mijuuhailu/african-climate-trend

### 🌍 Climate Data Analysis using NASA POWER Dataset ## Project Overview This project presents a comprehensive data profiling, cleaning, and exploratory data analysis (EDA) of climate data obtained from the NASA Prediction Of Worldwide Energy Resources database. The dataset contains daily meteorological observations for five African countries: Ethiopia Kenya Sudan Tanzania Nigeria covering the period January 2015 to March 2026. The primary goal is to transform raw satellite-derived climate data into a clean and structured format, and to extract meaningful insights related to temperature, precipitation, humidity, and wind patterns. ## Objectives Perform data cleaning and preprocessing (handling missing values, duplicates, and outliers) Convert raw time variables into proper datetime format Conduct exploratory data analysis (EDA) to identify trends and patterns Analyze seasonal variations in temperature and rainfall Examine relationships between key climate variables Prepare datasets for future predictive modeling ## Dataset Description Each dataset contains daily observations with the following key variables: Column Description YEAR Year of observation DOY Day of year (converted to date during preprocessing) T2M Mean temperature (°C) T2M_MAX Maximum temperature (°C) T2M_MIN Minimum temperature (°C) T2M_RANGE Temperature range (°C) PRECTOTCORR Precipitation (mm/day) RH2M Relative humidity (%) WS2M Wind speed (m/s) WS2M_MAX Maximum wind speed (m/s) PS Surface pressure (kPa) QV2M Specific humidity (g/kg) ## Methodology # 1. Data Cleaning Replaced -999 with NaN Removed duplicate records Handled missing values using forward-fill and row filtering Converted YEAR and DOY into a proper datetime column Extracted monthly features for seasonal analysis # 2. Exploratory Data Analysis (EDA) - Time Series Analysis Monthly average temperature trends Monthly total precipitation patterns Identification of seasonal cycl …