ade-irawan / dummy-datasets

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

dummy-datasets

  1. hr_data.csv
    Why are our best and most experienced employees leaving prematurely?
    A data frame with 14999 rows and 10 variables

    Details

     satisfaction_level: Level of satisfaction (0-1)
     last_evaluation: Time since last performance evaluation (in Years)
     number_project: Number of projects completed while at work
     average_montly_hours: Average monthly hours at workplace
     time_spend_company: Number of years spent in the company
     Work_accident: Whether the employee had a workplace accident
     left: Whether the employee left the workplace or not (1 or 0) Factor
     promotion_last_5years: Whether the employee was promoted in the last five years
     sales Department: in which they work for
     salary: Relative level of salary (high)
    

    source: https://www.rdocumentation.org/packages/breakDown/versions/0.2.1/topics/HR_data

  2. melb_data.csv
    Why are our best and most experienced employees leaving prematurely?
    A data frame with 14999 rows and 10 variables

    Details

     Rooms: Number of rooms
     Price: Price in dollars
     Method: S - property sold; SP - property sold prior; PI - property passed in; PN - sold prior not disclosed; SN - sold not disclosed; NB - no bid; VB - vendor bid; W - withdrawn prior to auction; SA - sold after auction; SS - sold after auction price not disclosed. N/A - price or highest bid not available.
     Type: br - bedroom(s); h - house,cottage,villa, semi,terrace; u - unit, duplex; t - townhouse; dev site - development site; o res - other residential.
     SellerG: Real Estate Agent
     Date: Date sold
     Distance: Distance from CBD
     Regionname: General Region (West, North West, North, North east …etc)
     Propertycount: Number of properties that exist in the suburb.
     Bedroom2 : Scraped # of Bedrooms (from different source)
     Bathroom: Number of Bathrooms
     Car: Number of carspots
     Landsize: Land Size
     BuildingArea: Building Size
     CouncilArea: Governing council for the area
    

    source: https://www.kaggle.com/datasets/dansbecker/melbourne-housing-snapshot

About