Evaluate and apply key steps and issues involved in data preparation, cleaning, exploring, creating, optimizing and evaluating models.

his assessment is designed to demonstrate a student`s completion of the following Learning Outcomes:

Learning Outcome 1:Critically analyse and evaluate various statistical and computational techniques for analysing datasets and determine the most appropriate technique for a business problem;

Learning Outcome 2:Critically evaluate, develop and implement solutions for processing datasets and solving complex problems in variousenvironments using relevant programming paradigms;

Learning Outcome 3:Evaluate and apply key steps and issues involved in data preparation, cleaning, exploring, creating, optimizing and evaluating models;

Learning Outcome 4:Evaluate and apply aspects of data science applications and their use.

Assessment Requirements

This assignment will use employment data of Wales from the StatsWales data source. This dataset provides workplace employment estimates, or estimates of total jobs, for Wales and its NUTS2 areas, along with comparable UK data disaggregated by industry section.

For this assignment students will undertake a data analysis and machine learning approach to reveal the workplace employment landscape of Wales.

Part 1. Data processing
1.1. Download the dataset for the period 2009 - 2018 and create a dataframe that concatenates Wales (total)employment value only.

1.2. Check for any null value or outlier. If found replace that with mean value.

1.3. Change the name of the industries as bellow

The final data frame should look like following

Part 2. Data analysis
For each question provide graph/chart along with your own interpretation (~ 50 words)
2.1. Which industry employed highest and lowest workers over the period?

2.2. Which industry has the highest and lowest overall growth over the period?

2.3. Which years are the best and worst performing year in relation to number of employment. (highest and lowest employment)

Part 3. Visual analysis

Create a dynamic scatter/bubble plot showing the change of workforce number over the period using Plotly express.