BIGDATA SIMULATION ONE PIECE WORLD CENSUS

Overview

BIGDATA SIMULATION ONE PIECE WORLD CENSUS

=================

Solution Architecture

delta

Description


ONE PIECE is a Japanese manga of great international success. The story turns inhabited in a fictional world, tells the adventures of a young man whose body gained rubber properties after accidentally eating a devil fruit (AKUMA NO MI). In this universe there are three types of AKUMA NO MI; Logia, Zoan and Paramecia. Each has a characteristic. The Logia type are elements that can modify the body, the Zoan are of the animal type (and can be extinct or not) and Paramecia are of the object type. These powers may or may not represent a danger to society, all that pose a danger to society are considered criminals and, varying the type of crime, are announced with a reward. The government always seeks to collect its taxes. So in this BigData project we explore the census of this population. Imagining a population of at least 100,000.00 inhabitants, we wrote a project that has MONGODB as its final repository, a non-relational database that organizes its documents by Collections. Below is a glossary of data.

Glossary of Data


Fields Type Description
_id string undescore ID
region_birth string region of birth
country_birth string country of birth
city_birth string city_birth
current_region string current region
current_country string current country
current_city string current city
street string current street
number string number of house
postalcode string postal code
mailer string mailer
street string street name informed
number string number of street name informed
register_data string date your data was entered into the record
type_of_fruit string type of fruit
fruit_name string fruit name
fruit_category string fruit hazard level
number_times_resurrected string number of times that fruit was resurrected
job string occupation
current_job string current job
contracting_company string name of contracting company
start_date string start date in job company
year_working_time string time in year working in company
initial_salary string initial salary
current_wage string current wage
first_name string first name
last_name string last name
gender string gender
race string race of person
birthday string date of birthday
age string age
has_disability string have or do not have a disability
security_social_number string security social number
phone string phone
sketch string sketch
has_tatoo string have or do not have a tatoo
has_scar string have or do not have a scar
has_rewards string have or do not have a rewards
devil_fruit_user string whether or not you are an akuma no mi user
color_hair string color of hair
color_skill string color of skill
type_of_tatoo string type of tatoo
where_in_body string where in body is the tatoo
color_of_tatoo string color of tatoo
scar string where in body is the scar
color_eyes string color of eyes
main_crime string If the person is a criminal. main crime
code_crime string code of crime
tax_collected_government string tax collected by government
debt_with_government string debt with government
rewards string rewards

Description


For a better view of the world of ONE PIECE, its regions, cities and islands, we put the map created for the world.

Map


delta

Start the Project


To run the project, you need to install the dependencies located in the "dependencies" folder and in the root of the project, run the shell_script "run_script.sh".

Sample of Payload in Stagin


address

{
 "_id":"2W1159879A",
 "region_birth":"East Blue",
 "country_birth":"Warship Island",
 "city_birth":"North Wayne",
 "current_region":"East Blue",
 "current_country":"Warship Island",
 "current_city":"East Joshua",
 "street":"Christine Fields",
 "number":"4104",
 "postalcode":"04650",
 "mailer":"m[email protected]",
 "register_data":"20210423"
}

fruit

{
 "_id":"3Y6898825C",
 "type_of_fruit":"it does not have",
 "fruit_name":"it does not have",
 "fruit_category":"it does not have",
 "number_times_resurrected":"0",
 "register_data":"20210622"
}

job

{
 "_id":"2W1159879A",
 "job":"Freight forwarder",
 "current_job":"YES",
 "contracting_company":"Robinson, Simon and Hernandez",
 "start_date":"1981/11/02",
 "year_working_time":40,
 "initial_salary":4904.0,
 "current_wage":5345.36,
 "register_data":"20210423"
}

persona

{
 "_id":"7P1521176A",
 "first_name":"Kristin",
 "last_name":"Smith",
 "gender":"F",
 "race":"Minks",
 "birthday":"1967-03-26",
 "age":"54",
 "devil_fruit_user":"it does not have",
 "has_job":"has",
 "has_tatoo":"it does not have",
 "has_scar":"has",
 "has_disability":"no deficiency",
 "security_social_number":"575-40-5565",
 "phone":"001-985-833-8626x33224",
 "has_rewards":"has",
 "sketch":"https://www.lorempixel.com/350/215",
 "register_data":"20210816"
}

physical_characteristics

{
 "_id":"1S6151128X",
 "color_hair":"SeaShell",
 "color_skill":"BLUISH",
 "type_of_tatoo":"it does not have",
 "where_in_body":"it does not have",
 "color_of_tatoo":"it does not have",
 "scar":"Left arm",
 "color_eyes":"SeaShell",
 "register_data":"20210828"
}

rewards

{
 "_id":"2W1159879A",
 "ssn_people":"165-53-1723",
 "main_crime":"female violence",
 "code_crime":13,
 "tax_collected_government":37824.56,
 "debt_with_government":31503.56,
 "rewards":961679.94,
 "register_data":"20210423"
}

Sample of Payload in Datalake


one_piece

collection not_fruit_user

> db.not_fruit_user.findOne()
{
        "_id" : ObjectId("61a80938f9fae20940d6d7a9"),
        "payload" : {
                "personal_information" : {
                        "first_name" : "Kimberly",
                        "last_name" : "Thompson",
                        "gender" : "F",
                        "race" : "Dwarf",
                        "birthday" : "1996-11-11",
                        "age" : "25"
                },
                "physical_characteristics" : {
                        "has_disability" : "no deficiency",
                        "color_hair" : "Blue",
                        "color_skill" : "WHITE",
                        "scar" : "Back",
                        "color_eyes" : "Blue"
                },
                "social_characteristics" : {
                        "security_social_number" : "740-38-7150",
                        "phone" : "+1-705-306-4346x28383",
                        "sketch" : "https://dummyimage.com/716x261"
                }
        }
}

collection fruit_user

> db.fruit_user.findOne()
{
        "_id" : ObjectId("61a8143e22cbec6d05f38f4e"),
        "payload" : {
                "personal_characteristics" : {
                        "first_name" : "Kenneth",
                        "last_name" : "Brady",
                        "gender" : "M",
                        "race" : "Skypiea",
                        "birthday" : "2000-05-28",
                        "age" : "21"
                },
                "fruit_characteristics" : {
                        "type_of_fruit" : "Logia",
                        "fruit_name" : "Bismuth\t Bismuth\t no Mi",
                        "fruit_category" : "Dangerous",
                        "number_times_resurrected" : "2"
                },
                "job_characteristics" : {
                        "job" : "Swordsman",
                        "current_job" : "YES",
                        "contracting_company" : "Williams, Wilson and Patterson",
                        "start_date" : "1954/09/01",
                        "year_working_time" : "67",
                        "initial_salary" : "4058.0",
                        "current_wage" : "4423.22"
                },
                "physical_characteristics" : {
                        "type_of_tatoo" : "it does not have",
                        "where_in_body" : "it does not have",
                        "color_of_tatoo" : "it does not have",
                        "color_eyes" : "Red",
                        "color_hair" : "Red",
                        "has_disability" : "no deficiency"
                },
                "social_characteristics" : {
                        "security_social_number" : "151-48-5282",
                        "phone" : "+1-842-853-5857",
                        "sketch" : "https://dummyimage.com/428x136"
                },
                "rewards_informations" : {
                        "main_crime" : "Tax evasion",
                        "code_crime" : "9",
                        "tax_collected_government" : 29491.37,
                        "debt_with_government" : "25393.37",
                        "rewards" : "968090.23"
                }
        }
}

Owner
Maycon Cypriano
DATA ENGINEER | DATA SCIENCE | DATA PYTHON | DATA DRIVEN |
Maycon Cypriano
Program that predicts the NBA mvp based on data from previous years.

NBA MVP Predictor A machine learning model using RandomForest Regression that predicts NBA MVP's using player data. Explore the docs » View Demo · Rep

Muhammad Rabee 1 Jan 21, 2022
Desafio proposto pela IGTI em seu bootcamp de Cloud Data Engineer

Desafio Modulo 4 - Cloud Data Engineer Bootcamp - IGTI Objetivos Criar infraestrutura como código Utuilizando um cluster Kubernetes na Azure Ingestão

Otacilio Filho 4 Jan 23, 2022
BAyesian Model-Building Interface (Bambi) in Python.

Bambi BAyesian Model-Building Interface in Python Overview Bambi is a high-level Bayesian model-building interface written in Python. It's built on to

861 Dec 29, 2022
Useful tool for inserting DataFrames into the Excel sheet.

PyCellFrame Insert Pandas DataFrames into the Excel sheet with a bunch of conditions Install pip install pycellframe Usage Examples Let's suppose that

Luka Sosiashvili 1 Feb 16, 2022
MDAnalysis is a Python library to analyze molecular dynamics simulations.

MDAnalysis Repository README [*] MDAnalysis is a Python library for the analysis of computer simulations of many-body systems at the molecular scale,

MDAnalysis 933 Dec 28, 2022
Uses MIT/MEDSL, New York Times, and US Census datasources to analyze per-county COVID-19 deaths.

Covid County Executive summary Setup Install miniconda, then in the command line, run conda create -n covid-county conda activate covid-county conda i

Ahmed Fasih 1 Dec 22, 2021
A project consists in a set of assignements corresponding to a BI process: data integration, construction of an OLAP cube, qurying of a OPLAP cube and reporting.

TennisBusinessIntelligenceProject - A project consists in a set of assignements corresponding to a BI process: data integration, construction of an OLAP cube, qurying of a OPLAP cube and reporting.

carlo paladino 1 Jan 02, 2022
Python Implementation of Scalable In-Memory Updatable Bitmap Indexing

PyUpBit CS490 Large Scale Data Analytics — Implementation of Updatable Compressed Bitmap Indexing Paper Table of Contents About The Project Usage Cont

Hyeong Kyun (Daniel) Park 1 Jun 28, 2022
Reading streams of Twitter data, save them to Kafka, then process with Kafka Stream API and Spark Streaming

Using Streaming Twitter Data with Kafka and Spark Reading streams of Twitter data, publishing them to Kafka topic, process message using Kafka Stream

Rustam Zokirov 1 Dec 06, 2021
A simplified prototype for an as-built tracking database with API

Asbuilt_Trax A simplified prototype for an as-built tracking database with API The purpose of this project is to: Model a database that tracks constru

Ryan Pemberton 1 Jan 31, 2022
Python script to automate the plotting and analysis of percentage depth dose and dose profile simulations in TOPAS.

topas-create-graphs A script to automatically plot the results of a topas simulation Works for percentage depth dose (pdd) and dose profiles (dp). Dep

Sebastian Schäfer 10 Dec 08, 2022
pandas: powerful Python data analysis toolkit

pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive.

pandas 36.4k Jan 03, 2023
This repository contains some analysis of possible nerdle answers

Nerdle Analysis https://nerdlegame.com/ This repository contains some analysis of possible nerdle answers. Here's a quick overview: nerdle.py contains

0 Dec 16, 2022
Pypeln is a simple yet powerful Python library for creating concurrent data pipelines.

Pypeln Pypeln (pronounced as "pypeline") is a simple yet powerful Python library for creating concurrent data pipelines. Main Features Simple: Pypeln

Cristian Garcia 1.4k Dec 31, 2022
Pyspark Spotify ETL

This is my first Data Engineering project, it extracts data from the user's recently played tracks using Spotify's API, transforms data and then loads it into Postgresql using SQLAlchemy engine. Data

16 Jun 09, 2022
CPSPEC is an astrophysical data reduction software for timing

CPSPEC manual Introduction CPSPEC is an astrophysical data reduction software for timing. Various timing properties, such as power spectra and cross s

Tenyo Kawamura 1 Oct 20, 2021
A model checker for verifying properties in epistemic models

Epistemic Model Checker This is a model checker for verifying properties in epistemic models. The goal of the model checker is to check for Pluralisti

Thomas Träff 2 Dec 22, 2021
WithPipe is a simple utility for functional piping in Python.

A utility for functional piping in Python that allows you to access any function in any scope as a partial.

Michael Milton 1 Oct 26, 2021
Codes for the collection and predictive processing of bitcoin from the API of coinmarketcap

Codes for the collection and predictive processing of bitcoin from the API of coinmarketcap

Teo Calvo 5 Apr 26, 2022
BinTuner is a cost-efficient auto-tuning framework, which can deliver a near-optimal binary code that reveals much more differences than -Ox settings.

BinTuner is a cost-efficient auto-tuning framework, which can deliver a near-optimal binary code that reveals much more differences than -Ox settings. it also can assist the binary code analysis rese

BinTuner 42 Dec 16, 2022