Pesticide-Related Opportunity-Challenge Data Analysis

This project analyzes open-ended responses collected from companies regarding pesticide use. The data originates from an EU-supported study focused on agricultural practices and sustainability.

Purpose

To identify and categorize firms' perceptions related to pesticide use — including opportunities, challenges, impacts, and suggestions — and visualize these using basic data analysis techniques.

Contents

• firsat_zorluk_analizi.ipynb: Jupyter Notebook containing all analysis steps
• AB-VERI-DUZENLENMISS.csv: Dataset with qualitative responses from companies
• Frequency tables and visualizations (bar chart, heatmap)
• A keyword-based classifier for automatic tagging into 4 categories:
  • Opportunity
  • Challenge
  • Impact
  • Suggestion

Libraries Used

• pandas
• matplotlib
• seaborn

How to Use

1. Install the required libraries:

pip install pandas matplotlib seaborn
# pesticide-opportunity-challenge-analysis