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This repository contains the code and data for analyzing revenue trends of NSE-listed multinational corporations (MNCs) in India. The analysis focuses on understanding the revenue performance of these companies and assessing their profitability.

Jupyter Notebook 100.00%
data-analysis data-visualization jupyter-notebook python data-preprocessing

data-analysis---nse-mnc-revenue-21-23's Introduction

Data analysis - NSE MNC Revenue 21-23

This repository contains the code and data for analyzing revenue trends of NSE-listed multinational corporations (MNCs) in India. The analysis focuses on understanding the revenue performance of these companies and assessing their profitability.

Data Collection

The revenue data for fiscal years 2021, 2022, and 2023 were collected from Moneycontrol.com, a reputable financial data platform. Additionally, company details such as addresses and email addresses were sourced from Cleartax.in to ensure consistency and reliability in data collection.

Methodology

  • The data was cleaned and processed to calculate percentage changes in revenue for each company between fiscal years.
  • Analysis was conducted to identify companies with significant revenue growth and assess overall profitability post-pandemic.

Key Findings

  • Almost all analyzed companies exhibit profitability, with consistent revenue growth observed across multiple fiscal years.
  • Several companies stand out for experiencing significant percentage changes in revenue, indicating resilience and adaptability.

Repository Contents

How to Use

  1. Clone this repository to your local machine.
  2. Open and run the NSE MNC Revenue 21-23.ipynb notebook in Jupyter environment to view the analysis.
  3. Explore the code and data to gain insights into revenue trends and profitability of NSE-listed MNCs.

Future Work

  • Further analysis could be conducted to delve deeper into specific industries or companies with notable revenue changes.
  • Visualization techniques could be enhanced to provide more interactive and insightful representations of the data.

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