Commodity Price Data Analysis Using Web Scraping

Abstract

Today, analysis of data which is available on the web has become more popular, by using such data we are capable to solve many issues. Our project deals with the analysis of commodity price data available on the web. In general, commodity price data analysis is performed to know inflation rate prevailing in the country and also to know cost price index (CPI). Presently in some countries this analysis is done manually by collecting data from different cities, then calculate inflation and CPI using some predefined formulae. To make this entire process automatic we are developing this project. Now a day’s most of the customers are depending on online websites for their day to day purchases. This is the reason we are implementing a system to collect the data available in various e-commerce sites for commodity price analysis. Here, we are going to introduce a data scraping technique which enables us to collect data of various products available online and then store it in a database there after we perform analysis on them. By this process we can reduce the burden of collecting data manually by reaching various cities. The system consists of web module which perform analysis and visualization of data available in the database.