Merge pull request #341 from Shreya7tripathy/Unemployment_Analysis

Added Unemployment Analysis due to COVID

Data Analysis/Readme.md

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+# 📊 Data Analysis Projects
+
+Welcome to the **Data Analysis** section of our Project PyVerse! Here, you’ll find a collection of projects that showcase skills in data analysis, insights derived from various datasets, and visualizations created to communicate those insights effectively.
+
+---
+
+## 🚀 Projects Overview
+
+### Data Analysis Insights
+- **Description**: This section includes analyses of diverse datasets, revealing trends, patterns, and key insights. Each project features a combination of exploratory data analysis, visualization techniques, and graphical representations that enhance understanding and interpretation of the data.
+- **Key Highlights**:
+  - Insights into performance metrics, correlations, and statistical relationships.
+  - Comprehensive visualizations, including charts, graphs, and plots that illustrate findings clearly.
+
+---
+
+## 📈 Key Technologies Used
+
+- **Python Libraries**: 
+  - `pandas` for data manipulation
+  - `numpy` for numerical operations
+  - `matplotlib` and `seaborn` for visualizations
+
+## 💡 Insights Gained
+
+- Each analysis project provided unique insights into the respective datasets, showcasing trends and correlations.
+- Visualization plays a critical role in understanding complex data patterns and communicating findings effectively.
+
+---
+
+## ⭐ Show some ❤️ by starring this Repository!
+
+💌 More projects will be added consecutively. 💌
+
+🎉 We welcome all contributors! Please read our Code of Conduct and Contributing Rules. 🎉
+
+---
+
+## 🚦 Welcome Developers to the Data Analysis Domain of PyVerse!
+
+## 🤝 Contributions
+
+Feel free to contribute! If you have suggestions or improvements, please raise an issue. Only if your issue is assigned to you by our Project Admin , then fork the repository and create a pull request.
+
+---
+
+## 📧 Contact
+
+For any inquiries, feel free to reach out via:
+📧 utsavsinghal26@gmail.com (Project Admin, Utsav Singhal)
+
+---
+
+Thank you for visiting our Data Analysis section! I hope you find the insights and analyses intriguing and informative. 🚀

Data Analysis/Unemployment Analysis due to COVID/Readme.md

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+# 📊 Unemployment Analysis due to COVID
+
+## 🎯 Goal
+The goal of this project is to analyze the impact of the COVID-19 pandemic on unemployment rates across different states and regions in India. The purpose of this analysis is to identify the most affected states, observe the trends before and after lockdown periods, and gain insights into the economic repercussions of the pandemic.
+
+## 🧵 Dataset
+The dataset used in this project is titled "Unemployment in India," and it is sourced from Kaggle. The dataset provides comprehensive data on unemployment rates across India, segmented by states and regions during the COVID-19 pandemic.
+
+🔗 [Dataset link](https://www.kaggle.com/datasets/gokulrajkmv/unemployment-in-india)
+
+## 🧾 Description
+This project focuses on the analysis of unemployment rates in India during the COVID-19 pandemic. By comparing unemployment rates before and after the lockdown phases, this analysis seeks to uncover key insights into how different regions were impacted. Visualizations are used to understand patterns and trends in unemployment rates at both the state and region levels.
+
+## 🧮 What I had done!
+1. **Data Import and Cleaning**: Imported the dataset and performed necessary data cleaning such as handling missing values and formatting the dataset for analysis.
+2. **Exploratory Data Analysis (EDA)**: Conducted EDA to gain insights into the unemployment rate trends across different states and regions.
+3. **State-wise Analysis**: Grouped the data by states and calculated the mean unemployment rate for each state.
+4. **Region-wise Analysis**: Similarly grouped the data by regions to observe trends across different parts of India.
+5. **Lockdown Impact Analysis**: Divided the dataset into two periods: before lockdown and after lockdown. Compared the unemployment rates between these periods for various states.
+6. **Visualization**: Created insightful visualizations, such as bar graphs ,Pie charts and line plots, to illustrate unemployment trends and lockdown impacts.
+
+## 🚀 Models Implemented
+This project does not involve machine learning models as it focuses solely on data analysis and visualization.
+
+## 📚 Libraries Needed
+The following libraries were used in the project:
+- `pandas` – For data manipulation and analysis.
+- `numpy` – For numerical computations.
+- `matplotlib` – For static visualizations.
+- `seaborn` – For enhanced visualizations and styling.
+- `plotly` – For interactive plots and charts.
+
+## 📊 Exploratory Data Analysis Results
+### Unemployment Rate Before and After Lockdown by States
+![Unemployment Rate Before and After Lockdown by States](line_chart.png)
+
+
+### Estimated Unemployment Rate by Region
+![Estimated Unemployment Rate by Region](pie.png)
+
+*These visualizations highlight the unemployment trends across different states and regions, along with the effect of the COVID-19 lockdown on unemployment rates.*
+
+## 📈 Performance of the Models based on the Accuracy Scores
+Since this project is focused on data analysis and does not involve machine learning, model accuracy scores are not applicable.
+
+## 📢 Conclusion
+From this analysis, it is clear that the COVID-19 pandemic and the subsequent lockdown significantly impacted the unemployment rates across different states in India. States like **Puducherry, Jharkhand, Bihar, Haryana, and Tamil Nadu** were among the most severely affected. The lockdown period showed a noticeable increase in unemployment rates across the nation, with varying impacts in different regions. 
+
+This project provides valuable insights into the socio-economic impact of the pandemic and can be used as a reference for further studies.
+
+---
+
+Thanks :)