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Socio-economic indicators are extracted using API and web scraping. The data is analyzed for multiple countries and over time using Python. This project was implemented as part of Intermediate Python Coursework.

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premlogan/Analyze_Social_Indicators_Data_Using_Python

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Project title: Socio- Economic Indicators Portal using Python

Different packages used:JSON, pandas, requests, urlib.request, Matplotlib, seaborn and Beautiful Soup

Abstract:

Socio-economic indicators for different countries are present on different website for agencies like World Health Organization and World Bank. As the data is in different formats, this project creates a program that will compare and analyze performance of ten socio-economic indicators like GDP per capita, infant mortality etc., for ten South Asian Countries for ten years.

Data on the public websites was in the form of API, JSON, CSV or text. So, we used API function call and web scraping to extract and integrate the data. The final program shows a country’s profile, compare indicators for different South Asia country and allow the user to find the correlation for any two indicators for a country.

Team members: Aamir Abbas, Ali Iftikhar, Ajay Valecha, Premkumar Loganathan

Instructions to the run the code: Run the Main_menu.py file which loads all other .py files and provides the menu options to analyze different socio economic indicator data.

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Socio-economic indicators are extracted using API and web scraping. The data is analyzed for multiple countries and over time using Python. This project was implemented as part of Intermediate Python Coursework.

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