General starter file There were several steps to preparing the general starter file for analysis. This included changing the format of several columns, such as the due date column, to a year format. The quartile data columns needed to be changed to 0 decimal place. It was also important to remove any unnecessary data completed

The quality and reliability of datasets play a crucial role in the success of any project. Datasets are not immune to bias and quality issues, and if not dealt with, these can have consequences for data analysis. Data Bias Bias in datasets refers to unfair or unrepresentative elements that can skew the results. It can

All datasets needed to be uploaded to OneDrive. This is something I am familiar with and I had no issue in utilising OneDrive as required. It is vital to store datasets securely when using these for analysis. As good practice, ensuring data is stored and only accessible by those who require it again follows the

General starter file The starter file uses the UK Government’s gender pay gap data set. The data has been cleaned to remove some columns such as the mean and median bonus percentages, male and female bonus percent and responsible person. Removing the responsible person’s data allows us to follow the Data Ethics Framework and GDPR

The planning stage was a straightforward process to undertake as part of the Data Science Project. As an allocated data set would be used, this provided a starting point that allowed me to begin investigating the area where I wished to focus my investigation. Defining the problem I split the planning stage into six sections