Assessment of Factors That Drive Entrepreneurship Among Women in Sunyani

This project explores the key factors influencing women's entrepreneurship in Sunyani, Ghana. Using survey data and statistical analysis for a beta testing by the author, it aims to provide insights into the challenges and opportunities women face in entrepreneurial ventures within this context.

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Table of Contents

• Project Overview
• Features
• Technologies Used
• Dataset
• Setup and Installation
• How to Use
• Project Structure
• Deployment
• Acknowledgments

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Project Overview

This project is part of a study on women's entrepreneurship in Sunyani. It investigates various factors such as:

• Access to financial resources,
• Business training and mentorship,
• Socio-cultural norms and biases,
• Challenges with market opportunities, and
• Motivations like financial independence and self-reliance.

By analyzing these factors, the project aims to provide actionable recommendations to policymakers, educators, and stakeholders to foster a more inclusive entrepreneurial environment.

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Features

• Descriptive Statistics: Provides an overview of the dataset.
• Data Visualization: Graphical representation of key findings using Python libraries.
• Insights: Highlights the most influential factors driving entrepreneurship among women.
• Scalability: Can be adapted to other regions or sectors.

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Technologies Used

The project leverages the following tools and technologies:

• Python (pandas, matplotlib, seaborn, Streamlit)
• Jupyter Notebook
• Excel for data preparation and cleaning
• Git for version control
• Anaconda for environment management

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Dataset

The dataset contains responses to a survey conducted among women entrepreneurs in Sunyani. Key fields include:

• Demographics: Age, educational background, marital status, number of children.
• Experience: Years as an entrepreneur, prior business experience, formal training.
• Challenges: Access to credit, socio-cultural barriers, market opportunities.
• Motivations: Financial independence, passion for the industry, family support.

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Setup and Installation

Follow these steps to set up the project on your local machine:

1. Clone the Repository:

   git clone https://github.com/Ionkansah/Women-Entrepreneurship-Awareness-Project
   

2. Navigate to the Project Directory

     cd https://github.com/Ionkansah/Women-Entrepreneurship-Awareness
   

3. Set Up the Virtual Environment: Install Anaconda. Create an environment:

     conda create -n data-science-env python=3.9
     conda activate data-science-env
   

4. Install Dependencies:

     pip install pandas matplotlib seaborn streamlit
   

How to Use

a. Open the Jupyter Notebook file: jupyter lab

b. Run the notebook step-by-step to analyze the data. To deploy the project using Streamlit:

  streamlit run app.py

Project Structure

project/ │ ├── data/ │ ├── survey_data.csv # Raw data file │ └── cleaned_data.csv # Processed data file │ ├── notebooks/ │ └── analysis.ipynb # Jupyter Notebook for data analysis │ ├── app.py # Streamlit application file ├── README.md # Project documentation ├── .gitignore # Files and directories to ignore ├── requirements.txt # Python dependencies └── LICENSE # Project license

Deployment

The project is designed to be deployed using Streamlit. You can deploy it locally or on a platform like Streamlit Cloud.

Acknowledgments

This project was made possible with the following: Respondents who shared valuable insights through the survey. Guidance from mentors and collaborators in the field of data science. Open-source libraries and tools that power the analysis and visualization. Author: Isaac's Projects Consulting For inquiries, please contact [isaac3g@outlook.com].