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Global Shark Attacks Data Analysis

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Global Shark Attacks Data Analysis

An analysis of shark attacks reported worldwide from 1854-2015

Introduction:

A shark attack is an attack on a human by a shark. Every year around 80 unprovoked attacks are reported worldwide. Despite their relative rarity, the effect the media has on the population's view of shark attacks has generally been negative. Starting with the effects generated from news broadcasts, a shark attack is quickly broadcasted across the country, particularly if fatal, even though more people die from random occurrences such as lightning strikes than from a shark attack

The International Shark Attack File, internationally recognized as the definitive source of scientifically accurate information on shark attacks, is a compilation of investigations of all known shark attacks.  Established in 1958, it is administered by the Florida Museum of Natural History at the University of Florida under the auspices of the American Elasmobranch Society, the world's foremost international organization of scientists studying sharks, skates, and rays. The database contains information on more than 6,000 individual investigations from the mid-1500's to present.  Many of the data in the ISAF originate from the voluntary submissions of numerous cooperating scientists who serve worldwide as regional observers.  Data submitted to the ISAF is screened, coded, and computerized.

The International shark attack file reported 5750 incidents of alleged shark-human interaction occurring worldwide and dating back from 1854 to 2016, 2,785 were confirmed unprovoked shark attacks, of which 439 were fatal. The aim of this project is to investigate the frequency of these attacks and to produce a comprehensive exploratory data analysis of the global shark attack datasets with an emphasis on the incidents happening at the united states of America and in later years.

The analysis conducted in this project stresses out where shark attacks are most common, which country has the most shark attacks and what activities are associated with each of these incidents. In addition to the fatality rate of shark attacks and when exactly have they most occurred.  Our analysis also briefly highlights the type of injuries resulting of each attack, number of survivors over the years and the specific shark species involved in each incident.

The probability of a recorded shark attack can be modeled as the joint probability of multiple processes: the probability that a person and a shark encounter one another p(E), that such an encounter results in a bite p(B), and that the attack is communicated p(C). p(E) depends on the abundance of humans (H) and sharks (S) in the water, and on the spatial overlap between people and sharks (O). If we assume that for any given encounter p(B) and p(C) remain constant, then the probability of a recorded shark attack depends only on H, S, and O. We are analyzing the data using this probability framework.

The conclusions drawn from this study are the responses to the number of questions that can be asked about the global shark attacks data. Our goal is that the comprehensive analysis helps us introduce a perception of the risk of a shark attack.

Understanding the data:

The Global shark attacks data is in csv format and consists initially of 5750 observations and 16 attributes. Most of these attributes are categorical variables. Table 1 is describing each one of the attribute and its domain:

                        Table1: Attributes domain and specifications of the Global Shark Attacks Dataset  

                                                             Attribute n: 1

Name:

Date

Scale:

Categorical variable

Type:

Character date indicating the date of the attack

                                                            Attribute n :2

Name

Year

Scale

Numerical

Type

Number indicating the year the incident was reported (range: 1543-2016)

                                                           Attribute n:3

Name:

Type (Type of the attack)

Scale

Categorical variable

Type

Character describing the type of the attack

                                                           Attribute n: 4

Name:

Country

Scale

Categorical

Type

Character describing the country where the attack took place

                                                            Attribute n:5

Name:

Area

Scale:

Categorical

Type:

Character describing the area where the attack took place

                                                          Attribute n:6

Name:

Location

Scale:

Categorical

Type:

Character describing the location where the attack took place

                                                           Attribute n:7

Name:

Activity

Scale:

Categorical

Type:

Character: the activity associated with the attack

                                                           Attribute n:8

Name:

Name

Scale:

Categorical

Type:

Character string indicating the name of the victim

                                                            Attribute n:9

Name

Sex

Scale:

Categorical

Type:

Character indicating the sex of the victim

                                                           Attribute n:10

Name:

Age

Scale:

Numerical Variable

Type:

The age of the victim

                                                         Attribute n:11

Name:

Injury

Scale:

Categorical variable

Type:

Character indicating the type of injury the victim of the attack suffered

                                                      Attribute n:12

Name:

Fatal..Y.N  (Fatal yes or no)

Scale:

Categorical Variable

Type:

Character (Y-N) whether the attack was fatal or not

                                                      Attribute n:13

Name:

Time

Scale:

Categorical Variable

Type:

The time the attack happened

                                                       Attribute n:14

Name:

Species

Scale:

Categorical Variable

Type:

Character indicating the shark specie responsible for each incident

                                                      Attribute n:15

Name:

Investigator or source

Scale:

Categorical variable

Type:

Investigator/source

...

...

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