ibrahim-talib-ds/tanzania-weather-analysis-2025

📊 Comprehensive analysis of Tanzania's 2025 hourly weather data using Pandas. Explores temperature patterns, humidity trends, wind speed distributions, and weather conditions through statistical analysis, filtering, and grouping techniques. Perfect for learning data analysis with real-world time-series weather data. # 🌤️ Tanzania Weather Data Analysis (2025) ## 📋 Overview This project provides a comprehensive analysis of hourly weather data across Tanzania for the year 2025. Using **Pandas DataFrame**, we uncover regional weather patterns, statistical insights, and seasonal trends from the Tanzania Weather Dataset. ### 📊 Dataset Information - **Time Period**: January 1, 2025 - December 31, 2025 - **Records**: 365 hourly observations - **Features**: 8 weather parameters | Column | Description | Data Type | |--------|-------------|-----------| | Date/Time | Timestamp of observation | String | | Temp_C | Temperature in Celsius | float64 | | DewPoint_TempC | Dew point temperature | float64 | | Relative_Humidity | Humidity percentage | int64 | | Wind_Speed_km/h | Wind speed in km/h | int64 | | Visibility_Km | Visibility in kilometers | int64 | | Pressure_kPa | Atmospheric pressure | float64 | | Weather_Condition | Weather condition type | String | --- ## 🛠️ Pandas Techniques Demonstrated This project implements the following Pandas operations: | Technique | Method | Purpose | |-----------|--------|---------| | Unique Values | `.unique()` / `.nunique()` | Find distinct values in columns | | Value Counting | `.value_counts()` | Get frequency distribution | | Filtering | Boolean indexing | Select rows by conditions | | Grouping | `.groupby()` | Aggregate data by categories | | Group Access | `.get_group()` | Extract specific groups | | Null Detection | `.isnull()` / `.notnull()` | Identify missing values | | Column Renaming | `.rename()` | Modify column names | | Statistics | `.mean()`, `.std()`, `.var()` | Calculate statistical measures | | String Methods | `.str.contains()` | Pattern matching in text | | Logical Operators | `&` (AND), `\|` (OR) | Combine multiple conditions | | Range Analysis | `.min()`, `.max()` | Find extreme values | --- ## 📈 Key Findings ### Weather Condition Distribution