a. Find and get a dataset from the datasets available within R. Perform exploratory data analysis (EDA) and prepare a codebook on that dataset using a newer method in R

Codebook

x <- enframe(get_label(quakes))

colnames(x) <- c("variable", "details")

x$details[1] = "Latitude of event"
x$details[2] = "Longitude"
x$details[3] = "Depth (km)"
x$details[4] = "Richter Magnitude"
x$details[5] = "Number of stations reporting"

x

## # A tibble: 5 x 2
##   variable details                     
##   <chr>    <chr>                       
## 1 lat      Latitude of event           
## 2 long     Longitude                   
## 3 depth    Depth (km)                  
## 4 mag      Richter Magnitude           
## 5 stations Number of stations reporting

new_codebook_rmd()
codebook(quakes)

## No missing values.

Metadata

Description

Dataset name: quakes

The dataset has N=1000 rows and 5 columns. 1000 rows have no missing values on any column.

Metadata for search engines

Date published: 2021-12-31

x
lat
long
depth
mag
stations

#Variables

lat

Distribution

Distribution of values for lat

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
lat	numeric	0	1	-39	-20	-11	-20.64275	5.028791	<U+2581><U+2581><U+2585><U+2587><U+2583>	NA

long

Distribution

Distribution of values for long

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
long	numeric	0	1	166	181	188	179.462	6.069497	<U+2582><U+2581><U+2581><U+2587><U+2583>	NA

depth

Distribution

Distribution of values for depth

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
depth	numeric	0	1	40	247	680	311.371	215.5355	<U+2587><U+2583><U+2582><U+2583><U+2585>	NA

mag

Distribution

Distribution of values for mag

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
mag	numeric	0	1	4	4.6	6.4	4.6204	0.402773	<U+2587><U+2587><U+2583><U+2581><U+2581>	NA

stations

Distribution

Distribution of values for stations

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
stations	numeric	0	1	10	27	132	33.418	21.90039	<U+2587><U+2582><U+2581><U+2581><U+2581>	NA

Missingness report

Codebook table

name	data_type	complete_rate	min	median	max	mean	sd	hist	label
lat	numeric	1	-39	-20.3	-10.7	-20.64275	5.028791	<U+2581><U+2581><U+2585><U+2587><U+2583>	NA
long	numeric	1	166	181.4	188.1	179.46202	6.069497	<U+2582><U+2581><U+2581><U+2587><U+2583>	NA
depth	numeric	1	40	247.0	680.0	311.37100	215.535498	<U+2587><U+2583><U+2582><U+2583><U+2585>	NA
mag	numeric	1	4	4.6	6.4	4.62040	0.402773	<U+2587><U+2587><U+2583><U+2581><U+2581>	NA
stations	numeric	1	10	27.0	132.0	33.41800	21.900386	<U+2587><U+2582><U+2581><U+2581><U+2581>	NA

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": "quakes",
  "datePublished": "2021-12-31",
  "description": "The dataset has N=1000 rows and 5 columns.\n1000 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n|name     |label | n_missing|\n|:--------|:-----|---------:|\n|lat      |NA    |         0|\n|long     |NA    |         0|\n|depth    |NA    |         0|\n|mag      |NA    |         0|\n|stations |NA    |         0|\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.2).",
  "keywords": ["lat", "long", "depth", "mag", "stations"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "lat",
      "@type": "propertyValue"
    },
    {
      "name": "long",
      "@type": "propertyValue"
    },
    {
      "name": "depth",
      "@type": "propertyValue"
    },
    {
      "name": "mag",
      "@type": "propertyValue"
    },
    {
      "name": "stations",
      "@type": "propertyValue"
    }
  ]
}`

Scatter plot of magnitude versus depth

ggplot(quakes, aes(x=depth, y=mag))+geom_bin2d()+labs(title="Magnitude of earthquake according to the depth", x="Depth(km)", y="Magnitude(Scalar Ritcher)")

Analysis : null / no relationship

Line graph of number of station versus depth

ggplot(quakes, aes(x=depth, y=stations))+geom_bar(stat="identity")+labs(title="Number of stations reporting about earthquake depending on depth", x="Depth(km)", y="Number of Stations")

Analysis : Low amount of stations are alerted between 300km-400km, Moderate amount of stations are alerted between 500km-700km, High amount of stations are alerted below 300km depth

Earthquakes plotted on map

ggplot(quakes, aes(long,lat))+geom_point(size = .25, show.legend = FALSE) + coord_quickmap() + labs(title="Earthquakes plotted on map", x="Longitude", y="Latitude")

Analysis : Earthquakes occured the most in at latitude between -25 to -5 and longitude between 180 to 185

Mean of Depth

mean(quakes$depth)

## [1] 311.371

Median of Depth

median(quakes$depth)

## [1] 247

Interquartile range of Depth

IQR(quakes$depth)

## [1] 444

Mean of Magnitude

mean(quakes$mag)

## [1] 4.6204

Median of Magnitude

median(quakes$mag)

## [1] 4.6

Interquartile range of Magnitude

IQR(quakes$mag)

## [1] 0.6

b. Demonstrate these FIVE (5) functions of dplyr for data manipulation:

i) filter()

Only show rows with mag greater than 5.5

quakes %>% filter(mag>5.5)

##       lat   long depth mag stations
## 1  -20.70 169.92   139 6.1       94
## 2  -13.64 165.96    50 6.0       83
## 3  -22.55 185.90    42 5.7       76
## 4  -23.34 184.50    56 5.7      106
## 5  -15.56 167.62   127 6.4      122
## 6  -26.00 182.12   205 5.6       98
## 7  -32.22 180.20   216 5.7       90
## 8  -22.13 180.38   577 5.7      104
## 9  -24.57 178.40   562 5.6       80
## 10 -15.33 186.75    48 5.7      123
## 11 -17.84 181.30   535 5.7      112
## 12 -22.91 183.95    64 5.9      118
## 13 -34.68 179.82    75 5.6       79
## 14 -19.89 174.46   546 5.7       99
## 15 -18.82 182.21   417 5.6      129
## 16 -37.03 177.52   153 5.6       87
## 17 -11.40 166.07    93 5.6       94
## 18 -15.93 167.91   183 5.6      109
## 19 -21.08 180.85   627 5.9      119
## 20 -21.14 174.21    40 5.7       78
## 21 -12.23 167.02   242 6.0      132
## 22 -17.85 181.44   589 5.6      115
## 23 -20.25 184.75   107 5.6      121
## 24 -21.59 170.56   165 6.0      119

ii) arrange()

Sort i) in ascending order of stations

quakes %>% filter(mag>5.5) %>% arrange(stations)

##       lat   long depth mag stations
## 1  -22.55 185.90    42 5.7       76
## 2  -21.14 174.21    40 5.7       78
## 3  -34.68 179.82    75 5.6       79
## 4  -24.57 178.40   562 5.6       80
## 5  -13.64 165.96    50 6.0       83
## 6  -37.03 177.52   153 5.6       87
## 7  -32.22 180.20   216 5.7       90
## 8  -20.70 169.92   139 6.1       94
## 9  -11.40 166.07    93 5.6       94
## 10 -26.00 182.12   205 5.6       98
## 11 -19.89 174.46   546 5.7       99
## 12 -22.13 180.38   577 5.7      104
## 13 -23.34 184.50    56 5.7      106
## 14 -15.93 167.91   183 5.6      109
## 15 -17.84 181.30   535 5.7      112
## 16 -17.85 181.44   589 5.6      115
## 17 -22.91 183.95    64 5.9      118
## 18 -21.08 180.85   627 5.9      119
## 19 -21.59 170.56   165 6.0      119
## 20 -20.25 184.75   107 5.6      121
## 21 -15.56 167.62   127 6.4      122
## 22 -15.33 186.75    48 5.7      123
## 23 -18.82 182.21   417 5.6      129
## 24 -12.23 167.02   242 6.0      132

Sort i) in descending order of stations

quakes %>% filter(mag>5.5) %>% arrange(desc(stations))

##       lat   long depth mag stations
## 1  -12.23 167.02   242 6.0      132
## 2  -18.82 182.21   417 5.6      129
## 3  -15.33 186.75    48 5.7      123
## 4  -15.56 167.62   127 6.4      122
## 5  -20.25 184.75   107 5.6      121
## 6  -21.08 180.85   627 5.9      119
## 7  -21.59 170.56   165 6.0      119
## 8  -22.91 183.95    64 5.9      118
## 9  -17.85 181.44   589 5.6      115
## 10 -17.84 181.30   535 5.7      112
## 11 -15.93 167.91   183 5.6      109
## 12 -23.34 184.50    56 5.7      106
## 13 -22.13 180.38   577 5.7      104
## 14 -19.89 174.46   546 5.7       99
## 15 -26.00 182.12   205 5.6       98
## 16 -20.70 169.92   139 6.1       94
## 17 -11.40 166.07    93 5.6       94
## 18 -32.22 180.20   216 5.7       90
## 19 -37.03 177.52   153 5.6       87
## 20 -13.64 165.96    50 6.0       83
## 21 -24.57 178.40   562 5.6       80
## 22 -34.68 179.82    75 5.6       79
## 23 -21.14 174.21    40 5.7       78
## 24 -22.55 185.90    42 5.7       76

iii) mutate()

Add a new column based on current column depth

Add column depthinmeter based on column depth (in km)

quakes %>% filter(mag>5.5) %>% select(depth) %>% mutate(depthinmeter = depth*1000)

##    depth depthinmeter
## 1    139       139000
## 2     50        50000
## 3     42        42000
## 4     56        56000
## 5    127       127000
## 6    205       205000
## 7    216       216000
## 8    577       577000
## 9    562       562000
## 10    48        48000
## 11   535       535000
## 12    64        64000
## 13    75        75000
## 14   546       546000
## 15   417       417000
## 16   153       153000
## 17    93        93000
## 18   183       183000
## 19   627       627000
## 20    40        40000
## 21   242       242000
## 22   589       589000
## 23   107       107000
## 24   165       165000

iv) select()

Select specific column

quakes %>% filter(mag>5.5) %>% select(depth)

##    depth
## 1    139
## 2     50
## 3     42
## 4     56
## 5    127
## 6    205
## 7    216
## 8    577
## 9    562
## 10    48
## 11   535
## 12    64
## 13    75
## 14   546
## 15   417
## 16   153
## 17    93
## 18   183
## 19   627
## 20    40
## 21   242
## 22   589
## 23   107
## 24   165

v) summarise()

Creates a new dataframe with selected column

quakes %>% filter(mag>5.5) %>%  summarise(depth,mag)

##    depth mag
## 1    139 6.1
## 2     50 6.0
## 3     42 5.7
## 4     56 5.7
## 5    127 6.4
## 6    205 5.6
## 7    216 5.7
## 8    577 5.7
## 9    562 5.6
## 10    48 5.7
## 11   535 5.7
## 12    64 5.9
## 13    75 5.6
## 14   546 5.7
## 15   417 5.6
## 16   153 5.6
## 17    93 5.6
## 18   183 5.6
## 19   627 5.9
## 20    40 5.7
## 21   242 6.0
## 22   589 5.6
## 23   107 5.6
## 24   165 6.0

AAQ1

CHE WAN AR-RAYYAN

12/30/2021

a. Find and get a dataset from the datasets available within R. Perform exploratory data analysis (EDA) and prepare a codebook on that dataset using a newer method in R

Codebook

Metadata

Description

lat

Distribution

Summary statistics

long

Distribution

Summary statistics

depth

Distribution

Summary statistics

mag

Distribution

Summary statistics

stations

Distribution

Summary statistics

Missingness report

Codebook table

Scatter plot of magnitude versus depth

Line graph of number of station versus depth

Earthquakes plotted on map

Mean of Depth

Median of Depth

Interquartile range of Depth

Mean of Magnitude

Median of Magnitude

Interquartile range of Magnitude

b. Demonstrate these FIVE (5) functions of dplyr for data manipulation: