# Weather Data Analysis Using OpenWeather API
## Project Overview
This project retrieves real-time weather data for selected Nigerian cities using the OpenWeather API. The data is processed with Python, converted into a Pandas DataFrame, exported as a CSV file, and analyzed to identify weather patterns.
## Objectives
- Retrieve weather data from the OpenWeather API.
- Store the data in a Pandas DataFrame.
- Export the data to a CSV file.
- Perform basic weather analysis.
## Technologies Used
- Python
- Pandas
- Requests
- OpenWeather API
- Jupyter Notebook
## Cities Analyzed
- Lagos
- Abuja
- Kano
- Port Harcourt
- Ibadan
## Data Collected
The dataset includes:
- City
- Temperature (°C)
- Humidity (%)
- Weather Condition
- Wind Speed (m/s)
- Date & Time
## Basic Analysis
The project includes:
- Temperature comparison across cities.
- Identification of the city with the highest humidity.
- Comparison of weather conditions.
- Comparison of wind speed across cities.
- Calculation of the average temperature.
## Output
- Weather dataset exported as `weather_data.csv`
- Basic analysis and insights displayed in the Jupyter Notebook.
## Author
Fathiat Sulaimon