Reference no: EM132755604

CIS7031 Programming for Data Analysis - Cardiff University

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 various environments 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.

EDGE

The Cardiff Met EDGE supports students in graduating with the knowledge, skills, and attributes that allow them to contribute positively and effectively to the communities in which they live and work.

This module assessment provides opportunities for students to demonstrate development of the following EDGE Competencies:

Assessment Requirements / Tasks (include all guidance notes)

This assignment will use COVID-19 Data from our world in data data source. This dataset is updated daily and includes data on confirmed cases, deaths, hospitalizations, and testing, as well as other variables of potential interest. The description of the fields can be found here.
For this assignment students will undertake a data analysis and machine learning approach to reveal the .

1. Data processing
1.1. Download the dataset from the link above and create a dataframe that contains Europe data only.
1.2. Check for any null value or outlier. If found then treat appropriately (replace with zeros, means, drop rows).
1.3. Drop the columns related to handwashing , testing, smoking and continent.

Show the result.

2. Data analysis
For each question provide graph/chart along with your own interpretation (~ 50 words)
2.1. Which country has reported the highest and lowest covid cases over the period?
2.2. Which country has the has the highest and lowest deaths per million residents?
2.3. Which date was the highest number of cases reported and by which country?
2.4. Which date did UK report lowest number of cases?
3. Visual analysis
Create a dynamic scatter/bubble plot showing the total cases per country over the period using Plotly express. Write your interpretation of the findings (~100 words).
4. PCA/Correlation
4.1. Undertake a PCA (PC=2; columns should be like PC1, PC2) and produce a scatter plot. Write your interpretation about the plot and in relation to the analysis of section 2 & 3 (explain the variance.)
4.2. Is there a correlation between the number of deaths and age? Support your answer with discussion and plots.

5. Clustering (k means & hierarchical)
5.1. Using the hospital beds and GDP per capita ,undertake a K means clustering analysis (K=2 & 3) and identify countries cluster together. Write your own interpretation (~100 words).

5.2. Using the same dataset (5.1) create a hierarchical cluster. Compare the cluster with k means clusters (~100 words).

6. Discussion
Provide a brief discussion (~ 300 words) on the COVID deaths with respect to Countries economic activity and demographics based on the data analysis results.

Attachment:- Programming for Data Analysis.rar