Wages in the United States increased 4.86 percent in August of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset provides annual personal income estimates for State of Iowa produced by the U.S. Bureau of Economic Analysis beginning in 1997. Data includes the following estimates: personal income, per capita personal income, wages and salaries, supplements to wages and salaries, private nonfarm earnings, compensation of employees, average compensation per job, and private nonfarm compensation. Personal income is defined as the sum of wages and salaries, supplements to wages and salaries, proprietors’ income, dividends, interest, and rent, and personal current transfer receipts, less contributions for government social insurance. Personal income for Iowa is the income received by, or on behalf of all persons residing in Iowa, regardless of the duration of residence, except for foreign nationals employed by their home governments in Iowa. Per capita personal income is personal income divided by the Census Bureau’s annual midyear (July 1) population estimates. Wages and salaries is defined as the remuneration receivable by employees (including corporate officers) from employers for the provision of labor services. It includes commissions, tips, and bonuses; employee gains from exercising stock options; and pay-in-kind. Judicial fees paid to jurors and witnesses are classified as wages and salaries. Wages and salaries are measured before deductions, such as social security contributions, union dues, and voluntary employee contributions to defined contribution pension plans. Supplements to wages and salaries consists of employer contributions for government social insurance and employer contributions for employee pension and insurance funds. Private nonfarm earnings is the sum of wages and salaries, supplements to wages and salaries, and nonfarm proprietors' income, excluding farm and government. Compensation to employees is the total remuneration, both monetary and in kind, payable by employers to employees in return for their work during the period. It consists of wages and salaries and of supplements to wages and salaries. Compensation is presented on an accrual basis - that is, it reflects compensation liabilities incurred by the employer in a given period regardless of when the compensation is actually received by the employee. Average compensation per job is compensation of employees divided by total full-time and part-time wage and salary employment. Private nonfarm compensation is the sum of wages and salaries and supplements to wages and salaries, excluding farm and government. More terms and definitions are available on https://apps.bea.gov/regional/definitions/.

💾 The data

The data comes from Datacamp competition. Data collected by a survey hosted by an HR consultancy, available in 'salaries.csv'.

Each row represents a single employee's salary record for a given year:

• work_year - The year the salary was paid.
• experience_level - Employee experience level:
  • EN: Entry-level / Junior
  • MI: Mid-level / Intermediate
  • SE: Senior / Expert
  • EX: Executive / Director
• employment_type - Employment type:
  • PT: Part-time
  • FT: Full-time
  • CT: Contract
  • FL: Freelance
• job_title - The job title during the year.
• salary - Gross salary paid (in local currency).
• salary_currency - Salary currency (ISO 4217 code).
• salary_in_usd - Salary converted to USD using average yearly FX rate.
• employee_residence - Employee's primary country of residence (ISO 3166 code).
• remote_ratio - Percentage of remote work:
  • 0: No remote work (<20%)
  • 50: Hybrid (50%)
  • 100: Fully remote (>80%)
• company_location - Employer's main office location (ISO 3166 code).
• company_size - Company size:
  • S: Small (<50 employees)
  • M: Medium (50–250 employees)
  • L: Large (>250 employees)

Corporate Profits in the United States increased to 3259.41 USD Billion in the second quarter of 2025 from 3252.44 USD Billion in the first quarter of 2025. This dataset provides the latest reported value for - United States Corporate Profits - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Statistics on average annual salaries of graduates of full-time UGC-funded programmes who were in Full-time Employment

This dataset contains the salaries of Data Science Professionals for year 2020 and 2021.

About Dataset :

work_year : The year during which the salary was paid. There are two types of work year values: 2020 Year with a definitive amount from the past 2021e Year with an estimated amount (e.g. current year)

experience_level : The experience level in the job during the year with the following possible values: EN Entry-level / Junior MI Mid-level / Intermediate SE Senior-level / Expert EX Executive-level / Director

employment_type : The type of employement for the role: PT Part-time FT Full-time CT Contract FL Freelance

job_title : The role worked in during the year. salary The total gross salary amount paid.

salary_currency : The currency of the salary paid as an ISO 4217 currency code.

salaryinusd : The salary in USD (FX rate divided by avg. USD rate for the respective year via fxdata.foorilla.com).

employee_residence : Employee's primary country of residence in during the work year as an ISO 3166 country code.

remote_ratio : The overall amount of work done remotely, possible values are as follows: 0 No remote work (less than 20%) 50 Partially remote 100 Fully remote (more than 80%)

company_location : The country of the employer's main office or contracting branch as an ISO 3166 country code.

company_size : The average number of people that worked for the company during the year: S less than 50 employees (small) M 50 to 250 employees (medium) L more than 250 employees (large)

Dataset Source - ai-jobs.net Salaries

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

Average and median disability pay ratio in annual employment income and in annual wages, salaries and commissions. Data are available by gender, age group and highest level of education.

Average hourly and weekly wage rate, and median hourly and weekly wage rate by North American Industry Classification System (NAICS), type of work, gender, and age group.

📹Project Video available on YouTube - https://youtu.be/fykrwQD3HR4

🖇️Connect with me on LinkedIn - https://www.linkedin.com/in/rohit-grewal

Human Resource (HR) Data of a Multi-national Corporation (MNC) - 2 Million Records

This dataset contains HR information for employees of a multinational corporation (MNC). It includes 2 Million (20 Lakhs) employee records with details about personal identifiers, job-related attributes, performance, employment status, and salary information. The dataset can be used for HR analytics, including workforce distribution, attrition analysis, salary trends, and performance evaluation.

This data is available as a CSV file. We are going to analyse this data set using the Pandas. This analyse will be helpful for those working in HR domain.

Using this dataset, we answered multiple questions with Python in our Project.

Q.1) What is the distribution of Employee Status (Active, Resigned, Retired, Terminated) ?

Q.2) What is the distribution of work modes (On-site, Remote) ?

Q.3) How many employees are there in each department ?

Q.4) What is the average salary by Department ?

Q.5) Which job title has the highest average salary ?

Q.6) What is the average salary in different Departments based on Job Title ?

Q.7) How many employees Resigned & Terminated in each department ?

Q.8) How does salary vary with years of experience ?

Q.9) What is the average performance rating by department ?

Q.10) Which Country have the highest concentration of employees ?

Q.11) Is there a correlation between performance rating and salary ?

Q.12) How has the number of hires changed over time (per year) ?

Q.13) Compare salaries of Remote vs. On-site employees — is there a significant difference ?

Q.14) Find the top 10 employees with the highest salary in each department.

Q.15) Identify departments with the highest attrition rate (Resigned %).

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These are the main Features/Columns available in the dataset :

1) Unnamed: 0 – Index column (auto-generated, not useful for analysis, will be deleted).

2) Employee_ID – Unique identifier assigned to each employee (e.g., EMP0000001).

3) Full_Name – Full name of the employee.

4) Department – Department in which the employee works (e.g., IT, HR, Marketing, Operations).

5) Job_Title – Designation or role of the employee (e.g., Software Engineer, HR Manager).

6) Hire_Date – The date when the employee was hired by the company.

7) Location – Geographical location of the employee (city, country).

8) Performance_Rating – Performance evaluation score (numeric scale, higher is better).

9) Experience_Years – Number of years of professional experience the employee has.

10) Status – Current employment status (e.g., Active, Resigned).

11) Work_Mode – Mode of working (e.g., On-site, Hybrid, Remote).

12) Salary_INR – Annual salary of the employee in Indian Rupees.

Average and median gender pay ratio in annual employment income and in annual wages, salaries and commissions. Data are available by National Occupational Classification (NOC) and age group.

Superintendent's Annual Report - Total Instructional Positions and Average Annual Salaries - Fiscal Year 2023

Average weekly earnings at industry level including manufacturing, construction and energy, Great Britain, monthly, non-seasonally adjusted. Monthly Wages and Salaries Survey.

The baseball industry is one of the most lucrative sports in the world, with players and teams earning substantial amounts of money each year. The salaries of baseball players are determined by a variety of factors, including their performance statistics, years of experience, and the financial resources of their respective teams. To gain a better understanding of how these factors impact player salaries, a comprehensive dataset has been compiled that contains information on baseball player statistics and team financials.

The dataset includes information on player salaries, performance metrics such as batting average, home runs, and RBI, as well as team data such as win-loss records and payroll. With this information, researchers and analysts can explore the relationship between player performance and compensation, as well as the spending habits of individual teams.

This dataset has the potential to provide valuable insights into the inner workings of the baseball industry and could be used to inform decisions related to player contracts, team management, and league policies. Additionally, the dataset may be of interest to fans of the sport who want to better understand how their favorite players and teams are compensated.

Average weekly earnings at sector level headline estimates, Great Britain, monthly, seasonally adjusted. Monthly Wages and Salaries Survey.

Abstract copyright UK Data Service and data collection copyright owner. The Monthly Wages and Salaries Survey (MWSS) is the main source of information for three key indicators of Short-Term Earnings generated by the Office for National Statistics: the Average Earnings Index, the Average Weekly Earnings and the Index of Labour Costs per Hour. The MWSS is distributed monthly to approximately 8,800 businesses and covers around 12.8 million employees. Companies are required to respond under the Statistics of Trade Act 1947. Businesses are selected from the Inter-Departmental Business Register. Every company with more than 1,000 employees is surveyed. Sampling is random for businesses with fewer than 1,000 employees. The MWSS does not cover businesses with fewer than 20 employees, and so the very smallest businesses in the economy are not represented. The self-employed and government-supported trainees are also not surveyed. The major strength of the MWSS is that it provides comprehensive information on earnings, by industry. In terms of industrial coverage, information on all industries is collected, as defined by the Standard Industrial Classifications (1992). Information on both the public and private sectors is available. Linking to other business studiesThese data contain Inter-Departmental Business Register reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.Latest edition informationFor the fortieth edition (August 2024), three monthly data files for February 2024 to April 2024 have been added to the study. Main Topics: The survey measures commission, bonuses, overtime and pay award arrears, in addition to pay. The survey also collects data on the number of employees on the payroll. The measures are the sums for each company, and are not subdivided by occupation or by individual workers. The survey excludes redundancy payments and benefits in kind.The data files have been processed to include average weekly pay data and all of the processing variables such as grossing factors and grossed values.

The average monthly salary for active Child Protective staff as of the last day of the fiscal year by staff type. The county and region of the employees are determined by the office to which they are assigned. More information at www.dfps.texas.gov NOTE: Child Protective Investigations (CPI), Child Care Investigations (CCI), and Child Protective Services (CPS) Staff are all included. Child Care Investigations (CCI), which is a part of CPI and include Day Care Investigations (DCI) and Residential Child Care Investigations (RCCI) are only available from 2018 onward. This is due to the split of those job functions from Child Care Licensing, which was a part of DFPS until 2017, when it was transferred to the Health and Human Services Commission (HHSC). This addresses Texas Human Resource Code Section 40.0516(11).

Superintendent's Annual Report - Total Instructional Positions and Average Annual Salaries - Fiscal Year 2022

Superintendent's Annual Report - Total Instructional Positions and Average Annual Salaries - Fiscal Year 2021

Average weekly earnings, average hourly wage rate and average usual weekly hours by union status and type of work, last 5 years.