yash22222 / analysis-of-amcat-aspiring-minds

Analyzing employment outcomes for engineering graduates based on a provided dataset. Specifically, it aims to verify a claim regarding the salary range for fresh graduates in certain engineering roles and investigate potential relationships between gender and specialization preferences.

Engineering Graduates Employment Analysis

Analyzing employment outcomes for engineering graduates based on a provided dataset. Specifically, it aims to verify a claim regarding the salary range for fresh graduates in certain engineering roles and investigate potential relationships between gender and specialization preferences.

Overview

This project aims to analyze employment outcomes for engineering graduates using Python. The dataset contains information on salaries, job titles, gender, specialization, and other relevant variables. The analysis focuses on verifying claims regarding salary ranges for specific engineering roles and investigating potential relationships between gender and specialization preferences. Insights gained from this analysis can inform decision-making processes in the engineering industry and contribute to promoting diversity and inclusion.

Dataset

The dataset used for this analysis is sourced from Aspiring Minds Employment Outcome 2015 (AMEO). It contains around 40 independent variables and 4000 data points, primarily limited to students with engineering disciplines. The variables include continuous and categorical features such as salary, job titles, gender, specialization, College CGPA, and more.

Analysis Steps

1. Introduction: Provides a detailed overview of the dataset and project objectives.
2. Data Import and Description: Loads the dataset, displays its head, and shape, and describes the data.
3. Univariate Analysis: Conducts exploratory analysis on individual variables, including histograms, boxplots, and countplots.
4. Bivariate Analysis: Explores relationships between variables using scatter plots, bar plots, and stacked bar plots.
5. Research Questions: Investigate specific research questions related to salary claims and gender-specialization relationships.
6. Conclusion: Summarizes key findings and insights from the analysis.
7. Bonus: Proposes additional research questions for further exploration.

Getting Started

To run the analysis:

1. Clone the repository:

   git clone https://github.com/Yash22222/ANALYSIS-OF-AMCAT-ASPIRING-MINDS.git

2. Install the required dependencies:

   pip install -r requirements.txt

3. Run the Jupyter Notebook:

   jupyter notebook AMCAT_ANALYSIS.ipynb

Contributors

• Yash Ashok Shirsath

License

This project is licensed under the .

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