options(repos = c(CRAN = "https://cran.rstudio.com"))
install.packages("tidyverse")
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##  C:\Users\Ryzen\AppData\Local\Temp\Rtmpiqkn94\downloaded_packages
install.packages("dplyr")
## package 'dplyr' successfully unpacked and MD5 sums checked
## Warning: cannot remove prior installation of package 'dplyr'
## Warning in file.copy(savedcopy, lib, recursive = TRUE): problem copying
## D:\R-4.3.1\library\00LOCK\dplyr\libs\x64\dplyr.dll to
## D:\R-4.3.1\library\dplyr\libs\x64\dplyr.dll: Permission denied
## Warning: restored 'dplyr'
## 
## The downloaded binary packages are in
##  C:\Users\Ryzen\AppData\Local\Temp\Rtmpiqkn94\downloaded_packages
install.packages("vctrs")
## package 'vctrs' successfully unpacked and MD5 sums checked
## Warning: cannot remove prior installation of package 'vctrs'
## Warning in file.copy(savedcopy, lib, recursive = TRUE): problem copying
## D:\R-4.3.1\library\00LOCK\vctrs\libs\x64\vctrs.dll to
## D:\R-4.3.1\library\vctrs\libs\x64\vctrs.dll: Permission denied
## Warning: restored 'vctrs'
## 
## The downloaded binary packages are in
##  C:\Users\Ryzen\AppData\Local\Temp\Rtmpiqkn94\downloaded_packages
library(tidyverse)
## Warning: package 'tidyverse' was built under R version 4.3.2
## Warning: package 'ggplot2' was built under R version 4.3.2
## Warning: package 'readr' was built under R version 4.3.2
## Warning: package 'dplyr' was built under R version 4.3.2
## Warning: package 'forcats' was built under R version 4.3.2
## Warning: package 'lubridate' was built under R version 4.3.2
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.4
## ✔ forcats   1.0.0     ✔ stringr   1.5.0
## ✔ ggplot2   3.4.4     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.0
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(datasets)
library(vctrs)
## Warning: package 'vctrs' was built under R version 4.3.2
## 
## Attaching package: 'vctrs'
## 
## The following object is masked from 'package:dplyr':
## 
##     data_frame
## 
## The following object is masked from 'package:tibble':
## 
##     data_frame
data("quakes")
view(quakes)
quakes <- tibble::as.tibble(quakes)
## Warning: `as.tibble()` was deprecated in tibble 2.0.0.
## ℹ Please use `as_tibble()` instead.
## ℹ The signature and semantics have changed, see `?as_tibble`.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
class(quakes)
## [1] "tbl_df"     "tbl"        "data.frame"
glimpse(quakes)
## Rows: 1,000
## Columns: 5
## $ lat      <dbl> -20.42, -20.62, -26.00, -17.97, -20.42, -19.68, -11.70, -28.1…
## $ long     <dbl> 181.62, 181.03, 184.10, 181.66, 181.96, 184.31, 166.10, 181.9…
## $ depth    <int> 562, 650, 42, 626, 649, 195, 82, 194, 211, 622, 583, 249, 554…
## $ mag      <dbl> 4.8, 4.2, 5.4, 4.1, 4.0, 4.0, 4.8, 4.4, 4.7, 4.3, 4.4, 4.6, 4…
## $ stations <int> 41, 15, 43, 19, 11, 12, 43, 15, 35, 19, 13, 16, 19, 10, 94, 1…
head(quakes)
## # A tibble: 6 × 5
##     lat  long depth   mag stations
##   <dbl> <dbl> <int> <dbl>    <int>
## 1 -20.4  182.   562   4.8       41
## 2 -20.6  181.   650   4.2       15
## 3 -26    184.    42   5.4       43
## 4 -18.0  182.   626   4.1       19
## 5 -20.4  182.   649   4         11
## 6 -19.7  184.   195   4         12
mean(quakes$mag) == quakes$mag %>% mean()
## [1] TRUE
#SUMMARIZE AND ARRANGE
quakes %>% group_by(stations) %>% summarize(mean=mean(mag)) %>% print(n=100) 
## # A tibble: 102 × 2
##     stations  mean
##        <int> <dbl>
##   1       10  4.23
##   2       11  4.23
##   3       12  4.20
##   4       13  4.33
##   5       14  4.28
##   6       15  4.28
##   7       16  4.27
##   8       17  4.35
##   9       18  4.44
##  10       19  4.38
##  11       20  4.39
##  12       21  4.36
##  13       22  4.45
##  14       23  4.38
##  15       24  4.48
##  16       25  4.53
##  17       26  4.5 
##  18       27  4.58
##  19       28  4.58
##  20       29  4.57
##  21       30  4.65
##  22       31  4.66
##  23       32  4.59
##  24       33  4.59
##  25       34  4.59
##  26       35  4.72
##  27       36  4.69
##  28       37  4.67
##  29       38  4.82
##  30       39  4.63
##  31       40  4.82
##  32       41  4.71
##  33       42  4.78
##  34       43  4.89
##  35       44  4.74
##  36       45  4.97
##  37       46  4.93
##  38       47  4.84
##  39       48  4.93
##  40       49  5.01
##  41       50  4.88
##  42       51  4.85
##  43       52  4.85
##  44       53  5.3 
##  45       54  5.05
##  46       55  5   
##  47       56  4.98
##  48       57  4.95
##  49       58  5.1 
##  50       59  5   
##  51       60  5.13
##  52       61  5.2 
##  53       62  4.9 
##  54       63  5.1 
##  55       64  5.08
##  56       65  5.16
##  57       66  5.2 
##  58       67  5.24
##  59       68  5.19
##  60       69  5.2 
##  61       70  5.23
##  62       71  5.28
##  63       72  5.17
##  64       73  5.3 
##  65       74  5.12
##  66       75  5.3 
##  67       76  5.7 
##  68       77  5   
##  69       78  5.35
##  70       79  5.28
##  71       80  5.5 
##  72       81  5.3 
##  73       82  5.3 
##  74       83  6   
##  75       85  5.4 
##  76       86  5.37
##  77       87  5.4 
##  78       88  5.4 
##  79       89  5.25
##  80       90  5.7 
##  81       91  5.27
##  82       92  5.5 
##  83       93  5.3 
##  84       94  5.85
##  85       95  5.5 
##  86       98  5.6 
##  87       99  5.7 
##  88      100  5   
##  89      104  5.6 
##  90      105  5.45
##  91      106  5.7 
##  92      109  5.6 
##  93      110  5.4 
##  94      112  5.7 
##  95      115  5.6 
##  96      118  5.9 
##  97      119  5.95
##  98      121  5.6 
##  99      122  6.4 
## 100      123  5.7 
## # ℹ 2 more rows
quakes %>% arrange(mag) %>% print(n=100)
## # A tibble: 1,000 × 5
##       lat  long depth   mag stations
##     <dbl> <dbl> <int> <dbl>    <int>
##   1 -20.4  182.   649   4         11
##   2 -19.7  184.   195   4         12
##   3 -17.9  181.   537   4         15
##   4 -23.6  181.   349   4         10
##   5 -19.3  184.   223   4         15
##   6 -22.1  181.   584   4         11
##   7 -15.3  186.   152   4         11
##   8 -17.7  182.   450   4         11
##   9 -19.7  182.   375   4         18
##  10 -19.1  182.   477   4         16
##  11 -20.6  181.   582   4         14
##  12 -17.9  182.   573   4         19
##  13 -17.7  182.   445   4         12
##  14 -23.5  180.   574   4         12
##  15 -17.7  185    383   4         10
##  16 -17.9  182.   601   4         16
##  17 -30.6  181.   175   4         16
##  18 -16.9  186.   135   4         22
##  19 -10.7  166.   195   4         14
##  20 -18.6  182.   563   4         17
##  21 -22.7  183.   180   4         13
##  22 -21    183.   296   4         16
##  23 -17.0  183.   406   4         17
##  24 -19.5  184.   280   4         16
##  25 -15.4  185.   249   4         11
##  26 -17.9  181.   555   4         17
##  27 -17.1  183.   390   4         14
##  28 -30.3  181.   275   4         14
##  29 -25.6  180.   440   4         12
##  30 -20.7  186.    80   4         10
##  31 -16.4  183.   391   4         16
##  32 -21.6  180.   595   4         22
##  33 -17.9  182.   589   4         12
##  34 -28    182    199   4         16
##  35 -22.1  180.   532   4         14
##  36 -21.6  182.   350   4         12
##  37 -19.7  182.   397   4         12
##  38 -18.5  185.   243   4         11
##  39 -21.0  181.   638   4         14
##  40 -17.8  181.   530   4         15
##  41 -17.8  181.   538   4         33
##  42 -25.1  183.   133   4         14
##  43 -18.1  182.   574   4         20
##  44 -23.5  180.   530   4         23
##  45 -17.9  181.   614   4         12
##  46 -18.0  181.   642   4         17
##  47 -18.0  182.   626   4.1       19
##  48 -17.7  181.   585   4.1       17
##  49 -21.2  182.   260   4.1       12
##  50 -20.1  182.   587   4.1       13
##  51 -19.2  185.   197   4.1       11
##  52 -17.0  186.   108   4.1       12
##  53 -18.0  180.   626   4.1       19
##  54 -20.2  181.   627   4.1       11
##  55 -15.2  185.    99   4.1       14
##  56 -15.0  182.   399   4.1       10
##  57 -17.8  181.   542   4.1       20
##  58 -20.4  182.   534   4.1       14
##  59 -24.1  180.   605   4.1       21
##  60 -28.2  182.   226   4.1       19
##  61 -24.4  183.   148   4.1       16
##  62 -23.8  180.   498   4.1       12
##  63 -17.7  181.   515   4.1       19
##  64 -17.3  181.   497   4.1       13
##  65 -17.5  181.   573   4.1       17
##  66 -23.4  183.   158   4.1       20
##  67 -17.0  187.    70   4.1       22
##  68 -18.4  183.   343   4.1       10
##  69 -14.8  185.   294   4.1       10
##  70 -17.9  181.   593   4.1       13
##  71 -17.6  181.   537   4.1       11
##  72 -17.1  185.   223   4.1       15
##  73 -17.8  182.   598   4.1       14
##  74 -19.2  183.   570   4.1       22
##  75 -21.8  185     74   4.1       15
##  76 -17.8  181.   539   4.1       12
##  77 -18.9  181.   655   4.1       14
##  78 -17.6  182.   548   4.1       10
##  79 -17.2  183.   383   4.1       11
##  80 -25.1  178.   554   4.1       15
##  81 -16.4  187.    75   4.1       20
##  82 -17.8  185.   223   4.1       10
##  83 -19.1  185.   230   4.1       16
##  84 -21.8  181    618   4.1       10
##  85 -18.1  182.   593   4.1       16
##  86 -20.2  182.   576   4.1       16
##  87 -19.1  185.   210   4.1       22
##  88 -22.1  180.   603   4.1       11
##  89 -22.1  180.   587   4.1       23
##  90 -15.7  185.    70   4.1       15
##  91 -19.4  182.   326   4.1       15
##  92 -15.8  186.   121   4.1       17
##  93 -17.6  181.   580   4.1       16
##  94 -15.2  186.    77   4.1       16
##  95 -15.6  185.   315   4.1       15
##  96 -17.9  182.   567   4.1       27
##  97 -17.7  181.   559   4.1       16
##  98 -18.4  182.   600   4.1       11
##  99 -23.5  180.   543   4.1       21
## 100 -19.7  184.   223   4.1       23
## # ℹ 900 more rows
quakes %>% arrange(desc(long)) %>% print(n=100)
## # A tibble: 1,000 × 5
##       lat  long depth   mag stations
##     <dbl> <dbl> <int> <dbl>    <int>
##   1 -15.9  188.    52   5         30
##   2 -17.7  188.    45   4.2       10
##   3 -15.5  188.    40   5.5       91
##   4 -16.5  188.    40   4.5       18
##   5 -17.4  188.    40   4.5       14
##   6 -18.8  188.    44   4.8       35
##   7 -16.1  187.    61   4.5       19
##   8 -16.1  187.    42   5.1       68
##   9 -15.2  187.    50   4.7       28
##  10 -15.6  187.    49   5         30
##  11 -15.5  187.    60   4.5       17
##  12 -16.5  187.    62   4.9       46
##  13 -17.7  187.    45   4.9       62
##  14 -17.0  187     70   4.7       30
##  15 -15.5  187.    46   4.7       18
##  16 -19.5  187.    58   4.4       20
##  17 -15.4  187.    78   4.7       44
##  18 -19.0  187.    45   5.2       65
##  19 -17.7  187.   112   4.5       35
##  20 -17.0  187.    70   4.1       22
##  21 -15.7  187.    45   4.4       11
##  22 -17.7  187.   104   5.1       71
##  23 -15.3  187.    48   5.7      123
##  24 -16.6  187.    82   4.8       51
##  25 -15.5  187.    82   4.4       17
##  26 -15.4  187.    83   4.7       37
##  27 -16.4  187.    75   4.1       20
##  28 -18.8  187.    68   4.8       48
##  29 -15.4  187.   130   5.5       95
##  30 -15.4  187.   112   5.1       57
##  31 -19.3  187.    56   5.2       49
##  32 -17.4  187.    85   4.2       28
##  33 -16.2  187.   111   4.8       30
##  34 -20.4  187.    63   5         28
##  35 -15.4  186.    69   4.3       42
##  36 -15.3  186.   153   4.6       31
##  37 -15.4  186.    98   4.4       17
##  38 -19.4  186.   100   4.7       40
##  39 -15.4  186.   123   4.2       16
##  40 -20.1  186.    63   4.6       19
##  41 -20.7  186.    80   4         10
##  42 -15.6  186.    64   5.1       54
##  43 -15.2  186.   158   5         57
##  44 -19.7  186.    47   4.8       19
##  45 -20.4  186.   102   4.3       21
##  46 -19.3  186.    44   5.4      110
##  47 -15.3  186.    96   4.6       32
##  48 -20.4  186.    74   4.3       22
##  49 -16.0  186.   143   4.6       41
##  50 -15.5  186.    94   4.3       26
##  51 -16.3  186     48   4.5       10
##  52 -15.3  186.   162   4.4       36
##  53 -17.1  186.   180   4.2       29
##  54 -17.0  186.    95   4.3       12
##  55 -15.2  186.    77   4.1       16
##  56 -22.6  186.    42   5.7       76
##  57 -20.8  186.   104   4.5       19
##  58 -17.1  186.   127   5.4       75
##  59 -15.8  186.   121   4.1       17
##  60 -16.4  186.   148   5         47
##  61 -21.5  186.    55   4.9       46
##  62 -19.3  186.    48   5         40
##  63 -15.3  186.   152   4         11
##  64 -21.3  186.    69   4.9       74
##  65 -20.8  186.   118   4.6       15
##  66 -20.7  186.    69   4.3       25
##  67 -21.3  186.    57   5.3       69
##  68 -16.2  186.   154   4.5       22
##  69 -16.4  186.   126   4.7       30
##  70 -17.0  186.   178   4.2       32
##  71 -16.9  186.   135   4         22
##  72 -16.5  186.    90   4.7       30
##  73 -20.5  186.    93   5.4       85
##  74 -15.7  186.   138   4.3       21
##  75 -21.6  186.    66   4.9       38
##  76 -17.0  186.   108   4.1       12
##  77 -19    186.   107   4.5       15
##  78 -21.1  186.    85   5.3       86
##  79 -16.6  186.   218   5         52
##  80 -22    186.    52   4.4       18
##  81 -21.6  186.    47   4.5       29
##  82 -21.5  185.    51   5         29
##  83 -18    185.   143   4.4       29
##  84 -17.4  185.   189   4.5       22
##  85 -16.0  185.   297   4.8       25
##  86 -18.5  185.   243   4         11
##  87 -19.6  185.    57   4.9       31
##  88 -17.8  185.   223   4.1       10
##  89 -21.1  185.   123   4.7       36
##  90 -16.1  185.   257   4.7       30
##  91 -17.1  185.   223   4.1       15
##  92 -15.9  185.    57   4.4       19
##  93 -22.1  185.    50   4.6       22
##  94 -15.5  185.    93   4.4       25
##  95 -18.4  185.   201   4.7       57
##  96 -15.4  185.   224   4.2       21
##  97 -20.9  185.    54   5.1       44
##  98 -19.0  185.   129   5.1       73
##  99 -15.8  185.    82   4.4       39
## 100 -15.8  185.   280   4.5       28
## # ℹ 900 more rows
#SUMMARIZE AND ARRANGE
quakes %>% group_by(stations) %>% summarize(mean=mean(mag))
## # A tibble: 102 × 2
##    stations  mean
##       <int> <dbl>
##  1       10  4.23
##  2       11  4.23
##  3       12  4.20
##  4       13  4.33
##  5       14  4.28
##  6       15  4.28
##  7       16  4.27
##  8       17  4.35
##  9       18  4.44
## 10       19  4.38
## # ℹ 92 more rows
quakes %>% arrange(mag)
## # A tibble: 1,000 × 5
##      lat  long depth   mag stations
##    <dbl> <dbl> <int> <dbl>    <int>
##  1 -20.4  182.   649     4       11
##  2 -19.7  184.   195     4       12
##  3 -17.9  181.   537     4       15
##  4 -23.6  181.   349     4       10
##  5 -19.3  184.   223     4       15
##  6 -22.1  181.   584     4       11
##  7 -15.3  186.   152     4       11
##  8 -17.7  182.   450     4       11
##  9 -19.7  182.   375     4       18
## 10 -19.1  182.   477     4       16
## # ℹ 990 more rows
quakes %>% arrange(desc(mag))
## # A tibble: 1,000 × 5
##      lat  long depth   mag stations
##    <dbl> <dbl> <int> <dbl>    <int>
##  1 -15.6  168.   127   6.4      122
##  2 -20.7  170.   139   6.1       94
##  3 -13.6  166.    50   6         83
##  4 -12.2  167.   242   6        132
##  5 -21.6  171.   165   6        119
##  6 -22.9  184.    64   5.9      118
##  7 -21.1  181.   627   5.9      119
##  8 -22.6  186.    42   5.7       76
##  9 -23.3  184.    56   5.7      106
## 10 -32.2  180.   216   5.7       90
## # ℹ 990 more rows
#SELECT AND FILTER
quakes %>% filter(stations=="14") %>% print(n=30)
## # A tibble: 39 × 5
##      lat  long depth   mag stations
##    <dbl> <dbl> <int> <dbl>    <int>
##  1 -11.6  166.    96   4.3       14
##  2 -19.7  170.   271   4.2       14
##  3 -16.8  182.   388   4.2       14
##  4 -13.5  172.    64   4.7       14
##  5 -21.3  181.   624   4.3       14
##  6 -24.0  183.   199   4.6       14
##  7 -20.6  181.   582   4         14
##  8 -11.8  166.    69   4.2       14
##  9 -15.2  185.    99   4.1       14
## 10 -20.4  182.   534   4.1       14
## 11 -24    183.   175   4.5       14
## 12 -20.3  182.   508   4.5       14
## 13 -18.3  182.   342   4.2       14
## 14 -18.7  169.    82   4.4       14
## 15 -17.4  181.   479   4.4       14
## 16 -29.5  182.   129   4.4       14
## 17 -27.2  182.    56   4.5       14
## 18 -27.2  182.    65   4.2       14
## 19 -27.2  182.    69   4.3       14
## 20 -18.0  182.   590   4.2       14
## 21 -18.3  183.   103   4.5       14
## 22 -18.2  182.   553   4.4       14
## 23 -17.8  181.   573   4.2       14
## 24 -10.7  166.   195   4         14
## 25 -17.5  182.   417   4.2       14
## 26 -27.6  183.    80   4.3       14
## 27 -19.8  183.   524   4.6       14
## 28 -17.8  182.   598   4.1       14
## 29 -18.9  181.   655   4.1       14
## 30 -17.1  183.   390   4         14
## # ℹ 9 more rows
quakes %>% select(long,depth,mag,) %>% print(n=100)
## # A tibble: 1,000 × 3
##      long depth   mag
##     <dbl> <int> <dbl>
##   1  182.   562   4.8
##   2  181.   650   4.2
##   3  184.    42   5.4
##   4  182.   626   4.1
##   5  182.   649   4  
##   6  184.   195   4  
##   7  166.    82   4.8
##   8  182.   194   4.4
##   9  182.   211   4.7
##  10  180.   622   4.3
##  11  181.   583   4.4
##  12  167    249   4.6
##  13  182.   554   4.4
##  14  182.   600   4.4
##  15  170.   139   6.1
##  16  185.   306   4.3
##  17  166.    50   6  
##  18  182.   590   4.5
##  19  180.   570   4.4
##  20  180.   598   4.4
##  21  181.   576   4.5
##  22  166.   211   4.2
##  23  180.   512   4.4
##  24  182    125   4.7
##  25  180.   431   5.4
##  26  181.   537   4  
##  27  168.   155   4.6
##  28  181.   498   5.2
##  29  181.   582   4.5
##  30  182.   328   4.4
##  31  179.   553   4.6
##  32  167.    50   4.7
##  33  185.   292   4.8
##  34  181.   349   4  
##  35  186     48   4.5
##  36  179.   600   4.3
##  37  169.   206   4.5
##  38  181.   574   4.6
##  39  181.   585   4.1
##  40  169.   230   4.4
##  41  177.   263   4.7
##  42  186.    96   4.6
##  43  180.   511   4.4
##  44  186.    94   4.3
##  45  169.   246   4.6
##  46  182.    56   4.9
##  47  182.   329   4.5
##  48  166.    70   4.4
##  49  180.   493   4.3
##  50  185.   129   5.1
##  51  182.   554   4.2
##  52  184.   223   4  
##  53  173.    46   4.6
##  54  181.   593   4.3
##  55  182.   489   4.2
##  56  182.   562   4.4
##  57  181    445   4.5
##  58  181.   584   4  
##  59  181.   535   4.4
##  60  179.   530   4.3
##  61  182.   582   4.7
##  62  182.   260   4.1
##  63  172.   613   5  
##  64  166.    84   4.6
##  65  181.   593   4.9
##  66  185.   286   4.7
##  67  182.   587   4.1
##  68  180.   627   5  
##  69  182.   530   4.5
##  70  188.    40   5.5
##  71  186.   152   4  
##  72  184.   201   4.5
##  73  166.    96   4.3
##  74  180.   506   5.2
##  75  181.   546   4.4
##  76  180.   564   4.3
##  77  185.   197   4.1
##  78  167.   265   4.5
##  79  182.   323   4.2
##  80  181.   304   5.3
##  81  180.    75   5.2
##  82  181.   367   4.5
##  83  182.   579   4.6
##  84  183.   284   4.3
##  85  182.   450   4  
##  86  184.   170   4.3
##  87  170.   117   4.7
##  88  180.   538   4.5
##  89  186.   123   4.2
##  90  186.    69   4.3
##  91  168.   128   5.1
##  92  167.   236   4.7
##  93  182.   497   5.2
##  94  170.   271   4.2
##  95  185.   224   4.2
##  96  182.   375   4  
##  97  181.   365   4.5
##  98  183.   306   5.2
##  99  167.    50   5.1
## 100  180.   484   4.7
## # ℹ 900 more rows
quakes %>% select(-stations) %>% print(n=100)
## # A tibble: 1,000 × 4
##       lat  long depth   mag
##     <dbl> <dbl> <int> <dbl>
##   1 -20.4  182.   562   4.8
##   2 -20.6  181.   650   4.2
##   3 -26    184.    42   5.4
##   4 -18.0  182.   626   4.1
##   5 -20.4  182.   649   4  
##   6 -19.7  184.   195   4  
##   7 -11.7  166.    82   4.8
##   8 -28.1  182.   194   4.4
##   9 -28.7  182.   211   4.7
##  10 -17.5  180.   622   4.3
##  11 -21.4  181.   583   4.4
##  12 -12.3  167    249   4.6
##  13 -18.5  182.   554   4.4
##  14 -21    182.   600   4.4
##  15 -20.7  170.   139   6.1
##  16 -15.9  185.   306   4.3
##  17 -13.6  166.    50   6  
##  18 -17.8  182.   590   4.5
##  19 -23.5  180.   570   4.4
##  20 -22.6  180.   598   4.4
##  21 -20.8  181.   576   4.5
##  22 -11.0  166.   211   4.2
##  23 -23.3  180.   512   4.4
##  24 -30.2  182    125   4.7
##  25 -19.7  180.   431   5.4
##  26 -17.9  181.   537   4  
##  27 -14.7  168.   155   4.6
##  28 -16.5  181.   498   5.2
##  29 -21.0  181.   582   4.5
##  30 -19.8  182.   328   4.4
##  31 -22.6  179.   553   4.6
##  32 -16.3  167.    50   4.7
##  33 -15.6  185.   292   4.8
##  34 -23.6  181.   349   4  
##  35 -16.3  186     48   4.5
##  36 -25.8  179.   600   4.3
##  37 -18.7  169.   206   4.5
##  38 -17.6  181.   574   4.6
##  39 -17.7  181.   585   4.1
##  40 -18.8  169.   230   4.4
##  41 -37.4  177.   263   4.7
##  42 -15.3  186.    96   4.6
##  43 -25.0  180.   511   4.4
##  44 -15.5  186.    94   4.3
##  45 -19.2  169.   246   4.6
##  46 -30.1  182.    56   4.9
##  47 -26.4  182.   329   4.5
##  48 -11.8  166.    70   4.4
##  49 -24.1  180.   493   4.3
##  50 -19.0  185.   129   5.1
##  51 -18.8  182.   554   4.2
##  52 -19.3  184.   223   4  
##  53 -22.8  173.    46   4.6
##  54 -21.4  181.   593   4.3
##  55 -20.1  182.   489   4.2
##  56 -19.8  182.   562   4.4
##  57 -22.7  181    445   4.5
##  58 -22.1  181.   584   4  
##  59 -17.8  181.   535   4.4
##  60 -24.2  179.   530   4.3
##  61 -20.7  182.   582   4.7
##  62 -21.2  182.   260   4.1
##  63 -13.8  172.   613   5  
##  64 -11.5  166.    84   4.6
##  65 -20.7  181.   593   4.9
##  66 -17.1  185.   286   4.7
##  67 -20.1  182.   587   4.1
##  68 -22.0  180.   627   5  
##  69 -20.4  182.   530   4.5
##  70 -15.5  188.    40   5.5
##  71 -15.3  186.   152   4  
##  72 -19.9  184.   201   4.5
##  73 -11.6  166.    96   4.3
##  74 -23.7  180.   506   5.2
##  75 -17.7  181.   546   4.4
##  76 -23.5  180.   564   4.3
##  77 -19.2  185.   197   4.1
##  78 -12.1  167.   265   4.5
##  79 -21.8  182.   323   4.2
##  80 -29.0  181.   304   5.3
##  81 -34.0  180.    75   5.2
##  82 -23.8  181.   367   4.5
##  83 -19.6  182.   579   4.6
##  84 -20.1  183.   284   4.3
##  85 -17.7  182.   450   4  
##  86 -19.7  184.   170   4.3
##  87 -21.5  170.   117   4.7
##  88 -23.6  180.   538   4.5
##  89 -15.4  186.   123   4.2
##  90 -15.4  186.    69   4.3
##  91 -15.5  168.   128   5.1
##  92 -13.4  167.   236   4.7
##  93 -20.6  182.   497   5.2
##  94 -19.7  170.   271   4.2
##  95 -15.4  185.   224   4.2
##  96 -19.7  182.   375   4  
##  97 -27.2  181.   365   4.5
##  98 -18.2  183.   306   5.2
##  99 -13.7  167.    50   5.1
## 100 -24.6  180.   484   4.7
## # ℹ 900 more rows
#SELECT AND FILTER
quakes %>% filter(mag=="4.4")
## # A tibble: 101 × 5
##      lat  long depth   mag stations
##    <dbl> <dbl> <int> <dbl>    <int>
##  1 -28.1  182.   194   4.4       15
##  2 -21.4  181.   583   4.4       13
##  3 -18.5  182.   554   4.4       19
##  4 -21    182.   600   4.4       10
##  5 -23.5  180.   570   4.4       13
##  6 -22.6  180.   598   4.4       18
##  7 -23.3  180.   512   4.4       18
##  8 -19.8  182.   328   4.4       17
##  9 -18.8  169.   230   4.4       11
## 10 -25.0  180.   511   4.4       23
## # ℹ 91 more rows
quakes %>% select(lat,long,depth)
## # A tibble: 1,000 × 3
##      lat  long depth
##    <dbl> <dbl> <int>
##  1 -20.4  182.   562
##  2 -20.6  181.   650
##  3 -26    184.    42
##  4 -18.0  182.   626
##  5 -20.4  182.   649
##  6 -19.7  184.   195
##  7 -11.7  166.    82
##  8 -28.1  182.   194
##  9 -28.7  182.   211
## 10 -17.5  180.   622
## # ℹ 990 more rows
quakes %>% select(-lat,-long)
## # A tibble: 1,000 × 3
##    depth   mag stations
##    <int> <dbl>    <int>
##  1   562   4.8       41
##  2   650   4.2       15
##  3    42   5.4       43
##  4   626   4.1       19
##  5   649   4         11
##  6   195   4         12
##  7    82   4.8       43
##  8   194   4.4       15
##  9   211   4.7       35
## 10   622   4.3       19
## # ℹ 990 more rows
#MUTATE
quakes %>% mutate(area=3.14*long*long)
## # A tibble: 1,000 × 6
##      lat  long depth   mag stations    area
##    <dbl> <dbl> <int> <dbl>    <int>   <dbl>
##  1 -20.4  182.   562   4.8       41 103575.
##  2 -20.6  181.   650   4.2       15 102904.
##  3 -26    184.    42   5.4       43 106423.
##  4 -18.0  182.   626   4.1       19 103621.
##  5 -20.4  182.   649   4         11 103964.
##  6 -19.7  184.   195   4         12 106666.
##  7 -11.7  166.    82   4.8       43  86630.
##  8 -28.1  182.   194   4.4       15 103929.
##  9 -28.7  182.   211   4.7       35 103712.
## 10 -17.5  180.   622   4.3       19 101273.
## # ℹ 990 more rows
new_quakes <- quakes %>% select(-stations,-lat) %>% mutate(area=3.14*long*long)
new_quakes %>% print(n=102)
## # A tibble: 1,000 × 4
##      long depth   mag    area
##     <dbl> <int> <dbl>   <dbl>
##   1  182.   562   4.8 103575.
##   2  181.   650   4.2 102904.
##   3  184.    42   5.4 106423.
##   4  182.   626   4.1 103621.
##   5  182.   649   4   103964.
##   6  184.   195   4   106666.
##   7  166.    82   4.8  86630.
##   8  182.   194   4.4 103929.
##   9  182.   211   4.7 103712.
##  10  180.   622   4.3 101273.
##  11  181.   583   4.4 102517.
##  12  167    249   4.6  87571.
##  13  182.   554   4.4 104135.
##  14  182.   600   4.4 103621.
##  15  170.   139   6.1  90661.
##  16  185.   306   4.3 107408.
##  17  166.    50   6    86484.
##  18  182.   590   4.5 103439.
##  19  180.   570   4.4 101487.
##  20  180.   598   4.4 102087.
##  21  181.   576   4.5 103051.
##  22  166.   211   4.2  86860.
##  23  180.   512   4.4 101917.
##  24  182    125   4.7 104009.
##  25  180.   431   5.4 102053.
##  26  181.   537   4   103427.
##  27  168.   155   4.6  88107.
##  28  181.   498   5.2 102631.
##  29  181.   582   4.5 103404.
##  30  182.   328   4.4 104433.
##  31  179.   553   4.6 100879.
##  32  167.    50   4.7  87299.
##  33  185.   292   4.8 107525.
##  34  181.   349   4   102642.
##  35  186     48   4.5 108631.
##  36  179.   600   4.3 100980.
##  37  169.   206   4.5  89926.
##  38  181.   574   4.6 103188.
##  39  181.   585   4.1 103325.
##  40  169.   230   4.4  90032.
##  41  177.   263   4.7  98129.
##  42  186.    96   4.6 108748.
##  43  180.   511   4.4 101533.
##  44  186.    94   4.3 108678.
##  45  169.   246   4.6  90117.
##  46  182.    56   4.9 104353.
##  47  182.   329   4.5 103667.
##  48  166.    70   4.4  86860.
##  49  180.   493   4.3 101826.
##  50  185.   129   5.1 107757.
##  51  182.   554   4.2 104410.
##  52  184.   223   4   106794.
##  53  173.    46   4.6  94194.
##  54  181.   593   4.3 102495.
##  55  182.   489   4.2 104192.
##  56  182.   562   4.4 104158.
##  57  181    445   4.5 102870.
##  58  181.   584   4   102415.
##  59  181.   535   4.4 103268.
##  60  179.   530   4.3 100834.
##  61  182.   582   4.7 103496.
##  62  182.   260   4.1 104467.
##  63  172.   613   5    93305.
##  64  166.    84   4.6  86755.
##  65  181.   593   4.9 103336.
##  66  185.   286   4.7 107385.
##  67  182.   587   4.1 103553.
##  68  180.   627   5   101307.
##  69  182.   530   4.5 103849.
##  70  188.    40   5.5 110756.
##  71  186.   152   4   108398.
##  72  184.   201   4.5 106713.
##  73  166.    96   4.3  86734.
##  74  180.   506   5.2 101725.
##  75  181.   546   4.4 103131.
##  76  180.   564   4.3 101781.
##  77  185.   197   4.1 107118.
##  78  167.   265   4.5  87634.
##  79  182.   323   4.2 103678.
##  80  181.   304   5.3 102995.
##  81  180.    75   5.2 101974.
##  82  181.   367   4.5 102858.
##  83  182.   579   4.6 104444.
##  84  183.   284   4.3 105616.
##  85  182.   450   4   103667.
##  86  184.   170   4.3 106666.
##  87  170.   117   4.7  91281.
##  88  180.   538   4.5 101691.
##  89  186.   123   4.2 108982.
##  90  186.    69   4.3 109146.
##  91  168.   128   5.1  88128.
##  92  167.   236   4.7  87634.
##  93  182.   497   5.2 104032.
##  94  170.   271   4.2  90437.
##  95  185.   224   4.2 107769.
##  96  182.   375   4   104467.
##  97  181.   365   4.5 102995.
##  98  183.   306   5.2 105627.
##  99  167.    50   5.1  87090.
## 100  180.   484   4.7 101646.
## 101  186.   108   4.1 108176.
## 102  178.   583   4.6  99947.
## # ℹ 898 more rows
#MUTATE
quakes %>% mutate(longlat=long+lat)
## # A tibble: 1,000 × 6
##      lat  long depth   mag stations longlat
##    <dbl> <dbl> <int> <dbl>    <int>   <dbl>
##  1 -20.4  182.   562   4.8       41    161.
##  2 -20.6  181.   650   4.2       15    160.
##  3 -26    184.    42   5.4       43    158.
##  4 -18.0  182.   626   4.1       19    164.
##  5 -20.4  182.   649   4         11    162.
##  6 -19.7  184.   195   4         12    165.
##  7 -11.7  166.    82   4.8       43    154.
##  8 -28.1  182.   194   4.4       15    154.
##  9 -28.7  182.   211   4.7       35    153 
## 10 -17.5  180.   622   4.3       19    162.
## # ℹ 990 more rows
quakesbaru <- quakes %>% select(-lat,-long) %>% mutate(jumlah=mag+stations)
quakesbaru
## # A tibble: 1,000 × 4
##    depth   mag stations jumlah
##    <int> <dbl>    <int>  <dbl>
##  1   562   4.8       41   45.8
##  2   650   4.2       15   19.2
##  3    42   5.4       43   48.4
##  4   626   4.1       19   23.1
##  5   649   4         11   15  
##  6   195   4         12   16  
##  7    82   4.8       43   47.8
##  8   194   4.4       15   19.4
##  9   211   4.7       35   39.7
## 10   622   4.3       19   23.3
## # ℹ 990 more rows