Codebook - HR Dataset v13
Dr. Rich Huebner
9/27/2019
Introduction to the HR Dataset - Version 13
The HR Dataset was designed by Drs. Rich Huebner and Carla Patalano to accompany a case study designed for graduate HR students studying HR metrics, measurement, and analytics. The students use Tableau data visualization software to uncover insights about the case. This is a synthetic data set created specifically to go along with the case study (proprietary for the college that we teach at).
Every year or so, we update the data set to include additional columns, and to make slight changes to the underlying data. In this version, we add several new features to the data set:
- Engagement Survey Results, a floating-point number, range between 1 and 5.
- Special Project Count, integer, which is the number of special projects the employee worked on in the last year.
- Last Performance Review Date, date, to ensure that all employees are receiving timely reviews.
- Days Late in the Last 30 days, integer, as an attendance metric.
Fields removed since last iteration
- Any derived fields such as AGE and DaysEmployed have been removed.
Data Dictionary
| Feature | Description | DataType |
|---|---|---|
| Employee Name | Employee’s full name | Text |
| EmpID | Employee ID is unique to each employee | Text |
| MarriedID | Is the person married (1 or 0 for yes or no) | Binary |
| MaritalStatusID | Marital status code that matches the text field MaritalDesc | Integer |
| EmpStatusID | Employment status code that matches text field EmploymentStatus | Integer |
| DeptID | Department ID code that matches the department the employee works in | Integer |
| PerfScoreID | Performance Score code that matches the employee’s most recent performance score | Integer |
| FromDiversityJobFairID | Was the employee sourced from the Diversity job fair? 1 or 0 for yes or no | Binary |
| PayRate | The person’s hourly pay rate. All salaries are converted to hourly pay rate | Float |
| Termd | Has this employee been terminated - 1 or 0 | Binary |
| PositionID | An integer indicating the person’s position | Integer |
| Position | The text name/title of the position the person has | Text |
| State | The state that the person lives in | Text |
| Zip | The zip code for the employee | Text |
| DOB | Date of Birth for the employee | Date |
| Sex | Sex - M or F | Text |
| MaritalDesc | The marital status of the person (divorced, single, widowed, separated, etc) | Text |
| CitizenDesc | Label for whether the person is a Citizen or Eligible NonCitizen | Text |
| HispanicLatino | Yes or No field for whether the employee is Hispanic/Latino | Text |
| RaceDesc | Description/text of the race the person identifies with | Text |
| DateofHire | Date the person was hired | Date |
| DateofTermination | Date the person was terminated, only populated if, in fact, Termd = 1 | Date |
| TermReason | A text reason / description for why the person was terminated | Text |
| EmploymentStatus | A description/category of the person’s employment status. Anyone currently working full time = Active | Text |
| Department | Name of the department that the person works in | Text |
| ManagerName | The name of the person’s immediate manager | Text |
| ManagerID | A unique identifier for each manager. | Integer |
| RecruitmentSource | The name of the recruitment source where the employee was recruited from | Text |
| PerformanceScore | Performance Score text/category (Fully Meets, Partially Meets, PIP, Exceeds) | Text |
| EngagementSurvey | Results from the last engagement survey, managed by our external partner | Float |
| EmpSatisfaction | A basic satisfaction score between 1 and 5, as reported on a recent employee satisfaction survey | Integer |
| SpecialProjectsCount | The number of special projects that the employee worked on during the last 6 months | Integer |
| LastPerformanceReviewDate | The most recent date of the person’s last performance review. | Date |
| DaysLateLast30 | The number of times that the employee was late to work during the last 30 days | Integer |
Structure of HR Data Set
## 'data.frame': 401 obs. of 35 variables:
## $ Employee_Name : Factor w/ 311 levels "","Adinolfi, Wilson K",..: 30 156 271 129 257 262 34 41 67 68 ...
## $ EmpID : int 1103024456 1106026572 1302053333 1211050782 1307059817 711007713 1504073368 1403065721 1408069481 1306059197 ...
## $ MarriedID : int 1 0 0 1 0 1 1 0 0 1 ...
## $ MaritalStatusID : int 1 2 0 1 0 1 1 0 0 1 ...
## $ GenderID : int 0 1 1 0 0 0 0 0 0 1 ...
## $ EmpStatusID : int 1 1 1 1 1 5 5 1 1 1 ...
## $ DeptID : int 1 1 1 1 1 1 6 6 6 6 ...
## $ PerfScoreID : int 3 3 3 3 3 3 3 3 1 3 ...
## $ FromDiversityJobFairID : int 1 0 0 0 0 1 0 0 0 0 ...
## $ PayRate : num 28.5 23 29 21.5 16.6 ...
## $ Termd : int 0 0 0 1 0 1 1 0 0 0 ...
## $ PositionID : int 1 1 1 2 2 2 3 3 3 3 ...
## $ Position : Factor w/ 33 levels "","Accountant I",..: 2 2 2 3 3 3 4 4 4 4 ...
## $ State : Factor w/ 29 levels "","AL","AZ","CA",..: 12 12 12 12 12 12 27 28 29 17 ...
## $ Zip : int 1450 1460 2703 2170 2330 1844 21851 5664 98052 3062 ...
## $ DOB : Factor w/ 307 levels "","01/02/51",..: 284 88 205 224 116 140 130 111 110 220 ...
## $ Sex : Factor w/ 3 levels "","F","M ": 2 3 3 2 2 2 2 2 2 3 ...
## $ MaritalDesc : Factor w/ 6 levels "","Divorced",..: 3 2 5 3 5 3 3 5 5 3 ...
## $ CitizenDesc : Factor w/ 4 levels "","Eligible NonCitizen",..: 4 4 4 4 4 4 2 4 4 4 ...
## $ HispanicLatino : Factor w/ 5 levels "","no","No","yes",..: 3 3 3 3 3 3 3 3 5 3 ...
## $ RaceDesc : Factor w/ 7 levels "","American Indian or Alaska Native",..: 4 4 7 7 7 3 4 7 7 2 ...
## $ DateofHire : Factor w/ 100 levels "","1/10/2011",..: 21 10 95 33 53 93 85 87 36 87 ...
## $ DateofTermination : Factor w/ 94 levels "","01/02/12",..: 1 1 1 29 1 76 56 1 1 1 ...
## $ TermReason : Factor w/ 18 levels "","Another position",..: 12 12 12 1 12 4 2 12 12 12 ...
## $ EmploymentStatus : Factor w/ 6 levels "","Active","Future Start",..: 2 2 2 5 2 6 6 2 2 2 ...
## $ Department : Factor w/ 7 levels "","Admin Offices",..: 2 2 2 2 2 2 6 6 6 6 ...
## $ ManagerName : Factor w/ 22 levels "","Alex Sweetwater",..: 5 5 5 5 5 5 14 14 14 14 ...
## $ ManagerID : int 1 1 1 1 1 1 17 17 17 17 ...
## $ RecruitmentSource : Factor w/ 24 levels "","Billboard",..: 5 23 10 18 23 5 21 2 23 18 ...
## $ PerformanceScore : Factor w/ 5 levels "","Exceeds","Fully Meets",..: 3 3 3 3 3 3 3 3 5 3 ...
## $ EngagementSurvey : num 2.04 5 3.9 3.24 5 3.8 3.14 5 2.3 3.6 ...
## $ EmpSatisfaction : int 2 4 5 3 3 4 5 5 1 5 ...
## $ SpecialProjectsCount : int 6 4 5 4 5 4 0 0 0 0 ...
## $ LastPerformanceReview_Date: Factor w/ 43 levels "","1/10/2019",..: 5 7 8 1 5 1 1 11 18 20 ...
## $ DaysLateLast30 : int 0 0 0 NA 0 NA NA 0 0 0 ...
## NULLSample Visualizations using ggplot2 and ggthemes
