@nurshakirahmdsalleh
Stream Lit Iris

@nurshakirahmdsalleh

@nurshakirahmdsalleh

@saranyaravikumar

Sorry Dr Sara, we have mistakenly 'replied as a topic' to your post for our visualisation data presentation yesterday. We will reply here again with the results of our Colab.

First of all, our group members consists of:

1. Nur Fera Ereen
2. As Noor Aqilah
3. Nur Hidayah
4. Nazatul Shahirah

We have selected the HR_Data.

Problem Statement: To identify the duration of last employed job impacts on employee's decision on changing the job.

Our dataframe have six variables:

• gender: Categorical variable representing the gender of the individuals (e.g., "Male," "Female," "Other").

• relevent_experience: Categorical variable indicating whether the individual has relevant experience (e.g., "Has relevent experience," "No relevent experience").

• experience: Numeric variable representing the years of experience.

• last_new_job: Numeric variable indicating the time since the last job change.

• company_size: Numeric variable representing the size of the company.

• target: Binary variable (0 or 1) indicating whether the individual is the target of interest.

Four Variable (Two Numerical, Two Categorical)

Interpretation: This grouped bar plot visualizes the interaction between company size, last new job, gender, and relevant experience.

Conclusion: The plot suggests that the distribution of last new job changes varies across different company sizes, and this relationship differs between genders and relevant experience groups.

Five Variable (Three Numerical,Two Categorical)

Interpretation: This scatter plot shows the relationships between experience, last new job, and target, with points colored and shaped according to gender and relevant experience.

Conclusion: The plot provides a multidimensional view of the dataset, allowing for the examination of multiple variables simultaneously.

Findings:
We have identified that the duration of last employed job does give impacts on employee's decision on changing the job. As their duration of last employed job and experience increases over the years, they have the more tendency to stay at their jobs.

Thank you for your teaching, we truly appreciate your efforts and patience to guide us through! You make us become super interested in R-coding