.10 11.60 3.16
## 99 9 86.4 3.10 24.43 1.12
## 100 10 58.2 5.50 0.00 0.24
## 101 10 58.2 5.50 0.37 2.89
## 102 10 58.2 5.50 0.77 5.22
## 103 10 58.2 5.50 1.02 6.41
## 104 10 58.2 5.50 2.05 7.83
## 105 10 58.2 5.50 3.55 10.21
## 106 10 58.2 5.50 5.05 9.18
## 107 10 58.2 5.50 7.08 8.02
## 108 10 58.2 5.50 9.38 7.14
## 109 10 58.2 5.50 12.10 5.68
## 110 10 58.2 5.50 23.70 2.42
## 111 11 65.0 4.92 0.00 0.00
## 112 11 65.0 4.92 0.25 4.86
## 113 11 65.0 4.92 0.50 7.24
## 114 11 65.0 4.92 0.98 8.00
## 115 11 65.0 4.92 1.98 6.81
## 116 11 65.0 4.92 3.60 5.87
## 117 11 65.0 4.92 5.02 5.22
## 118 11 65.0 4.92 7.03 4.45
## 119 11 65.0 4.92 9.03 3.62
## 120 11 65.0 4.92 12.12 2.69
## 121 11 65.0 4.92 24.08 0.86
## 122 12 60.5 5.30 0.00 0.00
## 123 12 60.5 5.30 0.25 1.25
## 124 12 60.5 5.30 0.50 3.96
## 125 12 60.5 5.30 1.00 7.82
## 126 12 60.5 5.30 2.00 9.72
## 127 12 60.5 5.30 3.52 9.75
## 128 12 60.5 5.30 5.07 8.57
## 129 12 60.5 5.30 7.07 6.59
## 130 12 60.5 5.30 9.03 6.11
## 131 12 60.5 5.30 12.05 4.57
## 132 12 60.5 5.30 24.15 1.17Theop Kerangka data Theoph memiliki 132 baris dan 5 kolom data dari eksperimen farmakokinetik teofilin. Formatnya Objek kelas c("nfnGroupedData", "nfGroupedData", "groupedData", "data.frame") Untuk mengetahui informasi terkait dataset dapat menggunakan sintaks ?dan meletakannya sebelum nama dataset .
?Theoph
View(Theoph)Dataset tersebut akan dilakukan perintah arrange , mutate ,filter,select, dan summarise.
Theoph %>% select(Subject, Wt, Dose, Time,conc)## Subject Wt Dose Time conc
## 1 1 79.6 4.02 0.00 0.74
## 2 1 79.6 4.02 0.25 2.84
## 3 1 79.6 4.02 0.57 6.57
## 4 1 79.6 4.02 1.12 10.50
## 5 1 79.6 4.02 2.02 9.66
## 6 1 79.6 4.02 3.82 8.58
## 7 1 79.6 4.02 5.10 8.36
## 8 1 79.6 4.02 7.03 7.47
## 9 1 79.6 4.02 9.05 6.89
## 10 1 79.6 4.02 12.12 5.94
## 11 1 79.6 4.02 24.37 3.28
## 12 2 72.4 4.40 0.00 0.00
## 13 2 72.4 4.40 0.27 1.72
## 14 2 72.4 4.40 0.52 7.91
## 15 2 72.4 4.40 1.00 8.31
## 16 2 72.4 4.40 1.92 8.33
## 17 2 72.4 4.40 3.50 6.85
## 18 2 72.4 4.40 5.02 6.08
## 19 2 72.4 4.40 7.03 5.40
## 20 2 72.4 4.40 9.00 4.55
## 21 2 72.4 4.40 12.00 3.01
## 22 2 72.4 4.40 24.30 0.90
## 23 3 70.5 4.53 0.00 0.00
## 24 3 70.5 4.53 0.27 4.40
## 25 3 70.5 4.53 0.58 6.90
## 26 3 70.5 4.53 1.02 8.20
## 27 3 70.5 4.53 2.02 7.80
## 28 3 70.5 4.53 3.62 7.50
## 29 3 70.5 4.53 5.08 6.20
## 30 3 70.5 4.53 7.07 5.30
## 31 3 70.5 4.53 9.00 4.90
## 32 3 70.5 4.53 12.15 3.70
## 33 3 70.5 4.53 24.17 1.05
## 34 4 72.7 4.40 0.00 0.00
## 35 4 72.7 4.40 0.35 1.89
## 36 4 72.7 4.40 0.60 4.60
## 37 4 72.7 4.40 1.07 8.60
## 38 4 72.7 4.40 2.13 8.38
## 39 4 72.7 4.40 3.50 7.54
## 40 4 72.7 4.40 5.02 6.88
## 41 4 72.7 4.40 7.02 5.78
## 42 4 72.7 4.40 9.02 5.33
## 43 4 72.7 4.40 11.98 4.19
## 44 4 72.7 4.40 24.65 1.15
## 45 5 54.6 5.86 0.00 0.00
## 46 5 54.6 5.86 0.30 2.02
## 47 5 54.6 5.86 0.52 5.63
## 48 5 54.6 5.86 1.00 11.40
## 49 5 54.6 5.86 2.02 9.33
## 50 5 54.6 5.86 3.50 8.74
## 51 5 54.6 5.86 5.02 7.56
## 52 5 54.6 5.86 7.02 7.09
## 53 5 54.6 5.86 9.10 5.90
## 54 5 54.6 5.86 12.00 4.37
## 55 5 54.6 5.86 24.35 1.57
## 56 6 80.0 4.00 0.00 0.00
## 57 6 80.0 4.00 0.27 1.29
## 58 6 80.0 4.00 0.58 3.08
## 59 6 80.0 4.00 1.15 6.44
## 60 6 80.0 4.00 2.03 6.32
## 61 6 80.0 4.00 3.57 5.53
## 62 6 80.0 4.00 5.00 4.94
## 63 6 80.0 4.00 7.00 4.02
## 64 6 80.0 4.00 9.22 3.46
## 65 6 80.0 4.00 12.10 2.78
## 66 6 80.0 4.00 23.85 0.92
## 67 7 64.6 4.95 0.00 0.15
## 68 7 64.6 4.95 0.25 0.85
## 69 7 64.6 4.95 0.50 2.35
## 70 7 64.6 4.95 1.02 5.02
## 71 7 64.6 4.95 2.02 6.58
## 72 7 64.6 4.95 3.48 7.09
## 73 7 64.6 4.95 5.00 6.66
## 74 7 64.6 4.95 6.98 5.25
## 75 7 64.6 4.95 9.00 4.39
## 76 7 64.6 4.95 12.05 3.53
## 77 7 64.6 4.95 24.22 1.15
## 78 8 70.5 4.53 0.00 0.00
## 79 8 70.5 4.53 0.25 3.05
## 80 8 70.5 4.53 0.52 3.05
## 81 8 70.5 4.53 0.98 7.31
## 82 8 70.5 4.53 2.02 7.56
## 83 8 70.5 4.53 3.53 6.59
## 84 8 70.5 4.53 5.05 5.88
## 85 8 70.5 4.53 7.15 4.73
## 86 8 70.5 4.53 9.07 4.57
## 87 8 70.5 4.53 12.10 3.00
## 88 8 70.5 4.53 24.12 1.25
## 89 9 86.4 3.10 0.00 0.00
## 90 9 86.4 3.10 0.30 7.37
## 91 9 86.4 3.10 0.63 9.03
## 92 9 86.4 3.10 1.05 7.14
## 93 9 86.4 3.10 2.02 6.33
## 94 9 86.4 3.10 3.53 5.66
## 95 9 86.4 3.10 5.02 5.67
## 96 9 86.4 3.10 7.17 4.24
## 97 9 86.4 3.10 8.80 4.11
## 98 9 86.4 3.10 11.60 3.16
## 99 9 86.4 3.10 24.43 1.12
## 100 10 58.2 5.50 0.00 0.24
## 101 10 58.2 5.50 0.37 2.89
## 102 10 58.2 5.50 0.77 5.22
## 103 10 58.2 5.50 1.02 6.41
## 104 10 58.2 5.50 2.05 7.83
## 105 10 58.2 5.50 3.55 10.21
## 106 10 58.2 5.50 5.05 9.18
## 107 10 58.2 5.50 7.08 8.02
## 108 10 58.2 5.50 9.38 7.14
## 109 10 58.2 5.50 12.10 5.68
## 110 10 58.2 5.50 23.70 2.42
## 111 11 65.0 4.92 0.00 0.00
## 112 11 65.0 4.92 0.25 4.86
## 113 11 65.0 4.92 0.50 7.24
## 114 11 65.0 4.92 0.98 8.00
## 115 11 65.0 4.92 1.98 6.81
## 116 11 65.0 4.92 3.60 5.87
## 117 11 65.0 4.92 5.02 5.22
## 118 11 65.0 4.92 7.03 4.45
## 119 11 65.0 4.92 9.03 3.62
## 120 11 65.0 4.92 12.12 2.69
## 121 11 65.0 4.92 24.08 0.86
## 122 12 60.5 5.30 0.00 0.00
## 123 12 60.5 5.30 0.25 1.25
## 124 12 60.5 5.30 0.50 3.96
## 125 12 60.5 5.30 1.00 7.82
## 126 12 60.5 5.30 2.00 9.72
## 127 12 60.5 5.30 3.52 9.75
## 128 12 60.5 5.30 5.07 8.57
## 129 12 60.5 5.30 7.07 6.59
## 130 12 60.5 5.30 9.03 6.11
## 131 12 60.5 5.30 12.05 4.57
## 132 12 60.5 5.30 24.15 1.17Theoph %>% arrange(desc(Time))## Subject Wt Dose Time conc
## 1 4 72.7 4.40 24.65 1.15
## 2 9 86.4 3.10 24.43 1.12
## 3 1 79.6 4.02 24.37 3.28
## 4 5 54.6 5.86 24.35 1.57
## 5 2 72.4 4.40 24.30 0.90
## 6 7 64.6 4.95 24.22 1.15
## 7 3 70.5 4.53 24.17 1.05
## 8 12 60.5 5.30 24.15 1.17
## 9 8 70.5 4.53 24.12 1.25
## 10 11 65.0 4.92 24.08 0.86
## 11 6 80.0 4.00 23.85 0.92
## 12 10 58.2 5.50 23.70 2.42
## 13 3 70.5 4.53 12.15 3.70
## 14 1 79.6 4.02 12.12 5.94
## 15 11 65.0 4.92 12.12 2.69
## 16 6 80.0 4.00 12.10 2.78
## 17 8 70.5 4.53 12.10 3.00
## 18 10 58.2 5.50 12.10 5.68
## 19 7 64.6 4.95 12.05 3.53
## 20 12 60.5 5.30 12.05 4.57
## 21 2 72.4 4.40 12.00 3.01
## 22 5 54.6 5.86 12.00 4.37
## 23 4 72.7 4.40 11.98 4.19
## 24 9 86.4 3.10 11.60 3.16
## 25 10 58.2 5.50 9.38 7.14
## 26 6 80.0 4.00 9.22 3.46
## 27 5 54.6 5.86 9.10 5.90
## 28 8 70.5 4.53 9.07 4.57
## 29 1 79.6 4.02 9.05 6.89
## 30 11 65.0 4.92 9.03 3.62
## 31 12 60.5 5.30 9.03 6.11
## 32 4 72.7 4.40 9.02 5.33
## 33 2 72.4 4.40 9.00 4.55
## 34 3 70.5 4.53 9.00 4.90
## 35 7 64.6 4.95 9.00 4.39
## 36 9 86.4 3.10 8.80 4.11
## 37 9 86.4 3.10 7.17 4.24
## 38 8 70.5 4.53 7.15 4.73
## 39 10 58.2 5.50 7.08 8.02
## 40 3 70.5 4.53 7.07 5.30
## 41 12 60.5 5.30 7.07 6.59
## 42 1 79.6 4.02 7.03 7.47
## 43 2 72.4 4.40 7.03 5.40
## 44 11 65.0 4.92 7.03 4.45
## 45 4 72.7 4.40 7.02 5.78
## 46 5 54.6 5.86 7.02 7.09
## 47 6 80.0 4.00 7.00 4.02
## 48 7 64.6 4.95 6.98 5.25
## 49 1 79.6 4.02 5.10 8.36
## 50 3 70.5 4.53 5.08 6.20
## 51 12 60.5 5.30 5.07 8.57
## 52 8 70.5 4.53 5.05 5.88
## 53 10 58.2 5.50 5.05 9.18
## 54 2 72.4 4.40 5.02 6.08
## 55 4 72.7 4.40 5.02 6.88
## 56 5 54.6 5.86 5.02 7.56
## 57 9 86.4 3.10 5.02 5.67
## 58 11 65.0 4.92 5.02 5.22
## 59 6 80.0 4.00 5.00 4.94
## 60 7 64.6 4.95 5.00 6.66
## 61 1 79.6 4.02 3.82 8.58
## 62 3 70.5 4.53 3.62 7.50
## 63 11 65.0 4.92 3.60 5.87
## 64 6 80.0 4.00 3.57 5.53
## 65 10 58.2 5.50 3.55 10.21
## 66 8 70.5 4.53 3.53 6.59
## 67 9 86.4 3.10 3.53 5.66
## 68 12 60.5 5.30 3.52 9.75
## 69 2 72.4 4.40 3.50 6.85
## 70 4 72.7 4.40 3.50 7.54
## 71 5 54.6 5.86 3.50 8.74
## 72 7 64.6 4.95 3.48 7.09
## 73 4 72.7 4.40 2.13 8.38
## 74 10 58.2 5.50 2.05 7.83
## 75 6 80.0 4.00 2.03 6.32
## 76 1 79.6 4.02 2.02 9.66
## 77 3 70.5 4.53 2.02 7.80
## 78 5 54.6 5.86 2.02 9.33
## 79 7 64.6 4.95 2.02 6.58
## 80 8 70.5 4.53 2.02 7.56
## 81 9 86.4 3.10 2.02 6.33
## 82 12 60.5 5.30 2.00 9.72
## 83 11 65.0 4.92 1.98 6.81
## 84 2 72.4 4.40 1.92 8.33
## 85 6 80.0 4.00 1.15 6.44
## 86 1 79.6 4.02 1.12 10.50
## 87 4 72.7 4.40 1.07 8.60
## 88 9 86.4 3.10 1.05 7.14
## 89 3 70.5 4.53 1.02 8.20
## 90 7 64.6 4.95 1.02 5.02
## 91 10 58.2 5.50 1.02 6.41
## 92 2 72.4 4.40 1.00 8.31
## 93 5 54.6 5.86 1.00 11.40
## 94 12 60.5 5.30 1.00 7.82
## 95 8 70.5 4.53 0.98 7.31
## 96 11 65.0 4.92 0.98 8.00
## 97 10 58.2 5.50 0.77 5.22
## 98 9 86.4 3.10 0.63 9.03
## 99 4 72.7 4.40 0.60 4.60
## 100 3 70.5 4.53 0.58 6.90
## 101 6 80.0 4.00 0.58 3.08
## 102 1 79.6 4.02 0.57 6.57
## 103 2 72.4 4.40 0.52 7.91
## 104 5 54.6 5.86 0.52 5.63
## 105 8 70.5 4.53 0.52 3.05
## 106 7 64.6 4.95 0.50 2.35
## 107 11 65.0 4.92 0.50 7.24
## 108 12 60.5 5.30 0.50 3.96
## 109 10 58.2 5.50 0.37 2.89
## 110 4 72.7 4.40 0.35 1.89
## 111 5 54.6 5.86 0.30 2.02
## 112 9 86.4 3.10 0.30 7.37
## 113 2 72.4 4.40 0.27 1.72
## 114 3 70.5 4.53 0.27 4.40
## 115 6 80.0 4.00 0.27 1.29
## 116 1 79.6 4.02 0.25 2.84
## 117 7 64.6 4.95 0.25 0.85
## 118 8 70.5 4.53 0.25 3.05
## 119 11 65.0 4.92 0.25 4.86
## 120 12 60.5 5.30 0.25 1.25
## 121 1 79.6 4.02 0.00 0.74
## 122 2 72.4 4.40 0.00 0.00
## 123 3 70.5 4.53 0.00 0.00
## 124 4 72.7 4.40 0.00 0.00
## 125 5 54.6 5.86 0.00 0.00
## 126 6 80.0 4.00 0.00 0.00
## 127 7 64.6 4.95 0.00 0.15
## 128 8 70.5 4.53 0.00 0.00
## 129 9 86.4 3.10 0.00 0.00
## 130 10 58.2 5.50 0.00 0.24
## 131 11 65.0 4.92 0.00 0.00
## 132 12 60.5 5.30 0.00 0.00Theoph %>% filter(Time>6.70)## Subject Wt Dose Time conc
## 1 1 79.6 4.02 7.03 7.47
## 2 1 79.6 4.02 9.05 6.89
## 3 1 79.6 4.02 12.12 5.94
## 4 1 79.6 4.02 24.37 3.28
## 5 2 72.4 4.40 7.03 5.40
## 6 2 72.4 4.40 9.00 4.55
## 7 2 72.4 4.40 12.00 3.01
## 8 2 72.4 4.40 24.30 0.90
## 9 3 70.5 4.53 7.07 5.30
## 10 3 70.5 4.53 9.00 4.90
## 11 3 70.5 4.53 12.15 3.70
## 12 3 70.5 4.53 24.17 1.05
## 13 4 72.7 4.40 7.02 5.78
## 14 4 72.7 4.40 9.02 5.33
## 15 4 72.7 4.40 11.98 4.19
## 16 4 72.7 4.40 24.65 1.15
## 17 5 54.6 5.86 7.02 7.09
## 18 5 54.6 5.86 9.10 5.90
## 19 5 54.6 5.86 12.00 4.37
## 20 5 54.6 5.86 24.35 1.57
## 21 6 80.0 4.00 7.00 4.02
## 22 6 80.0 4.00 9.22 3.46
## 23 6 80.0 4.00 12.10 2.78
## 24 6 80.0 4.00 23.85 0.92
## 25 7 64.6 4.95 6.98 5.25
## 26 7 64.6 4.95 9.00 4.39
## 27 7 64.6 4.95 12.05 3.53
## 28 7 64.6 4.95 24.22 1.15
## 29 8 70.5 4.53 7.15 4.73
## 30 8 70.5 4.53 9.07 4.57
## 31 8 70.5 4.53 12.10 3.00
## 32 8 70.5 4.53 24.12 1.25
## 33 9 86.4 3.10 7.17 4.24
## 34 9 86.4 3.10 8.80 4.11
## 35 9 86.4 3.10 11.60 3.16
## 36 9 86.4 3.10 24.43 1.12
## 37 10 58.2 5.50 7.08 8.02
## 38 10 58.2 5.50 9.38 7.14
## 39 10 58.2 5.50 12.10 5.68
## 40 10 58.2 5.50 23.70 2.42
## 41 11 65.0 4.92 7.03 4.45
## 42 11 65.0 4.92 9.03 3.62
## 43 11 65.0 4.92 12.12 2.69
## 44 11 65.0 4.92 24.08 0.86
## 45 12 60.5 5.30 7.07 6.59
## 46 12 60.5 5.30 9.03 6.11
## 47 12 60.5 5.30 12.05 4.57
## 48 12 60.5 5.30 24.15 1.17Theoph %>% mutate(Month=Time*30)## Subject Wt Dose Time conc Month
## 1 1 79.6 4.02 0.00 0.74 0.0
## 2 1 79.6 4.02 0.25 2.84 7.5
## 3 1 79.6 4.02 0.57 6.57 17.1
## 4 1 79.6 4.02 1.12 10.50 33.6
## 5 1 79.6 4.02 2.02 9.66 60.6
## 6 1 79.6 4.02 3.82 8.58 114.6
## 7 1 79.6 4.02 5.10 8.36 153.0
## 8 1 79.6 4.02 7.03 7.47 210.9
## 9 1 79.6 4.02 9.05 6.89 271.5
## 10 1 79.6 4.02 12.12 5.94 363.6
## 11 1 79.6 4.02 24.37 3.28 731.1
## 12 2 72.4 4.40 0.00 0.00 0.0
## 13 2 72.4 4.40 0.27 1.72 8.1
## 14 2 72.4 4.40 0.52 7.91 15.6
## 15 2 72.4 4.40 1.00 8.31 30.0
## 16 2 72.4 4.40 1.92 8.33 57.6
## 17 2 72.4 4.40 3.50 6.85 105.0
## 18 2 72.4 4.40 5.02 6.08 150.6
## 19 2 72.4 4.40 7.03 5.40 210.9
## 20 2 72.4 4.40 9.00 4.55 270.0
## 21 2 72.4 4.40 12.00 3.01 360.0
## 22 2 72.4 4.40 24.30 0.90 729.0
## 23 3 70.5 4.53 0.00 0.00 0.0
## 24 3 70.5 4.53 0.27 4.40 8.1
## 25 3 70.5 4.53 0.58 6.90 17.4
## 26 3 70.5 4.53 1.02 8.20 30.6
## 27 3 70.5 4.53 2.02 7.80 60.6
## 28 3 70.5 4.53 3.62 7.50 108.6
## 29 3 70.5 4.53 5.08 6.20 152.4
## 30 3 70.5 4.53 7.07 5.30 212.1
## 31 3 70.5 4.53 9.00 4.90 270.0
## 32 3 70.5 4.53 12.15 3.70 364.5
## 33 3 70.5 4.53 24.17 1.05 725.1
## 34 4 72.7 4.40 0.00 0.00 0.0
## 35 4 72.7 4.40 0.35 1.89 10.5
## 36 4 72.7 4.40 0.60 4.60 18.0
## 37 4 72.7 4.40 1.07 8.60 32.1
## 38 4 72.7 4.40 2.13 8.38 63.9
## 39 4 72.7 4.40 3.50 7.54 105.0
## 40 4 72.7 4.40 5.02 6.88 150.6
## 41 4 72.7 4.40 7.02 5.78 210.6
## 42 4 72.7 4.40 9.02 5.33 270.6
## 43 4 72.7 4.40 11.98 4.19 359.4
## 44 4 72.7 4.40 24.65 1.15 739.5
## 45 5 54.6 5.86 0.00 0.00 0.0
## 46 5 54.6 5.86 0.30 2.02 9.0
## 47 5 54.6 5.86 0.52 5.63 15.6
## 48 5 54.6 5.86 1.00 11.40 30.0
## 49 5 54.6 5.86 2.02 9.33 60.6
## 50 5 54.6 5.86 3.50 8.74 105.0
## 51 5 54.6 5.86 5.02 7.56 150.6
## 52 5 54.6 5.86 7.02 7.09 210.6
## 53 5 54.6 5.86 9.10 5.90 273.0
## 54 5 54.6 5.86 12.00 4.37 360.0
## 55 5 54.6 5.86 24.35 1.57 730.5
## 56 6 80.0 4.00 0.00 0.00 0.0
## 57 6 80.0 4.00 0.27 1.29 8.1
## 58 6 80.0 4.00 0.58 3.08 17.4
## 59 6 80.0 4.00 1.15 6.44 34.5
## 60 6 80.0 4.00 2.03 6.32 60.9
## 61 6 80.0 4.00 3.57 5.53 107.1
## 62 6 80.0 4.00 5.00 4.94 150.0
## 63 6 80.0 4.00 7.00 4.02 210.0
## 64 6 80.0 4.00 9.22 3.46 276.6
## 65 6 80.0 4.00 12.10 2.78 363.0
## 66 6 80.0 4.00 23.85 0.92 715.5
## 67 7 64.6 4.95 0.00 0.15 0.0
## 68 7 64.6 4.95 0.25 0.85 7.5
## 69 7 64.6 4.95 0.50 2.35 15.0
## 70 7 64.6 4.95 1.02 5.02 30.6
## 71 7 64.6 4.95 2.02 6.58 60.6
## 72 7 64.6 4.95 3.48 7.09 104.4
## 73 7 64.6 4.95 5.00 6.66 150.0
## 74 7 64.6 4.95 6.98 5.25 209.4
## 75 7 64.6 4.95 9.00 4.39 270.0
## 76 7 64.6 4.95 12.05 3.53 361.5
## 77 7 64.6 4.95 24.22 1.15 726.6
## 78 8 70.5 4.53 0.00 0.00 0.0
## 79 8 70.5 4.53 0.25 3.05 7.5
## 80 8 70.5 4.53 0.52 3.05 15.6
## 81 8 70.5 4.53 0.98 7.31 29.4
## 82 8 70.5 4.53 2.02 7.56 60.6
## 83 8 70.5 4.53 3.53 6.59 105.9
## 84 8 70.5 4.53 5.05 5.88 151.5
## 85 8 70.5 4.53 7.15 4.73 214.5
## 86 8 70.5 4.53 9.07 4.57 272.1
## 87 8 70.5 4.53 12.10 3.00 363.0
## 88 8 70.5 4.53 24.12 1.25 723.6
## 89 9 86.4 3.10 0.00 0.00 0.0
## 90 9 86.4 3.10 0.30 7.37 9.0
## 91 9 86.4 3.10 0.63 9.03 18.9
## 92 9 86.4 3.10 1.05 7.14 31.5
## 93 9 86.4 3.10 2.02 6.33 60.6
## 94 9 86.4 3.10 3.53 5.66 105.9
## 95 9 86.4 3.10 5.02 5.67 150.6
## 96 9 86.4 3.10 7.17 4.24 215.1
## 97 9 86.4 3.10 8.80 4.11 264.0
## 98 9 86.4 3.10 11.60 3.16 348.0
## 99 9 86.4 3.10 24.43 1.12 732.9
## 100 10 58.2 5.50 0.00 0.24 0.0
## 101 10 58.2 5.50 0.37 2.89 11.1
## 102 10 58.2 5.50 0.77 5.22 23.1
## 103 10 58.2 5.50 1.02 6.41 30.6
## 104 10 58.2 5.50 2.05 7.83 61.5
## 105 10 58.2 5.50 3.55 10.21 106.5
## 106 10 58.2 5.50 5.05 9.18 151.5
## 107 10 58.2 5.50 7.08 8.02 212.4
## 108 10 58.2 5.50 9.38 7.14 281.4
## 109 10 58.2 5.50 12.10 5.68 363.0
## 110 10 58.2 5.50 23.70 2.42 711.0
## 111 11 65.0 4.92 0.00 0.00 0.0
## 112 11 65.0 4.92 0.25 4.86 7.5
## 113 11 65.0 4.92 0.50 7.24 15.0
## 114 11 65.0 4.92 0.98 8.00 29.4
## 115 11 65.0 4.92 1.98 6.81 59.4
## 116 11 65.0 4.92 3.60 5.87 108.0
## 117 11 65.0 4.92 5.02 5.22 150.6
## 118 11 65.0 4.92 7.03 4.45 210.9
## 119 11 65.0 4.92 9.03 3.62 270.9
## 120 11 65.0 4.92 12.12 2.69 363.6
## 121 11 65.0 4.92 24.08 0.86 722.4
## 122 12 60.5 5.30 0.00 0.00 0.0
## 123 12 60.5 5.30 0.25 1.25 7.5
## 124 12 60.5 5.30 0.50 3.96 15.0
## 125 12 60.5 5.30 1.00 7.82 30.0
## 126 12 60.5 5.30 2.00 9.72 60.0
## 127 12 60.5 5.30 3.52 9.75 105.6
## 128 12 60.5 5.30 5.07 8.57 152.1
## 129 12 60.5 5.30 7.07 6.59 212.1
## 130 12 60.5 5.30 9.03 6.11 270.9
## 131 12 60.5 5.30 12.05 4.57 361.5
## 132 12 60.5 5.30 24.15 1.17 724.5Theoph %>% group_by(Time)%>%summarise(sum=sum(Wt))## # A tibble: 78 x 2
## Time sum
## <dbl> <dbl>
## 1 0 835
## 2 0.25 340.
## 3 0.27 223.
## 4 0.3 141
## 5 0.35 72.7
## 6 0.37 58.2
## 7 0.5 190.
## 8 0.52 198.
## 9 0.57 79.6
## 10 0.58 150.
## # ... with 68 more rowsTheoph ## Subject Wt Dose Time conc
## 1 1 79.6 4.02 0.00 0.74
## 2 1 79.6 4.02 0.25 2.84
## 3 1 79.6 4.02 0.57 6.57
## 4 1 79.6 4.02 1.12 10.50
## 5 1 79.6 4.02 2.02 9.66
## 6 1 79.6 4.02 3.82 8.58
## 7 1 79.6 4.02 5.10 8.36
## 8 1 79.6 4.02 7.03 7.47
## 9 1 79.6 4.02 9.05 6.89
## 10 1 79.6 4.02 12.12 5.94
## 11 1 79.6 4.02 24.37 3.28
## 12 2 72.4 4.40 0.00 0.00
## 13 2 72.4 4.40 0.27 1.72
## 14 2 72.4 4.40 0.52 7.91
## 15 2 72.4 4.40 1.00 8.31
## 16 2 72.4 4.40 1.92 8.33
## 17 2 72.4 4.40 3.50 6.85
## 18 2 72.4 4.40 5.02 6.08
## 19 2 72.4 4.40 7.03 5.40
## 20 2 72.4 4.40 9.00 4.55
## 21 2 72.4 4.40 12.00 3.01
## 22 2 72.4 4.40 24.30 0.90
## 23 3 70.5 4.53 0.00 0.00
## 24 3 70.5 4.53 0.27 4.40
## 25 3 70.5 4.53 0.58 6.90
## 26 3 70.5 4.53 1.02 8.20
## 27 3 70.5 4.53 2.02 7.80
## 28 3 70.5 4.53 3.62 7.50
## 29 3 70.5 4.53 5.08 6.20
## 30 3 70.5 4.53 7.07 5.30
## 31 3 70.5 4.53 9.00 4.90
## 32 3 70.5 4.53 12.15 3.70
## 33 3 70.5 4.53 24.17 1.05
## 34 4 72.7 4.40 0.00 0.00
## 35 4 72.7 4.40 0.35 1.89
## 36 4 72.7 4.40 0.60 4.60
## 37 4 72.7 4.40 1.07 8.60
## 38 4 72.7 4.40 2.13 8.38
## 39 4 72.7 4.40 3.50 7.54
## 40 4 72.7 4.40 5.02 6.88
## 41 4 72.7 4.40 7.02 5.78
## 42 4 72.7 4.40 9.02 5.33
## 43 4 72.7 4.40 11.98 4.19
## 44 4 72.7 4.40 24.65 1.15
## 45 5 54.6 5.86 0.00 0.00
## 46 5 54.6 5.86 0.30 2.02
## 47 5 54.6 5.86 0.52 5.63
## 48 5 54.6 5.86 1.00 11.40
## 49 5 54.6 5.86 2.02 9.33
## 50 5 54.6 5.86 3.50 8.74
## 51 5 54.6 5.86 5.02 7.56
## 52 5 54.6 5.86 7.02 7.09
## 53 5 54.6 5.86 9.10 5.90
## 54 5 54.6 5.86 12.00 4.37
## 55 5 54.6 5.86 24.35 1.57
## 56 6 80.0 4.00 0.00 0.00
## 57 6 80.0 4.00 0.27 1.29
## 58 6 80.0 4.00 0.58 3.08
## 59 6 80.0 4.00 1.15 6.44
## 60 6 80.0 4.00 2.03 6.32
## 61 6 80.0 4.00 3.57 5.53
## 62 6 80.0 4.00 5.00 4.94
## 63 6 80.0 4.00 7.00 4.02
## 64 6 80.0 4.00 9.22 3.46
## 65 6 80.0 4.00 12.10 2.78
## 66 6 80.0 4.00 23.85 0.92
## 67 7 64.6 4.95 0.00 0.15
## 68 7 64.6 4.95 0.25 0.85
## 69 7 64.6 4.95 0.50 2.35
## 70 7 64.6 4.95 1.02 5.02
## 71 7 64.6 4.95 2.02 6.58
## 72 7 64.6 4.95 3.48 7.09
## 73 7 64.6 4.95 5.00 6.66
## 74 7 64.6 4.95 6.98 5.25
## 75 7 64.6 4.95 9.00 4.39
## 76 7 64.6 4.95 12.05 3.53
## 77 7 64.6 4.95 24.22 1.15
## 78 8 70.5 4.53 0.00 0.00
## 79 8 70.5 4.53 0.25 3.05
## 80 8 70.5 4.53 0.52 3.05
## 81 8 70.5 4.53 0.98 7.31
## 82 8 70.5 4.53 2.02 7.56
## 83 8 70.5 4.53 3.53 6.59
## 84 8 70.5 4.53 5.05 5.88
## 85 8 70.5 4.53 7.15 4.73
## 86 8 70.5 4.53 9.07 4.57
## 87 8 70.5 4.53 12.10 3.00
## 88 8 70.5 4.53 24.12 1.25
## 89 9 86.4 3.10 0.00 0.00
## 90 9 86.4 3.10 0.30 7.37
## 91 9 86.4 3.10 0.63 9.03
## 92 9 86.4 3.10 1.05 7.14
## 93 9 86.4 3.10 2.02 6.33
## 94 9 86.4 3.10 3.53 5.66
## 95 9 86.4 3.10 5.02 5.67
## 96 9 86.4 3.10 7.17 4.24
## 97 9 86.4 3.10 8.80 4.11
## 98 9 86.4 3.10 11.60 3.16
## 99 9 86.4 3.10 24.43 1.12
## 100 10 58.2 5.50 0.00 0.24
## 101 10 58.2 5.50 0.37 2.89
## 102 10 58.2 5.50 0.77 5.22
## 103 10 58.2 5.50 1.02 6.41
## 104 10 58.2 5.50 2.05 7.83
## 105 10 58.2 5.50 3.55 10.21
## 106 10 58.2 5.50 5.05 9.18
## 107 10 58.2 5.50 7.08 8.02
## 108 10 58.2 5.50 9.38 7.14
## 109 10 58.2 5.50 12.10 5.68
## 110 10 58.2 5.50 23.70 2.42
## 111 11 65.0 4.92 0.00 0.00
## 112 11 65.0 4.92 0.25 4.86
## 113 11 65.0 4.92 0.50 7.24
## 114 11 65.0 4.92 0.98 8.00
## 115 11 65.0 4.92 1.98 6.81
## 116 11 65.0 4.92 3.60 5.87
## 117 11 65.0 4.92 5.02 5.22
## 118 11 65.0 4.92 7.03 4.45
## 119 11 65.0 4.92 9.03 3.62
## 120 11 65.0 4.92 12.12 2.69
## 121 11 65.0 4.92 24.08 0.86
## 122 12 60.5 5.30 0.00 0.00
## 123 12 60.5 5.30 0.25 1.25
## 124 12 60.5 5.30 0.50 3.96
## 125 12 60.5 5.30 1.00 7.82
## 126 12 60.5 5.30 2.00 9.72
## 127 12 60.5 5.30 3.52 9.75
## 128 12 60.5 5.30 5.07 8.57
## 129 12 60.5 5.30 7.07 6.59
## 130 12 60.5 5.30 9.03 6.11
## 131 12 60.5 5.30 12.05 4.57
## 132 12 60.5 5.30 24.15 1.17Melakukan kelima perintah bersamaan
Theoph%>% select(Subject, Wt, Dose, Time,conc) %>% arrange(desc(Time)) %>% filter(Time>6.70)%>% mutate(Month=Time*30)%>% group_by(Time)%>%summarise(sum=sum(Wt))## # A tibble: 36 x 2
## Time sum
## <dbl> <dbl>
## 1 6.98 64.6
## 2 7 80
## 3 7.02 127.
## 4 7.03 217
## 5 7.07 131
## 6 7.08 58.2
## 7 7.15 70.5
## 8 7.17 86.4
## 9 8.8 86.4
## 10 9 208.
## # ... with 26 more rows