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A labor market is a place where workers and employees interact with each other. In the market, employers compete to hire the effective, and also the employers compete for the most effective satisfying job. A market in an economy functions with demand and providing of labor. In this market, labor demand is the firm's demand for labor, and supply is the worker's supply of labor. The supply and demand for labor in the market are influenced by changes in bargaining power.
The Indian labor market is divided into two segments: organized or formal sector and the other is the unorganized sector which is also known as the informal sector. The organized sector in India is that sector which is registered as well as pay tax which are licensed organizations. All self-employed, unlicensed or unregistered economic activity such as rural traders, handicrafts, farmers and owner manned general stores, etc. refers to the unorganized sector or own account enterprises.
Why: Problem statement
Employers demand labor as a result of workers being the most important part of the production process. Workers use tools and equipment to turn inputs into output. Without workers, employers could not manufacture products and services and earn profits. When graphed, the demand for labor looks very similar to the demand for different products and services; it's a downward slope. This indicates that a bigger amount of labor is demanded at lower costs than at higher costs. That is, in the labor market, employers are willing to buy more hours of labor at lower wages than at a higher wage.
In Indian labor markets, workers in the unorganized sector suffer from poor working conditions with almost no income or social security. On the other hand, workers in the organized sector enjoy rising wages, improving working conditions, and secure jobs. This analysis tries to deal with these problems, focusing on where and when the labor market comes down for the unorganized workers, and how to induce greater flexibility in the organized sector
How: Solution description
Labor market analysis is the process of, Identifying the appropriate labor market for various types of positions, Surveying the market to determine the salaries that are being paid for like positions, Identifying market trends such as ancillary pay, and merit and pay practices, Establishing, adjusting, and/or recommending salary changes and/or structures for staff positions, Consulting with management on their workforce needs. Those processes will make a country develop in the labor market and its country's economy.
In this project, I collected railway labour market dataset for the government website. After that I cleaned the dataset, In this cleaning process I applied python programming to clean the data. Then we analysed the labor market and visualised this analysis like scatter plot and bar plot. We are using matplotlib library for the visualization. Here I attached the plot that shows the labor market demand based on the year. Below plot shows the result for this project.
In this chart, you can see the number of laborers ranging from the year of 2000 to 2015.
How is it different from competition
The labor market trend analysis project is the new project listed openly by the Indian government that to be completed by any volunteers, This project is unique in the labor market and also with unique data visuality. In this project, We proposed a python programming language to analyze the labor market. We are using a simple plot. It is easy to understand all levels of laborers.
Who are your customers
The customers of this project are the government sectors, Analysts, Business sectors, Analytical companies, etc. where the supply and the demand for jobs meet, with the workers or labor providing the services that employers demand. The worker may be anyone who wishes to offer his services for compensation while the employer may be a single entity or an organization that is in need of an individual to do a specific job or to complete a task. The worker is then comparable to a seller while the employer is the buyer.
Project Phases and Schedule
Data collection - Data collection is the process of collecting or gathering data from the various resources.
Data wrangling - Data wrangling is also known as data cleaning. It is the process of transforming and mapping the data from one raw data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as data analytics.
Data analysis - Data analysis is a process of cleaning, transforming, and analysing data to discover useful information for business decision making. The purpose of Data Analysis is to extract useful information from data and take the decision based upon the data analysis.
Data visualization - Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.
Anaconda tool - Anaconda may be a free and open-source distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale processing, prediction analysis, etc.), that aims to clarify package management and implementation. The distribution includes data-science packages appropriate for Windows, Linux, and macOS. You can download anaconda tool for Python by clicking this link https://anaconda.org/anaconda/python.
Python version 3.7 - Underneath the Python Releases for Windows find Latest Python 3 Release – Python 3.7. 4 (latest stable release as of now is Python 3.7. The advantages of Python 3.7 are Easier access to debuggers through a new breakpoint() built-in, Simple class creation using data classes, Customized access to module attributes, Improved support for type hinting and Higher precision timing functions. Most companies are still using Python 2 for legacy reasons, but more and more companies are using Python 3, or beginning to make the switch from 2 to 3.
Numpy - The fundamental package for scientific and mathematical computing with Python.
Pandas - It is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
Matplotlib - Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy.