Name: Salary Prediction
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Salary Prediction

Jobs Dataset from Glassdoor

Tech job positions and salaries from glassdoor.com

About this dataset

This dataset contains job postings from Glassdoor.com from 2017 with the following features It can be used to analyze the current trends based on job positions, company size, etc.

How to use the dataset

This dataset contains job postings from Glassdoor.com from 2017, It can be used to analyze salaries based on company size and other information.

Research Ideas

Identify which factors most affect data science salaries

Determine which states and cities offer the highest paying data science jobs

Predict what a data science job posting will pay based on the job description

Acknowledgements

This dataset was scraped from Glassdoor.com by Ramiro Gomez.

License

> License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
> No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: eda_data.csv

Column name	Description
job_id	The unique identifier for the job posting (Numeric)
job_state	The state where the job is located (String)
same_state	A binary indicator of whether the job is in the same state as the person looking at the job (String)
age	The age of the person looking at the job (Numeric)
python_yn	A binary indicator of whether the person looking at the job knows Python (String)
R_yn	A binary indicator of whether the person looking at the job knows R (String)
spark	A binary indicator of whether the person looking at the job knows Spark (String)
aws	A binary indicator of whether the person looking at the job knows AWS (String)
excel	A binary indicator of whether the person looking at the job knows Excel (String)
job_simp	A simplified job title (String)
seniority	The seniority of the job (String)
desc_len	The length of the job description (Numeric)
num_comp	The number of competitors for the job (Numeric)

File: glassdoor_jobs.csv

Column name	Description
job_id	The unique identifier for the job posting (Numeric)

File: salary_data_cleaned.csv

Column name	Description
job_state	The state where the job is located (String)
same_state	A binary indicator of whether the job is in the same state as the person looking at the job (String)
age	The age of the person looking at the job (Numeric)
python_yn	A binary indicator of whether the person looking at the job knows Python (String)
R_yn	A binary indicator of whether the person looking at the job knows R (String)
spark	A binary indicator of whether the person looking at the job knows Spark (String)
aws	A binary indicator of whether the person looking at the job knows AWS (String)
excel	A binary indicator of whether the person looking at the job knows Excel (String)

Tables

Eda Data

@kaggle.thedevastator_jobs_dataset_from_glassdoor.eda_data

1.05 MB
742 rows
33 columns

CREATE TABLE eda_data (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "job_title" VARCHAR,
  "salary_estimate" VARCHAR,
  "job_description" VARCHAR,
  "rating" DOUBLE,
  "company_name" VARCHAR,
  "location" VARCHAR,
  "headquarters" VARCHAR,
  "size" VARCHAR,
  "founded" BIGINT,
  "type_of_ownership" VARCHAR,
  "industry" VARCHAR,
  "sector" VARCHAR,
  "revenue" VARCHAR,
  "competitors" VARCHAR,
  "hourly" BIGINT,
  "employer_provided" BIGINT,
  "min_salary" BIGINT,
  "max_salary" BIGINT,
  "avg_salary" DOUBLE,
  "company_txt" VARCHAR,
  "job_state" VARCHAR,
  "same_state" BIGINT,
  "age" BIGINT,
  "python_yn" BIGINT,
  "r_yn" BIGINT,
  "spark" BIGINT,
  "aws" BIGINT,
  "excel" BIGINT,
  "job_simp" VARCHAR,
  "seniority" VARCHAR,
  "desc_len" BIGINT,
  "num_comp" BIGINT
);

Glassdoor Jobs

@kaggle.thedevastator_jobs_dataset_from_glassdoor.glassdoor_jobs

1.27 MB
956 rows
15 columns

CREATE TABLE glassdoor_jobs (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "job_title" VARCHAR,
  "salary_estimate" VARCHAR,
  "job_description" VARCHAR,
  "rating" DOUBLE,
  "company_name" VARCHAR,
  "location" VARCHAR,
  "headquarters" VARCHAR,
  "size" VARCHAR,
  "founded" BIGINT,
  "type_of_ownership" VARCHAR,
  "industry" VARCHAR,
  "sector" VARCHAR,
  "revenue" VARCHAR,
  "competitors" VARCHAR
);

Salary Data Cleaned

@kaggle.thedevastator_jobs_dataset_from_glassdoor.salary_data_cleaned

1.04 MB
742 rows
28 columns

CREATE TABLE salary_data_cleaned (
  "job_title" VARCHAR,
  "salary_estimate" VARCHAR,
  "job_description" VARCHAR,
  "rating" DOUBLE,
  "company_name" VARCHAR,
  "location" VARCHAR,
  "headquarters" VARCHAR,
  "size" VARCHAR,
  "founded" BIGINT,
  "type_of_ownership" VARCHAR,
  "industry" VARCHAR,
  "sector" VARCHAR,
  "revenue" VARCHAR,
  "competitors" VARCHAR,
  "hourly" BIGINT,
  "employer_provided" BIGINT,
  "min_salary" BIGINT,
  "max_salary" BIGINT,
  "avg_salary" DOUBLE,
  "company_txt" VARCHAR,
  "job_state" VARCHAR,
  "same_state" BIGINT,
  "age" BIGINT,
  "python_yn" BIGINT,
  "r_yn" BIGINT,
  "spark" BIGINT,
  "aws" BIGINT,
  "excel" BIGINT
);