Anya’s Study Aims
For my assignment I settled on four research questions:
Which countries should I avoid if I wanted to reduce the likelihood of getting attacked by a shark?
Based on the data of which country has the highest amount of attacks, which area of that country do shark attacks occur the most?
Which species of shark is the most aggressive?
What year had the most shark attacks?
I have always associated Australia with shark attacks so I’m interested to know if they have the highest number of recorded attacks. I have also always been strangely fascinated by sharks and how they behave towards humans. I think this is because I have a huge fear of them and experiencing a shark attack is the worst thing I can think of! Therefore I figured finding a dataset with years and years worth of attacks would make my coding experience interesting and also would help me reduce my chances of ever being bitten by a shark, as I now know some areas in the world to steer clear of. The years spanning from the early 1900s to 2018 gives me freedom to work on data in specific years but also makes cleaning more difficult as there is simply so much data with some typos and different values. I plan to present my data visually in a range of eye catching and clear ways.
The data itself was called, Global Shark Attacks https://www.kaggle.com/datasets/teajay/global-shark-attacks?resource=download. I found the data on kaggle and it hasn’t been updated in 7 years however there were hundreds of attacks recorded. Originally it was compiled from Global Shark Attack File, who allow people to report an incident themselves on their website but have a range of people across different continents who are “authorized to gather data for forensic analysis of shark incidents on behalf of the Global Shark Attack File.”
All code for cleaning, annotating, and analysing the data, as well as plotting results, is contained in the Quarto document https://rpubs.com/anyabogdanovic/dataskillsassingment used to generate this report. For some R coding I used Chatgpt and and youtube tutorials to help troubleshoot problems, identify useful functions, and refine my methods. All research questions and design decisions were my own.
:: opts_knit$ set (root.dir = "/Users/anyabogdanovic/Documents/DataSkills_2" )library (here)
here() starts at /Users/anyabogdanovic/Documents
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.4 ✔ readr 2.1.5
✔ forcats 1.0.0 ✔ stringr 1.5.1
✔ ggplot2 3.5.1 ✔ tibble 3.2.1
✔ lubridate 1.9.4 ✔ tidyr 1.3.1
✔ purrr 1.0.4
── 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
Load Dataset
<- here ("/Users/anyabogdanovic/Documents/DataSkills_2" , "sharkattacks.csv" ) |> read_csv ()
Warning: One or more parsing issues, call `problems()` on your data frame for details,
e.g.:
dat <- vroom(...)
problems(dat)
Rows: 25637 Columns: 1
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (1): Case Number;Date;Year;Type;Country;Area;Location;Activity;Name;Sex ...
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
# A tibble: 25,637 × 1
Case Number;Date;Year;Type;Country;Area;Location;Activity;Name;Sex ;Age;Inj…¹
<chr>
1 2018.06.25;25-Jun-2018;2018;Boating;USA;California;Oceanside, San Diego Coun…
2 2018.06.18;18-Jun-2018;2018;Unprovoked;USA;Georgia;St. Simon Island, Glynn C…
3 2018.06.09;09-Jun-2018;2018;Invalid;USA;Hawaii;Habush, Oahu;Surfing;John Den…
4 2018.06.08;08-Jun-2018;2018;Unprovoked;AUSTRALIA;New South Wales;Arrawarra H…
5 2018.06.04;04-Jun-2018;2018;Provoked;MEXICO;Colima;La Ticla;Free diving;Gust…
6 2018.06.03.b;03-Jun-2018;2018;Unprovoked;AUSTRALIA;New South Wales;Flat Rock…
7 2018.06.03.a;03-Jun-2018;2018;Unprovoked;BRAZIL;Pernambuco;Piedade Beach, Re…
8 2018.05.27;27-May-2018;2018;Unprovoked;USA;Florida;Lighhouse Point Park, Pon…
9 2018.05.26.b;26-May-2018;2018;Unprovoked;USA;Florida;Cocoa Beach, Brevard C…
10 2018.05.26.a;26-May-2018;2018;Unprovoked;USA;Florida;Daytona Beach, Volusia …
# ℹ 25,627 more rows
# ℹ abbreviated name:
# ¹`Case Number;Date;Year;Type;Country;Area;Location;Activity;Name;Sex ;Age;Injury;Fatal (Y/N);Time;Species ;Investigator or Source;pdf;href formula;href;Case Number;Case Number;original order;;`
Start to clean
there was no spaces in my data set, only ;
library (readr)<- read_delim ("sharkattacks.csv" , delim = ";" )
New names:
• `Case Number` -> `Case Number...1`
• `Case Number` -> `Case Number...20`
• `Case Number` -> `Case Number...21`
• `` -> `...23`
• `` -> `...24`
Warning: One or more parsing issues, call `problems()` on your data frame for details,
e.g.:
dat <- vroom(...)
problems(dat)
Rows: 25723 Columns: 24
── Column specification ────────────────────────────────────────────────────────
Delimiter: ";"
chr (20): Case Number...1, Date, Type, Country, Area, Location, Activity, Na...
dbl (2): Year, original order
lgl (2): ...23, ...24
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
[1] "Case Number...1" "Date" "Year"
[4] "Type" "Country" "Area"
[7] "Location" "Activity" "Name"
[10] "Sex " "Age" "Injury"
[13] "Fatal (Y/N)" "Time" "Species "
[16] "Investigator or Source" "pdf" "href formula"
[19] "href" "Case Number...20" "Case Number...21"
[22] "original order" "...23" "...24"
Filter data down
Only from 2008 to 2018 to make cleaning and plotting easier
<- sharkattacks |> filter (Year >= 2008 & Year <= 2018 )head (sharkattacks_filteredd)
# A tibble: 6 × 24
`Case Number...1` Date Year Type Country Area Location Activity Name
<chr> <chr> <dbl> <chr> <chr> <chr> <chr> <chr> <chr>
1 2018.06.25 25-Jun-20… 2018 Boat… USA Cali… Oceansi… Paddling "Jul…
2 2018.06.18 18-Jun-20… 2018 Unpr… USA Geor… St. Sim… Standing "Ady…
3 2018.06.09 09-Jun-20… 2018 Inva… USA Hawa… Habush,… Surfing "Joh…
4 2018.06.08 08-Jun-20… 2018 Unpr… AUSTRA… New … Arrawar… Surfing "mal…
5 2018.06.04 04-Jun-20… 2018 Prov… MEXICO Coli… La Ticla Free di… "Gus…
6 2018.06.03.b 03-Jun-20… 2018 Unpr… AUSTRA… New … Flat Ro… Kite su… "Chr…
# ℹ 15 more variables: `Sex ` <chr>, Age <chr>, Injury <chr>,
# `Fatal (Y/N)` <chr>, Time <chr>, `Species ` <chr>,
# `Investigator or Source` <chr>, pdf <chr>, `href formula` <chr>,
# href <chr>, `Case Number...20` <chr>, `Case Number...21` <chr>,
# `original order` <dbl>, ...23 <lgl>, ...24 <lgl>
unique (sharkattacks$ Year)
[1] 2018 2017 NA 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005
[16] 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1984 1994 1993 1992 1991
[31] 1990 1989 1969 1988 1987 1986 1985 1983 1982 1981 1980 1979 1978 1977 1976
[46] 1975 1974 1973 1972 1971 1970 1968 1967 1966 1965 1964 1963 1962 1961 1960
[61] 1959 1958 1957 1956 1955 1954 1953 1952 1951 1950 1949 1948 1848 1947 1946
[76] 1945 1944 1943 1942 1941 1940 1939 1938 1937 1936 1935 1934 1933 1932 1931
[91] 1930 1929 1928 1927 1926 1925 1924 1923 1922 1921 1920 1919 1918 1917 1916
[106] 1915 1914 1913 1912 1911 1910 1909 1908 1907 1906 1905 1904 1903 1902 1901
[121] 1900 1899 1898 1897 1896 1895 1894 1893 1892 1891 1890 1889 1888 1887 1886
[136] 1885 1884 1883 1882 1881 1880 1879 1878 1877 1876 1875 1874 1873 1872 1871
[151] 1870 1869 1868 1867 1866 1865 1864 1863 1862 1861 1860 1859 1858 1857 1856
[166] 1855 1853 1852 1851 1850 1849 1847 1846 1845 1844 1842 1841 1840 1839 1837
[181] 1836 1835 1834 1832 1831 1830 1829 1828 1827 1826 1825 1823 1822 1819 1818
[196] 1817 1816 1815 1812 1811 1810 1808 1807 1805 1804 1803 1802 1801 1800 1797
[211] 1792 1791 1788 1787 1786 1785 1784 1783 1780 1779 1776 1771 1767 1764 1758
[226] 1753 1751 1749 1755 1748 1742 1738 1733 1723 1721 1703 1700 1642 1638 1637
[241] 1617 1595 1580 1555 1554 1543 500 77 5 0
nrow (sharkattacks_filteredd)colnames (sharkattacks_filteredd)
[1] "Case Number...1" "Date" "Year"
[4] "Type" "Country" "Area"
[7] "Location" "Activity" "Name"
[10] "Sex " "Age" "Injury"
[13] "Fatal (Y/N)" "Time" "Species "
[16] "Investigator or Source" "pdf" "href formula"
[19] "href" "Case Number...20" "Case Number...21"
[22] "original order" "...23" "...24"
Clean the data
<- sharkattacks_filteredd |> rename (Species = ` Species ` )colnames (sharkattacks_filteredd)
[1] "Case Number...1" "Date" "Year"
[4] "Type" "Country" "Area"
[7] "Location" "Activity" "Name"
[10] "Sex " "Age" "Injury"
[13] "Fatal (Y/N)" "Time" "Species"
[16] "Investigator or Source" "pdf" "href formula"
[19] "href" "Case Number...20" "Case Number...21"
[22] "original order" "...23" "...24"
Working towards finding the most aggressive species
Selecting species
Many of the Species were all worded differently. I decided to make the decision to narrow it down to only 5 species of Sharks that I saw appeared the most
library (stringr)<- sharkattacks_filteredd |> filter (str_detect (tolower (Species), "white shark|bull shark|tiger shark|wobbegong shark|hammerhead shark" ))head (sharkattacks_filteredd2)
# A tibble: 6 × 24
`Case Number...1` Date Year Type Country Area Location Activity Name
<chr> <chr> <dbl> <chr> <chr> <chr> <chr> <chr> <chr>
1 2018.06.25 25-Jun-20… 2018 Boat… USA Cali… Oceansi… Paddling "Jul…
2 2018.06.04 04-Jun-20… 2018 Prov… MEXICO Coli… La Ticla Free di… "Gus…
3 2018.06.03.a 03-Jun-20… 2018 Unpr… BRAZIL Pern… Piedade… Swimming "Jos…
4 2018.05.26.b 26-May-20… 2018 Unpr… USA Flor… Cocoa B… Walking "Cod…
5 2018.04.28.b 28-Apr-20… 2018 Unpr… COSTA … Coco… Manueli… Scuba d… "mal…
6 2018.04.24 24-Apr-20… 2018 Unpr… AUSTRA… West… South P… Surfing "Nat…
# ℹ 15 more variables: `Sex ` <chr>, Age <chr>, Injury <chr>,
# `Fatal (Y/N)` <chr>, Time <chr>, Species <chr>,
# `Investigator or Source` <chr>, pdf <chr>, `href formula` <chr>,
# href <chr>, `Case Number...20` <chr>, `Case Number...21` <chr>,
# `original order` <dbl>, ...23 <lgl>, ...24 <lgl>
|> print (n = Inf )
# A tibble: 329 × 24
`Case Number...1` Date Year Type Country Area Location Activity Name
<chr> <chr> <dbl> <chr> <chr> <chr> <chr> <chr> <chr>
1 2018.06.25 25-Jun-… 2018 Boat… USA "Cal… "Oceans… "Paddli… "Jul…
2 2018.06.04 04-Jun-… 2018 Prov… MEXICO "Col… "La Tic… "Free d… "Gus…
3 2018.06.03.a 03-Jun-… 2018 Unpr… BRAZIL "Per… "Piedad… "Swimmi… "Jos…
4 2018.05.26.b 26-May-… 2018 Unpr… USA "Flo… "Cocoa … "Walkin… "Cod…
5 2018.04.28.b 28-Apr-… 2018 Unpr… COSTA … "Coc… "Manuel… "Scuba … "mal…
6 2018.04.24 24-Apr-… 2018 Unpr… AUSTRA… "Wes… "South … "Surfin… "Nat…
7 2018.04.23 23-Apr-… 2018 Unpr… MALDIV… "Ali… "Madoog… "Fishin… "Ahm…
8 2018.04.22 22-Apr-… 2018 Unpr… SOUTH … "Wes… "Robber… "Paddle… "mal…
9 2018.04.15.d 15-Apr-… 2018 Unpr… THAILA… "Hua… "Sai No… "Swimmi… "Wer…
10 2018.04.14 14-Apr-… 2018 Unpr… BAHAMAS "New… "Nirvan… "Surfin… "Bru…
11 2018.04.05 05-Apr-… 2018 Unpr… BAHAMAS <NA> "Bimini" "Swimmi… "Sha…
12 2018.04.03 03-Apr-… 2018 Unpr… SOUTH … "Eas… "St. Fr… "Surfin… "Ros…
13 2018.03.31 31-Mar-… 2018 Unpr… USA "Haw… "Kukio … "Stand-… "mal…
14 2018.03.14 14-Mar-… 2018 Unpr… AUSTRA… "Wes… "Waterm… "Wading" "Luk…
15 2018.02.23 23-Feb-… 2018 Unpr… AUSTRA… "New… "Little… "Swimmi… "Ann…
16 2018.02.15 15-Feb-… 2018 Unpr… AUSTRA… "New… "Surf B… "Walkin… "Ada…
17 2018.01.28 28-Jan-… 2018 Unpr… AUSTRA… "Wes… "Cone B… <NA> "mal…
18 2018.01.21 21-Jan-… 2018 Unpr… NEW CA… <NA> "Nouvil… "Spearf… "mal…
19 2018.01.13 13-Jan-… 2018 Unpr… AUSTRA… "New… "Martin… "Free d… "Cal…
20 2018.01.05 05-Jan-… 2018 Unpr… AUSTRA… "Wes… "South … "Surfin… "Jus…
21 2017.12.31 31-Dec-… 2017 Unpr… USA "Haw… "Hultin… "Surfin… "Mar…
22 2017.11.30.b 30-Nov-… 2017 Unpr… COSTA … "Coc… "Manuel… "Scuba … "__ …
23 2017.11.30.a 30-Nov-… 2017 Unpr… COSTA … "Coc… "Manuel… "Scuba … "Roh…
24 2017.11.24 24-Nov-… 2017 Unpr… USA "Cal… "Stillw… "Spearf… "Gri…
25 2017.11.04 04-Nov-… 2017 Unpr… CUBA "Hol… "Guarda… "Night … "Jes…
26 2017.10.28 28-Oct-… 2017 Unpr… AUSTRA… "New… "Birubi… "Surfin… "mal…
27 2017.10.22 22-Oct-… 2017 Unpr… AUSTRA… "Sou… "Norman… "Kayaki… "Sar…
28 2017.10.09 09-Oct-… 2017 Unpr… USA "Haw… "Davids… "Surfin… "Mit…
29 2017.09.25.a 25-Sep-… 2017 Unpr… AUSTRA… "Wes… "Gracet… "Surfin… "Cat…
30 2017.09.14 Sep-2017 2017 Boat… AUSTRA… "Wes… "Espera… "Fishin… <NA>
31 2017.09.10.a 10-Sep-… 2017 Unpr… AUSTRA… "New… "Iluka … "Surfin… "Abe…
32 2017.08.29 29-Aug-… 2017 Unpr… AUSTRA… "Vic… "Cathed… "Surfin… "Mar…
33 2017.08.23 23-Aug-… 2017 Unpr… USA "Mas… "Marcon… "SUP" "Cle…
34 2017.08.01 01-Aug-… 2017 Boat… USA "Cal… "Betwee… "Kayaki… "Pat…
35 2017.07.23.b 23-Jul-… 2017 Unpr… USA "New… "Ventno… <NA> "Isa…
36 2017.07.20.b 20-Jul-… 2017 Boat… USA "Cal… "Stearn… "Kayaki… "Bre…
37 2017.07.20.a 20-Jul-… 2017 Unpr… USA "Cal… "Seal R… "SUP" "Rol…
38 2017.07.14.b 14-Jul-… 2017 Unpr… USA "Was… "South … "Surfin… "MK"
39 2017.07.11 11-Jul-… 2017 Boat… USA "Cal… "Santa … "Kayaki… "Ste…
40 2017.07.09 09-Jul-… 2017 Unpr… USA "Flo… "Haulov… "Swimmi… "Elv…
41 2017.07.07.R Reporte… 2017 Prov… MEXICO "Tab… "Sánche… "Fishin… "And…
42 2017.07.07 07-Jul-… 2017 Unpr… SOUTH … "Eas… "Nahoon… "Surfin… "Zoe…
43 2017.06.18.b 18-Jun-… 2017 Unpr… USA "Sou… "Burkes… "Swimmi… "Reg…
44 2017.06.18.a 18-Jun-… 2017 Unpr… REUNION <NA> "Roches… "Body b… "Jul…
45 2017.06.11 11-Jun-… 2017 Unpr… AUSTRA… "Wes… "Point … "Body b… "Pau…
46 2017.06.02 02-Jun-… 2017 Unpr… BAHAMAS "New… "Athol … "Snorke… "Tif…
47 2017.05.28 28-May-… 2017 Unpr… USA "Flo… "Off Ju… "Feedin… "Ran…
48 2017.04.17.a 17-Apr-… 2017 Unpr… AUSTRA… "Wes… "Kelpie… "Surfin… "Lae…
49 2017.04.14 14-Apr-… 2017 Unpr… USA "Haw… "Kekaha… "Surfin… "Bab…
50 2017.04.02.a 02-Apr-… 2017 Unpr… USA "Flo… "Destin… "Swimmi… "Cai…
51 2017.03.18 18-Mar-… 2017 Boat… USA "Cal… "Monter… "Kayaki… "Bri…
52 2017.02.25 25-Feb-… 2017 Unpr… AUSTRA… "Wes… "Mauds … "Snorke… "fem…
53 2017.02.06.a 06-Feb-… 2017 Boat… SOUTH … "Kwa… "Eastmo… "Kayak … "Mur…
54 2017.02.01.b 01-Feb-… 2017 Boat… USA "Sou… "16 mil… "Taggin… "Chi…
55 2017.01.21 21-Jan-… 2017 Unpr… AUSTRA… "Que… "Boot R… "Scuba … "Cra…
56 2017.01.09 09-Jan-… 2017 Unpr… INDONE… "Bal… "Balian… "Surfin… "Dan…
57 2016.12.19 19-Dec-… 2016 Unpr… SOUTH … "Wes… "Keurbo… "Surf s… "Ben…
58 2016.12.06 06-Dec-… 2016 Prov… AUSTRA… "New… "Merimb… "Surf f… "Jes…
59 2016.12.01 01-Dec-… 2016 Unpr… AUSTRA… "New… "Booti … "Surfin… "Col…
60 2016.11.14 14-Nov-… 2016 Unpr… USA "Haw… "Kamaol… "Floati… "Bar…
61 2016.10.13.R 13-Oct-… 2016 Inva… MEXICO <NA> "Guadal… "Cage D… "Min…
62 2016.09.26 26-Sep-… 2016 Unpr… AUSTRA… "New… "Lighth… "Surfin… "Coo…
63 2016.09.07 07-Sep-… 2016 Unpr… USA "Haw… "Makaha… "Swimmi… "Lul…
64 2016.09.01 01-Sep-… 2016 Unpr… USA "Cal… "Refugi… "Spearf… "Tyl…
65 2016.08.29.b 29-Aug-… 2016 Unpr… USA "Flo… "New Sm… "Surfin… "Sam…
66 2016.08.27 27-Aug-… 2016 Unpr… REUNION <NA> "Boucan… "Surfin… "Lau…
67 2016.08.06 06-Aug-… 2016 Unpr… USA "Haw… "Maui" "SUP Fo… "Con…
68 2016.07.28 28-Jul-… 2016 Boat… AUSTRA… "Wes… "Near A… "Kayaki… "Ian…
69 2016.07.23.a 23-Jul-… 2016 Unpr… BAHAMAS "Aba… "Green … "Spearf… "Ste…
70 2016.07.17 17-Jul-… 2016 Boat… USA "Ala… "8 mile… "Fishin… "Occ…
71 2016.07.15.b 15-Jul-… 2016 Unpr… USA "Cal… "Surfsi… "Kite s… "Lee…
72 2016.07.08 08-Jul-… 2016 Boat… USA "Cal… "Capito… "Fishin… "Mar…
73 2016.07.07.a 07-Jul-… 2016 Boat… USA "Cal… "Off Pa… "Fishin… "24'…
74 2016.06.23 23-Jun-… 2016 Unpr… SOUTH … "Wes… "Ryspun… "Spearf… "Ren…
75 2016.05.31 31-May-… 2016 Unpr… AUSTRA… "Wes… "Falcon… "Surfin… "Ben…
76 2016.05.21.b 21-May-… 2016 Unpr… USA "Flo… "St. Pe… "Swimmi… "Kry…
77 2016.04.25 25-Apr-… 2016 Unpr… INDONE… "Bal… "Balian" "Surfin… "Rya…
78 2016.04.22 22-Apr-… 2016 Unpr… SOUTH … "Wes… "Robber… "Surf-s… "Dav…
79 2016.04.19 19-Apr-… 2016 Unpr… AUSTRA… "New… "First … "Swimmi… "Zak…
80 2016.04.13 13-Apr-… 2016 Unpr… USA "Flo… "Off Si… "Spearf… "Kyl…
81 2016.04.09 09-Apr-… 2016 Unpr… NEW CA… "Gra… "Poe Be… "Walkin… "Nic…
82 2016.03.02 02-Mar-… 2016 Unpr… BRAZIL "San… "Escale… "Swimmi… "Raf…
83 2016.02.02 02-Feb-… 2016 Unpr… BRAZIL "Bal… "Estale… "Swimmi… "Raf…
84 2016.01.24.b 24-Jan-… 2016 Unpr… USA "Tex… "Off Su… "Spearf… "Kei…
85 2016.01.23 23-Jan-… 2016 Unpr… USA "Haw… "Wailea… "Paddle… "Mat…
86 2016.01.11.R Reporte… 2016 Unpr… AUSTRA… "Que… "Happy … "Surfin… "Sha…
87 2015.12.26 26-Dec-… 2015 Boat… SOUTH … "Kwa… "Westbr… "Kayak … "Occ…
88 2015.12.21.a 21-Dec-… 2015 Unpr… BRAZIL "Per… "Fernan… "Scuba … "Már…
89 2015.12.13 13-Dec-… 2015 Boat… AUSTRA… "New… "Lake M… "Fishin… "6 m…
90 2015.12.11 11-Dec-… 2015 Unpr… BAHAMAS <NA> "Off An… "Lobste… "Ric…
91 2015.11.10 10-Nov-… 2015 Unpr… AUSTRA… "New… "East B… "Surfin… "Sam…
92 2015.10.25 25-Oct-… 2015 Unpr… SOUTH … "Wes… "Stil B… "Surfin… "Stu…
93 2015.10.17.a 17-Oct-… 2015 Unpr… USA "Haw… "Lanika… "Swimmi… "Ton…
94 2015.10.09.a 09-Oct-… 2015 Unpr… USA "Haw… "Leftov… "Surfin… "Col…
95 2015.09.24 24-Sep-… 2015 Boat… USA "Cal… "Horses… "Kayak … "Dar…
96 2015.09.20.c 20-Sep-… 2015 Unpr… USA "Haw… "Upolu … "Spearf… " Br…
97 2015.09.19 19-Sep-… 2015 Boat… USA "Cal… "Gaviot… "Kayak … "Mar…
98 2015.09.06 06-Sep-… 2015 Unpr… USA "Cal… "El Pes… "Stand-… "Cat…
99 2015.09.05 05-Sep-… 2015 Prov… USA "Cal… "Deer C… "Kayak … "Dyl…
100 2015.09.04 04-Sep-… 2015 Unpr… AUSTRA… "New… "Hallid… "Surf-s… "Dav…
101 2015.09.00 Sep-2015 2015 Unpr… FIJI <NA> <NA> "Spearf… "Vil…
102 2015.08.29.b 29-Aug-… 2015 Unpr… USA "Cal… "Morro … "Surfin… "Eli…
103 2015.08.29.a 29-Aug-… 2015 Unpr… USA "Cal… "Morro … "Surfin… "Dan…
104 2015.08.18.b 18-Aug-… 2015 Boat… USA "Cal… "Santa … "Kayak … "Con…
105 2015.08.10 10-Aug-… 2015 Prov… USA "Cal… "Cortes… "Spearf… "Ric…
106 2015.07.31 31-Jul-… 2015 Unpr… AUSTRA… "New… "Evans … "Surfin… "Cra…
107 2015.07.25 25-Jul-… 2015 Unpr… AUSTRA… "Tas… "Lachan… "Scallo… "Dam…
108 2015.07.22 22-Jul-… 2015 Unpr… REUNION <NA> "St. Le… "Surfin… "Rod…
109 2015.07.19 19-Jul-… 2015 Unpr… SOUTH … "Eas… "Jeffre… "Surfin… "Mic…
110 2015.07.03 03-Jul-… 2015 Unpr… AUSTRA… "New… "Lennox… "Surfin… "Mic…
111 2015.07.02 02-Jul-… 2015 Unpr… AUSTRA… "New… "East B… "Body b… "Mat…
112 2015.06.27.b 27-Jun-… 2015 Unpr… USA "Nor… "Rodant… "Swimmi… "Joh…
113 2015.06.27.a 27-Jun-… 2015 Unpr… SOUTH … "Wes… "Buffel… "Body B… "Cal…
114 2015.06.26.b 26-Jun-… 2015 Unpr… SOUTH … "Wes… "Lookou… "Surfin… "Dyl…
115 2015.06.25.R Reporte… 2015 Prov… AUSTRA… "Wes… "Rottne… "Swimmi… "Ste…
116 2015.06.24.b 24-Jun-… 2015 Unpr… USA "Nor… "Surf C… "Swimmi… "Bra…
117 2015.06.24.a 24-Jun-… 2015 Inva… AUSTRA… "Wes… "Denmar… "Surfin… "Lil…
118 2015.06.14.b 14-Jun-… 2015 Unpr… USA "Nor… "Oak Is… "Wading" "Hun…
119 2015.06.14.a 14-Jun-… 2015 Unpr… USA "Nor… "Oak Is… "Wading" "Kie…
120 2015.06.07 07-Jun-… 2015 Unpr… USA "Flo… "Lori W… "Playin… "Luc…
121 2015.06.01 01-Jun-… 2015 Unpr… REUNION "Le … "Folett… "Surfin… "Edd…
122 2015.05.09 09-May-… 2015 Unpr… NEW CA… <NA> "Kouare… "Snorke… "Yve…
123 2015.05.03 03-May-… 2015 Unpr… AUSTRA… "New… "Saltwa… "Surfin… "Bru…
124 2015.05.02 02-May-… 2015 Unpr… SOUTH … "Eas… "Port S… "Diving" "Mat…
125 2015.04.25 25-Apr-… 2015 Unpr… AUSTRA… "Sou… "Fisher… "Surfin… "Chr…
126 2015.04.24.c 24-Jun-… 2015 Unpr… AUSTRA… "New… "Belong… "Surf s… "Woo…
127 2015.04.12 12-Apr-… 2015 Unpr… REUNION "Sai… "Cap Ho… "Surfin… "Eli…
128 2015.04.03 03-Apr-… 2015 Unpr… USA "Flo… "3 mile… "Spearf… "Ric…
129 2015.03.26 26-Mar-… 2015 Boat… SOUTH … "Eas… "Yellow… "Kayak … "Kay…
130 2015.03.18 18-Mar-… 2015 Unpr… USA "Haw… "Hapuna… "Standi… "Ken…
131 2015.02.15 15-Feb-… 2015 Boat… ATLANT… <NA> <NA> "Transa… "Ava…
132 2015.02.14 14-Feb-… 2015 Unpr… REUNION "d’É… "Ravine… "Swimmi… "Tal…
133 2015.01.30 30-Jan-… 2015 Boat… AUSTRA… "Que… "Nerang… "Rowing" "Rac…
134 2015.01.19.b 19-Jan-… 2015 Boat… USA "Flo… "Off Pa… "Fishin… "22-…
135 2015.01.06 06-Jan-… 2015 Unpr… BAHAMAS "Aba… "Tahiti… "Snorke… "Lac…
136 2014.12.29.a 29-Dec-… 2014 Unpr… AUSTRA… "Wes… "Three … "Spearf… "Jay…
137 2014.12.28.b 28-Dec-… 2014 Unpr… USA "Cal… "Montañ… "Surfin… "Kev…
138 2014.12.15 15-Dec-… 2014 Unpr… AUSTRA… "Que… "Rudder… "Spearf… "Dan…
139 2014.11.19 19-Nov-… 2014 Boat… AUSTRA… "Wes… "Freo" "Fishin… "Boa…
140 2014.11.17 Reporte… 2014 Boat… USA "Cal… "Frankl… <NA> "Boa…
141 2014.10.31 31-Oct-… 2014 Unpr… USA "Haw… "North … "Surfin… "McK…
142 2014.10.22 22-Oct-… 2014 Unpr… USA "Haw… "Kihei,… "Stand-… "Kim…
143 2014.10.14 14-Oct-… 2014 Unpr… USA "Sou… "Hilton… "Standi… "Kyr…
144 2014.10.03.b 03-Oct-… 2014 Boat… USA "Cal… "Santa … "Kayaki… "Rya…
145 2014.10.03.a 03-Oct-… 2014 Boat… USA "Cal… "Santa … "Kayaki… "Rau…
146 2014.10.02.a 02-Oct-… 2014 Unpr… AUSTRA… "Wes… "Kelpid… "Surfin… "Sea…
147 2014.09.06 06-Sep-… 2014 Unpr… USA "Ala… "Katrin… "Fishin… "Jam…
148 2014.09.03 03-Sep-… 2014 Boat… USA "Mas… "Manome… "Kayaki… "Ida…
149 2014.08.25 Reporte… 2014 Prov… USA "Flo… "Apalac… "Fishin… "Joh…
150 2014.08.12 12-Aug-… 2014 Unpr… USA "Flo… "3 to 4… "Standi… "Kyl…
151 2014.08.09.R 09-Aug-… 2014 Unpr… BAHAMAS <NA> <NA> "Spearf… "And…
152 2014.08.08 08-Aug-… 2014 Unpr… USA "Lou… "Lake P… "Swimmi… "Tre…
153 2014.08.01 01-Aug-… 2014 Unpr… SOUTH … "Wes… "Muizen… "Surfin… "Mat…
154 2014.07.27 27-Jul-… 2014 Unpr… USA "Nor… "Sunset… "Swimmi… "mal…
155 2014.07.05.b 5-Jul-2… 2014 Prov… USA "Cal… "Manhat… "Swimmi… "Ste…
156 2014.06.01.c 01-Jun-… 2014 Unpr… USA "Flo… "Fort L… "Swimmi… "Jes…
157 2014.05.27.R 24-May-… 2014 Unpr… AUSTRA… "Que… "Nerang… "Fell i… "Bia…
158 2014.05.14 14-May-… 2014 Unpr… AUSTRA… "Sou… "Ellist… "Surfin… "And…
159 2014.04.12.R Reporte… 2014 Boat SOUTH … <NA> <NA> "Shark … "Inf…
160 2014.04.03 03-Apr-… 2014 Unpr… AUSTRA… "New… "Tathra" "Swimmi… "Chr…
161 2014.03.12 12-Mar-… 2014 Unpr… AUSTRA… "New… "Lighth… "Swimmi… "Mik…
162 2014.00.00 2014 2014 Boat… NEW ZE… <NA> "Stewar… "Filmin… "Din…
163 2013.12.25 25-Dec-… 2013 Unpr… NEW CA… "Nor… "Lindér… "Snorke… "Loï…
164 2013.12.16 16-Dec-… 2013 Unpr… SOUTH … "Wes… "Die Pl… "Surfin… "Tho…
165 2013.12.11 11-Dec-… 2013 Unpr… USA "Haw… "Ninole… "Boogie… "mal…
166 2013.12.05 05-Dec-… 2013 Unpr… AUSTRA… "New… "Shelly… "Surfin… "mal…
167 2013.11.30 30-Nov-… 2013 Unpr… AUSTRA… "New… "Riecks… "Body b… "Zac…
168 2013.11.23.a 23-Nov-… 2013 Unpr… AUSTRA… "Wes… "Gracet… "Surfin… "Chr…
169 2013.11.22 22-Nov-… 2013 Unpr… USA "Ore… "Glened… "Surfin… "And…
170 2013.11.12 12-Nov-… 2013 Unpr… AUSTRA… "Wes… "Trigg … "Surfin… "Sha…
171 2013.10.31 31-Oct-… 2013 Unpr… USA "Haw… "Kanaha… "Kitebo… "Chr…
172 2013.10.26.b 26-Oct-… 2013 Unpr… REUNION "d’É… "Ravine… "Body b… "Gic…
173 2013.10.26.a 26-Oct-… 2013 Unpr… AUSTRA… "Wes… "Little… "Diving… "Tod…
174 2013.10.24 24-Oct-… 2013 Unpr… AUSTRA… "New… "South … "Surfin… "Ant…
175 2013.10.20 20-Oct-… 2013 Unpr… USA "Haw… "Pila'a… "Surfin… "Jef…
176 2013.10.11 11-Oct-… 2013 Unpr… SOUTH … "Eas… "Albatr… "Swimmi… "Bur…
177 2013.10.08 08-Oct-… 2013 Unpr… AUSTRA… "Wes… "Off Po… "Diving… "Gre…
178 2013.10.05 06-Oct-… 2013 Unpr… USA "Cal… "Bunker… "Surfin… "Jay…
179 2013.10.05 10-Oct-… 2013 Unpr… USA "Flo… "Destin… "Wading" "Zac…
180 2013.09.14 14-Sep-… 2013 Unpr… USA "Flo… "Casino… "Swimmi… "Tre…
181 2013.08.17 17-Aug-… 2013 Unpr… USA "Cal… "Pillar… "Surfin… "Wen…
182 2013.08.14 14-Aug-… 2013 Unpr… USA "Haw… "Makena… "Snorke… "Jan…
183 2013.08.11 11-Aug-… 2013 Unpr… USA "Sou… "Folly … "Surfin… "Tys…
184 2013.08.05 05-Aug-… 2013 Unpr… USA "Flo… "Sanibe… "Fishin… "Chr…
185 2013.07.29.a 29-Jul-… 2013 Unpr… USA "Haw… "White … "Surfin… "Kio…
186 2013.06.25.c 25-Jun-… 2013 Boat… USA "Cal… "Pacifi… "Kayaki… "Mic…
187 2013.06.25.b 25-Jun-… 2013 Unpr… USA "Flo… "Jackso… "Swimmi… "Col…
188 2013.06.18 18-Jun-… 2013 Unpr… USA "Haw… "Kona C… "Swimmi… "Jam…
189 2013.05.08.a 08-May-… 2013 Unpr… REUNION "Sai… "Brisan… "Body b… "Sté…
190 2013.04.24 24-Apr-… 2013 Unpr… MEXICO "Qui… "Seagul… "Swimmi… "Isa…
191 2013.04.13.b 13-Apr-… 2013 Unpr… USA "Flo… "New Sm… "Surfin… "Jos…
192 2013.03.12 12-Mar-… 2013 Unpr… JAMAICA "St.… "Pillik… "Spearf… "Geo…
193 2013.02.27 27-Feb-… 2013 Unpr… NEW ZE… "Nor… "Muriwa… "Swimmi… "Ada…
194 2013.01.26 26-Jan-… 2013 Boat AUSTRA… "Vic… "Cape N… "Fishin… "Occ…
195 2013.01.16 16-Jan-… 2013 Unpr… USA "Haw… "Kiholo… "Surfin… "Pau…
196 2012.12.28 28-Dec-… 2012 Unpr… AUSTRA… "New… "Kylie'… "Paddle… "Luk…
197 2012.12.25 25-Dec-… 2012 Unpr… SOUTH … "Eas… "Port S… "Swimmi… "Liy…
198 2012.12.19 19-Dec-… 2012 Unpr… AUSTRA… "Wes… "Trigg … "Surfin… "Ric…
199 2012.12.02 02-Dec-… 2012 Unpr… AUSTRA… "New… "Green … "Spearf… "mal…
200 2012.11.30 30-Nov-… 2012 Unpr… USA "Haw… "Kihei,… "Snorke… "Tho…
201 2012.11.04.b 04-Nov-… 2012 Unpr… USA "Haw… "Makena… "Diving" "Mar…
202 2012.11.04.a 04-Nov-… 2012 Unpr… USA "Haw… "Davids… "Surfin… "mal…
203 2012.10.30 30-Oct-… 2012 Unpr… USA "Cal… "Humbol… "Surfin… "Sco…
204 2012.10.27 27-Oct-… 2012 Unpr… USA "Haw… "Makena… "Swimmi… "Mar…
205 2012.10.23 23-Oct-… 2012 Unpr… USA "Cal… "Surf B… "Surfin… "Fra…
206 2012.09.10 10-Sep-… 2012 Unpr… TONGA "Vav… "Eueiki… "Swimmi… "Kyl…
207 2012.09.02.b 02-Sep-… 2012 Prov… USA "Haw… "Spreck… "Spearf… "M. …
208 2012.08.05 06-Aug-… 2012 Unpr… REUNION "Sai… <NA> "Surfin… "Fab…
209 2012.07.31.a 31-Jul-… 2012 Unpr… AUSTRA… "Sou… "Streak… "Surfin… "Joh…
210 2012.07.30.a 30-Jul-… 2012 Unpr… USA "Mas… "Ballst… "Body s… "Chr…
211 2012.07.14 14-Jul-… 2012 Unpr… AUSTRA… "Wes… "Off We… "Surfin… "Ben…
212 2012.06.26.c 26-Jun-… 2012 Unpr… USA "Flo… "Juno B… "Swimmi… "Nic…
213 2012.06.03 03-Jun-… 2012 Unpr… AUSTRA… "New… "Redhea… "Surf s… "Mar…
214 2012.05.29 29-May-… 2012 Unpr… MEXICO "Gue… " Boca … "Free d… "Ben…
215 2012.05.20 20-May-… 2012 Boat… USA "Haw… "Iroqui… "Kayak … "Jer…
216 2012.05.12 12-May-… 2012 Boat… USA "Cal… "Leffin… "Kayaki… "Joe…
217 2012.05.06 06-May-… 2012 Unpr… USA "Cal… "Off Ca… "Paddle… "Ros…
218 2012.04.19.a 19-Apr-… 2012 Unpr… SOUTH … "Wes… "Caves … "Body b… "Dav…
219 2012.04.11 11-Apr-… 2012 Boat… AUSTRA… "Sou… "Dolphi… "Kayaki… "Mic…
220 2012.04.03 03-Apr-… 2012 Unpr… USA "Haw… "Leftov… "Surfin… "Jos…
221 2012.03.31 31-Mar-… 2012 Unpr… AUSTRA… "Wes… "Strath… "Scuba … "Pet…
222 2012.03.22 22-Mar-… 2012 Boat… AUSTRA… "Wes… "Kalbar… "Crayfi… "cra…
223 2012.03.20 20-Mar-… 2012 Unpr… AUSTRA… "Que… "Nobby'… "Surfin… "Bil…
224 2012.03.15 15-Mar-… 2012 Unpr… USA "Flo… "Jensen… "Surfin… "Fra…
225 2012.02.20 20-Feb-… 2012 Boat SOUTH … "Wes… "Strand… "Fishin… "8m …
226 2012.01.19 19-Jan-… 2012 Unpr… AUSTRA… "Wes… "Coral … "Snorke… "Dav…
227 2012.01.22.R Reporte… 2012 Unpr… BAHAMAS <NA> "Cat Is… "Diving… "Rus…
228 2012.01.18.a 18-Jan-… 2012 Unpr… AUSTRA… "New… "Redhea… "Surfin… "Gle…
229 2012.01.15 15-Jan-… 2012 Unpr… SOUTH … "Eas… "Second… "Swimmi… "Lun…
230 2012.01.13 13-Jan-… 2012 Unpr… USA "Ore… "Lincol… "Surfin… "Ste…
231 2012.01.02 02-Jan-… 2012 Unpr… AUSTRA… "Que… "Duranb… "Spearf… "Hug…
232 2011.12.11 11-Dec-… 2011 Unpr… AUSTRA… "New… "Angour… "Surfin… "Ste…
233 2011.12.07.a 07-Dec-… 2011 Unpr… AUSTRA… "New… "Maroub… "Surfin… "Ron…
234 2011.11.28 28-Nov-… 2011 Unpr… AUSTRA… "Que… "Peregi… "Swimmi… "Eam…
235 2011.11.22 22-Nov-… 2011 Boat… USA "Cal… "Pigeon… "Kayaki… "Har…
236 2011.10.29. 29-Oct-… 2011 Unpr… USA "Cal… "Marina… "Surfin… "Eri…
237 2011.10.22 22-Oct-… 2011 Unpr… AUSTRA… "Wes… "Rottne… "Diving" "Geo…
238 2011.10.20 20-Oct-… 2011 Unpr… USA "Ore… "Newpor… "Surfin… "Bob…
239 2011.09.28.a 28-Sep-… 2011 Unpr… SOUTH … "Wes… "Clovel… "Swimmi… "Mic…
240 2011.09.24.b 24-Sep-… 2011 Unpr… USA "Flo… "Santa … "Spearf… "C.J…
241 2011.09.11.a 11-Sep-… 2011 Unpr… PAPUA … "Cen… "Hula, … "Kite S… "Tho…
242 2011.09.04.a 04-Sep-… 2011 Unpr… AUSTRA… "Wes… " Bunke… "Body b… "Kyl…
243 2011.08.23 23-Aug-… 2011 Unpr… SOUTH … "Wes… "Lookou… "Surfin… "Tim…
244 2011.08.17.c. 17-Aug-… 2011 Unpr… USA "Nor… "Kure B… "Wading" "Tra…
245 2011.08.16.a 16-Aug-… 2011 Unpr… SEYCHE… "Pra… "Anse L… "Swimmi… "Ian…
246 2011.07.22 22-Jul-… 2011 Unpr… SOUTH … "Eas… "Cintza… "Surfin… "Den…
247 2011.06.28 28-Jun-… 2011 Unpr… SOUTH … "Kwa… "Aliwal… "Scuba … "Pao…
248 2011.06.26 26-Jun-… 2011 Unpr… USA "Nor… "North … "Playin… "Cas…
249 2011.06.24 24-Jun-… 2011 Unpr… USA "Cal… "San On… "Surfin… "Dou…
250 2011.05.29 29-May-… 2011 Unpr… SOUTH … "Wes… "Robber… "Surfin… "Cli…
251 2011.05.25 25-May-… 2011 Unpr… USA "Haw… "Lyman … "Surfin… "The…
252 2011.05.22 22-May-… 2011 Unpr… USA "Haw… "Lyman … "Paddle… "Ala…
253 2011.05.21.a 21-May-… 2011 Unpr… NEW CA… "Nor… "Kendec" "Kite B… "Nat…
254 2011.04.26 26-Apr-… 2011 Unpr… USA "Flo… "Rivier… "Spearf… "Ant…
255 2011.04.12 13-Apr-… 2011 Unpr… INDONE… "Bal… "Balian" "Surfin… "Joe…
256 2011.03.24 24-Mar-… 2011 Unpr… MEXICO "Qui… "Gaviot… "Swimmi… "Liu…
257 2011.03.23 23-Mar-… 2011 Unpr… AUSTRA… "New… "Crowdy… "Surfin… "Dav…
258 2011.02.28.R Reporte… 2011 Prov… AUSTRA… "Que… "Betwee… "Fishin… "Sha…
259 2011.02.17 17-Feb-… 2011 Unpr… AUSTRA… "Sou… "Off Pe… "Diving… "Pet…
260 2011.01.03 03-Jan-… 2011 Boat AUSTRA… "Wes… "Bussel… "Fishin… "A '…
261 2010.11.12.R Reporte… 2010 Boat AUSTRA… "Wes… "Betwee… "Fishin… "4-m…
262 2010.10.30 30-Oct-… 2010 Unpr… AUSTRA… "Wes… "Off Ga… "Snorke… "Ely…
263 2010.10.22 22-Oct-… 2010 Unpr… USA "Cal… "Surf B… "Body b… "Luc…
264 2010.10.09 09-Oct-… 2010 Unpr… AUSTRA… "New… "Mullaw… "Surfin… "Ken…
265 2010.09.27 27-Sep-… 2010 Unpr… USA "Ore… "Winche… "Surfin… "Dav…
266 2010.09.21 21-Sep-… 2010 Unpr… SOUTH … "Wes… "Betwee… "Swimmi… "Kha…
267 2010.08.17 17-Aug-… 2010 Unpr… AUSTRA… "Wes… "Cowara… "Surfin… "Nic…
268 2010.08.14 14-Aug-… 2010 Boat… USA "Cal… "Pigeon… "Kayak … "Ada…
269 2010.08.02.b 02-Aug-… 2010 Boat… USA "Cal… "Near o… "Kayaki… "Dua…
270 2010.07.17.b 17-Jul-… 2010 Unpr… USA "Nor… "Wright… "Swimmi… "Ken…
271 2010.06.27 27-Jun-… 2010 Unpr… USA "Tex… "Eight … "Surfin… "Cha…
272 2010.02.11 11-Feb-… 2010 Unpr… AUSTRA… "New… "Mona V… "Surfin… "Pau…
273 2010.02.06.b 06-Feb-… 2010 Unpr… AUSTRA… "New… "Turner… "Body b… "Dea…
274 2010.01.30 31-Jan-… 2010 Unpr… BRAZIL "Rio… "Atlant… "Surfin… "And…
275 2010.01.12 12-Jan-… 2010 Unpr… SOUTH … "Wes… "Fish H… "Standi… "Llo…
276 2009.12.20.a 20-Dec-… 2009 Unpr… AUSTRA… "Que… "Lamont… "Spearf… "Joh…
277 2009.12.16 16-Dec-… 2009 Unpr… NEW ZE… "Sou… "Clark … "Swimmi… "Mau…
278 2009.12.12 12-Dec-… 2009 Boat… AUSTRA… "New… "Hawks … "Rowing" "Sur…
279 2009.12.06 05-Dec-… 2009 Prov… USA "New… "Advent… "Diving" "Rob…
280 2009.10.30 30-Oct-… 2009 Boat… AUSTRA… "Vic… "Portla… "Kayaki… "Rhy…
281 2009.10.14.R Reporte… 2009 Unpr… AUSTRA… "Wes… <NA> "Diving" "Mat…
282 2009.09.26 26-Sep-… 2009 Unpr… USA "Flo… "Key Co… "Swimmi… "Dan…
283 2009.08.29 29-Aug-… 2009 Unpr… SOUTH … "Wes… "Glenta… "Surfin… "Ger…
284 2009.08.25 25-Aug-… 2009 Unpr… USA "Cal… "Terram… "Swimmi… "Bet…
285 2009.08.11 11-Aug-… 2009 Unpr… SOUTH … "Kwa… "Alkant… "Body b… "Jea…
286 2009.08.06 06-Aug-… 2009 Unpr… USA "Haw… "Kawa'a… "Surfin… "Dyl…
287 2009.08.01 01-Aug-… 2009 Unpr… USA "Lou… "Curlew… "Wade F… "Chr…
288 2009.07.31 31-July… 2009 Unpr… BAHAMAS "Aba… "Spanis… "Spearf… "Der…
289 2009.06.14.R Reporte… 2009 Prov… VIETNAM <NA> <NA> "Fishin… "Tra…
290 2009.04.06.a 06-Apr-… 2009 Unpr… USA "Cal… "San Di… "Spearf… "Ray…
291 2009.03.16.R Reporte… 2009 Prov… AUSTRA… "Wes… "The Na… "Wading" "mal…
292 2009.02.12 12-Feb-… 2009 Unpr… AUSTRA… "New… "Bondi … "Surfin… "Gle…
293 2009.02.11 11-Feb-… 2009 Unpr… AUSTRA… "New… "Garden… "Diving… "Pau…
294 2009.02.07.b 07-Feb-… 2009 Unpr… AUSTRA… "New… "Cellit… "Surfin… "Dur…
295 2009.01.25 25-Jan-… 2009 Unpr… CUBA "Gua… "Guanta… "Spearf… "Joh…
296 2009.01.24.a 24-Jan-… 2009 Unpr… SOUTH … "Eas… "Second… "Swimmi… "Sik…
297 2009.01.18 18-Jan-… 2009 Boat AUSTRA… "Vic… "Off To… "Fishin… "Occ…
298 2009.01.13.R Reporte… 2009 Unpr… SOUTH … "Wes… "Shark … <NA> "4 p…
299 2009.01.11.b 11-Jan-… 2009 Unpr… AUSTRA… "Tas… "Binalo… "Surfin… "Han…
300 2009.01.11.a 11-Jan-… 2009 Unpr… AUSTRA… "New… "Fingal… "Surfin… "Jon…
301 2009.01.00 Jan-2009 2009 Unpr… CUBA "Gua… "Guanta… "Spearf… "Joh…
302 2008.12.27.b 27-Dec-… 2008 Boat… AUSTRA… "New… "Long R… "Kayaki… "Ste…
303 2008.12.27.a 27-Dec-… 2008 Unpr… AUSTRA… "Wes… "Port K… "Snorke… "Bri…
304 2008.12.20 20-Dec-… 2008 Boat… USA "Cal… "Dillon… "Kayaki… "Ton…
305 2008.12.06 06-Dec-… 2008 Boat… AUSTRA… "New… "Mowarr… "Fishin… "6 m…
306 2008.10.06 06-Oct-… 2008 Unpr… CROATIA " Sp… "Smokvi… "Spearf… "Dam…
307 2008.09.09 09-Sep-… 2008 Unpr… USA "Haw… "Ka'a'a… "Surfin… "Tod…
308 2008.09.08 08-Sep-… 2008 Unpr… USA "Cal… "Surf B… "Surfin… "Kyl…
309 2008.08.16 16-Aug-… 2008 Unpr… USA "US … "Buck I… "Treadi… "Eli…
310 2008.08.11 11-Aug-… 2008 Unpr… USA "Haw… "Ala Mo… "Diving" "mal…
311 2008.07.30.R 30-Jul-… 2008 Unpr… AUSTRA… "Vic… "Levys … "Surfin… "Aar…
312 2008.07.30 Reporte… 2008 Unpr… SOUTH … <NA> <NA> <NA> "Mic…
313 2008.06.28.b 28-Jun-… 2008 Unpr… BAHAMAS "Aba… <NA> "Spearf… "Max…
314 2008.06.28.a 28-Jun-… 2008 Unpr… SOUTH … "Wes… "Mossel… "Surf s… "Kob…
315 2008.06.26.R Reporte… 2008 Unpr… SOUTH … "Wes… "Struis… "Spearf… "Kev…
316 2008.06.21 21-Jun-… 2008 Boat… USA "Cal… "West C… "Kayaki… "Bet…
317 2008.06.01.a 01-Jun-… 2008 Unpr… BRAZIL "Per… "Piedad… "Swimmi… "Wel…
318 2008.05.24.b 24-May-… 2008 Sea … BAHAMAS "Gra… "Off We… "Sea Di… "unk…
319 2008.05.10 10-May-… 2008 Unpr… AUSTRA… "Wes… "Albany" "Swimmi… "Jas…
320 2008.05.07.b 07-May-… 2008 Unpr… NEW CA… "Nor… "Hiengh… "Fishin… "mal…
321 2008.04.28.b 28-Apr-… 2008 Unpr… MEXICO "Gue… "Tronco… "Surfin… "Adr…
322 2008.04.26.b 26-Apr-… 2008 Unpr… NEW CA… "Nor… "Poindi… "Swimmi… "Oli…
323 2008.04.25 25-Apr-… 2008 Unpr… USA "Cal… "Solana… "Swimmi… "Dav…
324 2008.04.20.a 20-Apr-… 2008 Unpr… AUSTRA… "New… "Cresce… <NA> "Jam…
325 2008.04.19.R Reporte… 2008 Inva… SOUTH … "Kwa… "Aliwal… "Free-d… "Jea…
326 2008.04.08 08-Apr-… 2008 Unpr… AUSTRA… "New… "Lighth… "Body b… "Pet…
327 2008.03.07 07-Mar-… 2008 Unpr… USA "Cal… " Hunti… "Surfin… "Tho…
328 2008.02.24 24-Feb-… 2008 Unpr… BAHAMAS "Nor… "Dive s… "Diving" "Mar…
329 2008.00.00.a Summer-… 2008 Unpr… MEXICO "Baj… "Playas… "Surfin… "Cha…
# ℹ 15 more variables: `Sex ` <chr>, Age <chr>, Injury <chr>,
# `Fatal (Y/N)` <chr>, Time <chr>, Species <chr>,
# `Investigator or Source` <chr>, pdf <chr>, `href formula` <chr>,
# href <chr>, `Case Number...20` <chr>, `Case Number...21` <chr>,
# `original order` <dbl>, ...23 <lgl>, ...24 <lgl>
Arranging the data
To descend from the species with the highest attack to the lowest
|> group_by (` Species ` ) |> summarise (attack_countt = n ()) |> arrange (desc (attack_countt))
# A tibble: 159 × 2
Species attack_countt
<chr> <int>
1 White shark 54
2 Tiger shark 22
3 Bull shark 20
4 Bull shark, 6' 7
5 Wobbegong shark 7
6 Tiger shark, 10' 6
7 White shark, 3.5 m 6
8 Bull shark, 2m 4
9 Sandtiger shark 4
10 Tiger shark, 12' 4
# ℹ 149 more rows
More Cleaning
I got rid of any NA values and cleaned the data
<- sharkattacks_filteredd2 |> mutate (species_clean = case_when (str_detect (Species, regex (" \\ bwhite shark \\ b" , ignore_case = TRUE )) ~ "White shark" ,str_detect (Species, regex (" \\ bbull shark \\ b" , ignore_case = TRUE )) ~ "Bull shark" ,str_detect (Species, regex (" \\ btiger shark \\ b" , ignore_case = TRUE )) ~ "Tiger shark" ,str_detect (Species, regex (" \\ bwobbegong shark \\ b" , ignore_case = TRUE )) ~ "Wobbegong shark" ,str_detect (Species, regex (" \\ bhammerhead shark \\ b" , ignore_case = TRUE )) ~ "Hammerhead shark" ,TRUE ~ NA_character_ |> select (where (~ ! all (is.na (.))))
|> filter (! is.na (species_clean)) |> count (species_clean, sort = TRUE )
# A tibble: 5 × 2
species_clean n
<chr> <int>
1 White shark 151
2 Bull shark 81
3 Tiger shark 66
4 Wobbegong shark 14
5 Hammerhead shark 5
Bar chart
ggplot (data = sharkattacks_cleaned |> filter (! is.na (species_clean)), aes (x = fct_infreq (species_clean))+ geom_bar (fill = "red3" , colour = "black" ) + labs (y = "Number of Attacks" , x = "Shark Species" ,title = "Most Aggressive Shark" )
Neatening it up
ggplot (data = sharkattacks_cleaned |> filter (! is.na (species_clean)), aes (x = fct_infreq (species_clean))+ geom_bar (fill = "red3" , colour = "black" ) + labs (y = "Number of Attacks" , x = "Shark Species" ,title = "Most Aggressive Shark" ) + theme_classic () + theme (axis.text.x = element_text (angle = 20 , hjust = 1 ))
Finished result - Which Shark is the most aggressive?
I felt red went with the shark attack theme but also was eye catching. I went for theme classic to eliminate grid lines and used black to outline the bars. I chose for the y axis to go up in 10 rather than 50 and tilted the x axis values so they don’t overlap.
ggplot (data = sharkattacks_cleaned |> filter (! is.na (species_clean)), aes (x = fct_infreq (species_clean))+ geom_bar (fill = "red3" , colour = "black" ) + labs (y = "Number of Attacks" , x = "Shark Species" ,title = "Most Aggressive Shark" ) + theme_classic () + theme (axis.text.x = element_text (angle = 15 , hjust = 1 )) + scale_y_continuous (breaks = seq (0 , max (table (sharkattacks_cleaned$ ` species_clean ` )), by = 10 ))
Interactive line chart
With the data i just cleaned I found the code for an interactive line chart in Robert Kabacoff’s 2024 Modern Data Visualization book and decided to try this out to present which years the sharks were most active in
options (repos = c (CRAN = "https://cran.rstudio.com" ))install.packages ("highcharter" )
The downloaded binary packages are in
/var/folders/3w/8nsv74zj2lv3851n2h_xl4bw0000gn/T//Rtmpbkormk/downloaded_packages
Registered S3 method overwritten by 'quantmod':
method from
as.zoo.data.frame zoo
Highcharts (www.highcharts.com) is a Highsoft software product which is
not free for commercial and Governmental use
library (dplyr)<- sharkattacks_cleaned |> select (Year, Species)library (tidyr)<- sharkattacks_cleaned |> group_by (Year, Species) |> summarise (count = n (), .groups = "drop" ) |> pivot_wider (names_from = Species, values_from = count, values_fill = 0 )<- highchart () %>% hc_xAxis (categories = plotdata$ Year) %>% hc_add_series (name = "White shark" , data = plotdata$ ` White shark ` ) %>% hc_add_series (name = "Tiger shark" , data = plotdata$ ` Tiger shark ` ) %>% hc_add_series (name = "Wobbegong shark" , data = plotdata$ ` Wobbegong shark ` ) %>% hc_add_series (name = "Bull shark" , data = plotdata$ ` Bull shark ` ) %>% hc_add_series (name = "Hammerhead shark" , data = plotdata$ ` Hammerhead shark ` )
Which Country has the most attacks?
During this section I think I lost 6 Hours of my life trying to figure out why my data would not plot on a world map. After many failed attempts of trying to organise and join the countries to the map I decided I would create a horizontal bar chart to present which countries had the highest amount of attacks.
# A tibble: 329 × 24
`Case Number...1` Date Year Type Country Area Location Activity Name
<chr> <chr> <dbl> <chr> <chr> <chr> <chr> <chr> <chr>
1 2018.06.25 25-Jun-2… 2018 Boat… USA Cali… Oceansi… Paddling "Jul…
2 2018.06.04 04-Jun-2… 2018 Prov… MEXICO Coli… La Ticla Free di… "Gus…
3 2018.06.03.a 03-Jun-2… 2018 Unpr… BRAZIL Pern… Piedade… Swimming "Jos…
4 2018.05.26.b 26-May-2… 2018 Unpr… USA Flor… Cocoa B… Walking "Cod…
5 2018.04.28.b 28-Apr-2… 2018 Unpr… COSTA … Coco… Manueli… Scuba d… "mal…
6 2018.04.24 24-Apr-2… 2018 Unpr… AUSTRA… West… South P… Surfing "Nat…
7 2018.04.23 23-Apr-2… 2018 Unpr… MALDIV… Alif… Madooga… Fishing "Ahm…
8 2018.04.22 22-Apr-2… 2018 Unpr… SOUTH … West… Robberg… Paddle-… "mal…
9 2018.04.15.d 15-Apr-2… 2018 Unpr… THAILA… Hua … Sai Noi… Swimming "Wer…
10 2018.04.14 14-Apr-2… 2018 Unpr… BAHAMAS New … Nirvana… Surfing "Bru…
# ℹ 319 more rows
# ℹ 15 more variables: `Sex ` <chr>, Age <chr>, Injury <chr>,
# `Fatal (Y/N)` <chr>, Time <chr>, Species <chr>,
# `Investigator or Source` <chr>, pdf <chr>, `href formula` <chr>,
# href <chr>, `Case Number...20` <chr>, `Case Number...21` <chr>,
# `original order` <dbl>, ...23 <lgl>, ...24 <lgl>
Cleaning country names
<- sharkattacks_filteredd2 |> mutate (Country = str_to_title (Country))<- sharkattacks_filteredd2 |> mutate (Country = if_else (Country == "Usa" , "USA" , Country))unique (sharkattacks_filteredd2$ Country)
[1] "USA" "Mexico" "Brazil" "Costa Rica"
[5] "Australia" "Maldives" "South Africa" "Thailand"
[9] "Bahamas" "New Caledonia" "Cuba" "Reunion"
[13] "Indonesia" "Fiji" "Atlantic Ocean" "New Zealand"
[17] "Jamaica" "Tonga" "Papua New Guinea" "Seychelles"
[21] "Vietnam" "Croatia"
Arranging
To make my graph clearer I ordered the countries from highest to lowest
library (dplyr)<- sharkattacks_filteredd2 |> count (Country, name = "Attack_No" ) |> arrange (desc (Attack_No)) |> print (n = Inf )
# A tibble: 22 × 2
Country Attack_No
<chr> <int>
1 USA 129
2 Australia 99
3 South Africa 37
4 Bahamas 12
5 Reunion 9
6 Mexico 8
7 New Caledonia 7
8 Brazil 6
9 Costa Rica 3
10 Cuba 3
11 Indonesia 3
12 New Zealand 3
13 Atlantic Ocean 1
14 Croatia 1
15 Fiji 1
16 Jamaica 1
17 Maldives 1
18 Papua New Guinea 1
19 Seychelles 1
20 Thailand 1
21 Tonga 1
22 Vietnam 1
Loading my libraries
library (stringr)library (tidyverse)library (here)library (sf)
Linking to GEOS 3.13.0, GDAL 3.8.5, PROJ 9.5.1; sf_use_s2() is TRUE
[1] "/Users/anyabogdanovic/Documents/DataSkills_2"
Plotting
ggplot (data = attacks_by_country,aes (x = reorder (Country, Attack_No), y = Attack_No)+ geom_col () + coord_flip ()
Lets make it clearer
I went for a turquoise colour to stick with the ocean theme and as it’s eye catching, I went for minimal theme as I felt getting rid of all grid lines wasn’t as clear. I changed the x axis to go up in 20 opposed to 50.
ggplot (data = attacks_by_country,aes (x = reorder (Country, Attack_No), y = Attack_No)+ geom_col (fill = "mediumturquoise" ) + coord_flip () + labs (x = "" , y = "Shark Attacks" ,title = "Global Shark Attacks (2008 - 2018)" ) + scale_y_continuous (breaks = seq (0 , max (attacks_by_country$ Attack_No), by = 20 )) + theme_minimal ()
Which state in Australia has the most attacks?
Even though the USA had the highest amount of attacks I chose Australia to find out which state had the most attacks.
I was still determined that I would make a map for one of my questions so I found a YouTube tutorial (https://www.youtube.com/watch?v=xXXqTvv5g3M) explaining how to find an Australian Territory map on R. Thankfully the states joined to the map with no issues.
Filtering
I made a new data set with just the Australian attacks from 2008 - 2018. I also descended the values.
<- sharkattacks_filteredd2 |> filter (Country == "Australia" ) |> count (Area, name = "Attack_No" ) |> arrange (desc (Attack_No))print (australia_attacks)
# A tibble: 7 × 2
Area Attack_No
<chr> <int>
1 New South Wales 41
2 Western Australia 34
3 Queensland 10
4 South Australia 6
5 Victoria 5
6 Tasmania 2
7 Westerm Australia 1
Mutuate
There seemed to be two Western Australia values so I merged them together and checked it worked.
<- australia_attacks |> mutate (Area = recode (Area, "Westerm Australia" = "Western Australia" ))unique (australia_attacks$ Area)
[1] "New South Wales" "Western Australia" "Queensland"
[4] "South Australia" "Victoria" "Tasmania"
# A tibble: 7 × 2
Area Attack_No
<chr> <int>
1 New South Wales 41
2 Western Australia 34
3 Queensland 10
4 South Australia 6
5 Victoria 5
6 Tasmania 2
7 Western Australia 1
<- australia_attacks |> group_by (Area) |> summarise (Total_Attacks = sum (Attack_No, na.rm = TRUE ), .groups = "drop" )unique (australia_attacks$ Area)
[1] "New South Wales" "Queensland" "South Australia"
[4] "Tasmania" "Victoria" "Western Australia"
# A tibble: 6 × 2
Area Total_Attacks
<chr> <int>
1 New South Wales 41
2 Queensland 10
3 South Australia 6
4 Tasmania 2
5 Victoria 5
6 Western Australia 35
New packages
install.packages ("ozmaps" )
The downloaded binary packages are in
/var/folders/3w/8nsv74zj2lv3851n2h_xl4bw0000gn/T//Rtmpbkormk/downloaded_packages
library (ozmaps)library (sf)
<- ozmap_data ("states" )
ggplot (data = sf_oz) + geom_sf ()
Simple feature collection with 9 features and 1 field
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 105.5507 ymin: -43.63203 xmax: 167.9969 ymax: -9.229287
Geodetic CRS: GDA94
# A tibble: 9 × 2
NAME geometry
* <chr> <MULTIPOLYGON [°]>
1 New South Wales (((150.7016 -35.12286, 150.6611 -35.11782, 150.6…
2 Victoria (((146.6196 -38.70196, 146.6721 -38.70259, 146.6…
3 Queensland (((148.8473 -20.3457, 148.8722 -20.37575, 148.85…
4 South Australia (((137.3481 -34.48242, 137.3749 -34.46885, 137.3…
5 Western Australia (((126.3868 -14.01168, 126.3625 -13.98264, 126.3…
6 Tasmania (((147.8397 -40.29844, 147.8902 -40.30258, 147.8…
7 Northern Territory (((136.3669 -13.84237, 136.3339 -13.83922, 136.3…
8 Australian Capital Territory (((149.2317 -35.222, 149.2346 -35.24047, 149.271…
9 Other Territories (((167.9333 -29.05421, 167.9188 -29.0344, 167.93…
Starting to plot
I joined my data set to the map by the area and name and plotted my map. I wanted to use a red gradient again for the attack theme. Theme classic cleaned up the grid lines and made it more visually pleasing
<- sf_oz |> left_join (australia_attacks, by = c ("NAME" = "Area" ))ggplot (data = sf_oz) + geom_sf (aes (fill = Total_Attacks)) + scale_fill_gradient (low = "lightcoral" , high = "darkred" ) + labs (title = "Shark Attacks by State in Australia (2008-2018)" ) + theme_classic ()
Finishing touches
New South Wales had slightly more attacks than Western Aus but I felt the red didn’t display this as well as a blue gradient so I decided to change it to that. The one colour gradient allows for this map to be printed in grey scale and still be readable. I also got rid of the coordinates along the axis
ggplot (data = sf_oz) + geom_sf (aes (fill = Total_Attacks)) + scale_fill_gradient (low = "powderblue" , high = "midnightblue" ) + labs (title = "Shark Attacks by State in Australia (2008-2018)" ) + theme_classic () + theme (axis.text = element_blank (),axis.title = element_blank (),axis.ticks = element_blank ()
