Uwaseanitha10/FINAL_EXAM_PROJECT-agricultural-and-rural-development-rwanda

# FINAL_EXAM_PROJECT-agricultural-and-rural-development-rwanda ## Project Title: Agricultural and Rural Development Analysis - Rwanda ## Prepared by: Uwase Anitha ## ID: 26945 ### 📊 Project Overview This capstone project uses Big Data Analytics and Visualization to explore the state of agriculture and rural development in Rwanda. By applying Python for data cleaning, exploratory analysis, and clustering models, we uncover key trends in land use, rural electrification, crop production, and population indicators. The findings are presented in an interactive Power BI dashboard, enabling stakeholders to explore insights and development phases visually. Dataset Dataset used: Agricultural and Rural Development - Rwanda Source: data.humdata.org File location: C:/Users/HP/Desktop/agriculture_features_final.csv ### running the codes using jupyter notebook source:localhost ## Data Processing Loaded dataset into Jupyter Notebook code ``` STEP 1: Import libraries import pandas as pd import numpy as np import os # STEP 2: Define correct file path file_path = "C:/Users/HP/Downloads/agriculture-and-rural-development_rwa.csv" # STEP 3: Load the dataset df = pd.read_csv(file_path) print("✅ Loaded successfully! Shape:", df.shape) df.head() ``` ### screensshot of data loading ### Cleaned missing values and handled duplicates codes ``` Check missing values print("Missing values per column:") print(df.isnull().sum()) df = df.dropna(thresh=len(df.columns) - 2) df = df.dropna() print("✅ Shape after removing missing data:", df.shape) df.head() ``` ### screenshot that remove missing values ### Transformed and pivoted data for analysis codes ``` Convert 'Value' to numeric to fix pivot error df['Value'] = pd.to_numeric(df['Value'], errors='coerce') # Pivot: years as rows, indicators as columns df_pivot = df.pivot_table(index='Year', columns='Indicato …