4everjoy/Palmora-Group-HR-Analysis-

#### Case Study 2 : A Company in Nigeria embroiled in issues bordering on gender inequality in its 3 regions. As a data analyst, analyse the company data and generate insights that the Palmoria management team would need to address this issue using appropriate charts , “Now, the future of gender equality in Palmoria lies in your hands” . # Palmora-Group-HR-Analysis- #### Case Study 2 : A Company in Nigeria embroiled in issues bordering on gender inequality in its 3 regions. As a data analyst, analyse the company data and generate insights that the Palmoria management team would need to address this issue using appropriate charts , “Now, the future of gender equality in Palmoria lies in your hands” . ##### Question 1. What is the gender distribution in the organization? Distil to regions and departments. ##### Question 2. Show insights on ratings based on gender ##### Question 3. Analyse the company’s salary structure. Identify if there is a gender pay gap. If there is, identify the department and regions that should be the focus of management ##### Question 4. A recent regulation was adopted which requires manufacturing companies to pay employees a minimum of $90,000 ● Does Palmoria meet this requirement? ● Show the pay distribution of employees grouped by a band of $10,000. For example: ● How many employees fall into a band of $10,000 – $20,000, $20,000 – $30,000, etc.? ● Also visualize this by regions ##### Question 5. Mr Gamma thought to himself that since you were already working on the employee data, you could help out with allocating the annual bonus pay to employees based on the performance rating. He handed you another data set that contains rules for making bonus payments and asked you to: ● Calculate the amount to be paid as a bonus to individual employees. ● Calculate the total amount to be paid to individual employees (salary inclusive of bonus). ● Total amount to be paid out per region and company-wide. ##### Step: * Cleaning of Data * Assigning generic gender for employees with missing or undisclossed gender represented with unknown. * Employee with no salary is filter * Rows with null department was removed. This is done to ensure only active employee with valid department information. * Stacked column was used for the Gender Distribution by Region and Department. * A …