i uploaded the files. subject name is data visualisation and it not R coding but i think it has to be done in R but it is report forVisualisation Project Planinstructions are there in data.pdf and...

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i uploaded the files. subject name is data visualisation and it not R coding but i think it has to be done in R but it is report forVisualisation Project Planinstructions are there in data.pdf and some instructions for data are there in advice,pdfi don't know the no of pages to written so follow the assignment and complete the report in pages that required
the data source(s) you choose should be large and rich enough to allow for visual presentation of data features from multiple perspectives and at different levels of complexity.


Note: The data you use for this project should not come from other courses you have completed or are currently undertaking. Rather, it should be identified specifically for the purposes of this project. Links to some public data sources are posted under Online Resources tab on the course website.





P a g e 1 | 2 INFS 5116 – DATA VISUALISATION Visualisation Project Plan (SP5 2019) Due 22 September by 11pm General instructions: • This assignment is worth 30% of your final grade and it is due no later than 11pm on Sunday 22 September. • You will need to submit your assignment via learnonline. • The submitted assignment needs to be a single file in pdf file format. • This assignment will be marked out of 30. Assessment task: The aim of this Visualisation Project Plan is to help you structure your proposed visualisation project and to perform some exploratory analysis of your data. It is an important preliminary work which will form a framework for your final submission. Suggested format for your Visualisation Project Plan is as follows: 1. Introduction (2 marks) Present the context for the proposed visualisation and the main question(s) you hope to be able to answer using visualisations. 2. Data Sources (5 marks) Describe the data source(s) that you plan on using for your visualisation project, where it comes from, how it was collected, its size, number and type of variables etc. Also, the data source(s) you choose should be large and rich enough to allow for visual presentation of data features from multiple perspectives and at different levels of complexity. P a g e 2 | 2 Note: The data you use for this project should not come from other courses you have completed or are currently undertaking. Rather, it should be identified specifically for the purposes of this project. Links to some public data sources are posted under Online Resources tab on the course website. 3. Project Plan (8 marks) Outline and justify the approach you propose to take in building your visualisations, including concepts and techniques covered in this course. Propose some elementary, intermediate and overall level questions that may be addressed using your chosen data set(s). Identify the scope of the proposed visualisation project and possible problems that may occur along the way. 4. Data Preparation (5 marks) Perform and provide a summary of any data preparation tasks that are required before you embark on building your data visualisations, e.g. joining of files and identifying data problems (missing values or data errors). 5. Exploratory Data Analysis (8 marks) Present results of preliminary exploration of your data, which can include descriptive statistics and graphs aimed at helping you to get to know and understand your data before you begin building your main visualisations. What do your preliminary results suggest in relation to the questions of interest identified in section 3? Comment briefly. 6. References (2 marks) Provide a list of all references that you have cited in the project plan. 1 INFS 5116 – Data Visualisation Visualisation Project Plan Context – choosing your project • What are you curious about? What would you like to know? Choose a topic that is of personal interest to you. • What is the purpose of your project going to be? What will you focus on? Who is going to be your intended audience? Working with data – initial stages • Data acquisition o What type of data will you need? o What data is actually available? o Where might you find the data you need? • Collection method o How will you obtain your data? • Data examination o Physical properties (type, size, condition) of your data • Data transformation o Cleaning (identifying and correcting problem areas) o Creating new variables o Consolidating data sources • Data exploration o This is an important step in planning your project o Use visual techniques and statistical analysis (but only as appropriate) in order to ‘see’ the data for yourself. o Note: graphics created at this stage may not be the ones you use in your final version. The idea here is to interrogate the data from many different angles to better understand it. Once you really know what you have, you may need to modify some of your plans. o You do not have to visualise all of your data; using only some of the variables or using summarised data may be more appropriate for your purpose. Visualisation Project Plan Context – choosing your project Working with data – initial stages
Answered Same DaySep 23, 2021

Answer To: i uploaded the files. subject name is data visualisation and it not R coding but i think it has to...

Pritam answered on Sep 27 2021
158 Votes
---
title: "Untitled"
author: "Untitled"
date: "27 September 2019"
output: pdf_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# Introduction:
The data set is
chosen for ansering different aspects of the NFL players involved in different arrest incidents. This mostly covers the data from the year of 2000 to 2017. Hence it could be assumed to be a rich source for any kind of visualization analysis. SO, the basic questions that are planned to be answered here is the following. During which year the players get arrested mostly? Who are the top 20 players involved in such arrest incidents? Which position players are involved in these kind of incidents? What are the main outcome of such incidents? What kind of categories do these incidents belong to?
# Data Sources:
Basically, the data is taken from http://nflarrest.com/ which actually provides an interactive visualized database of National Football League player Arrests & Charges. This is an official official website and hence trustworthy as far aS the validity and reliability of the data is concerned. The data set mainly contains 850 observations and 8 variables. All the attributes seem to be quite significant while answering the questions mentioned above. The variables are Date, Team, Name of the player, Case against him, Category of the case he was involved in, Description of the crime, Outcome of the arrest incident. As far as the questions asked are concerned this data seems to be perfect and rich enough to visualize the answers and hence to have a clarified concept about the players and the incidents.
# Project Plan:
Throughout the analysis the summarization technique is applied first to collect and arrange the data properly before any further visualization technique. The ggplot function in R has been quite useful in this concern. Mainly different types of bar chart to represent the idea properly.
# Exploratory data analysis(EDA):
# Required libraries:
```{r, warning=FALSE,...
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