This repository contains meteorological data collected from three different weather stations. The data is stored in two CSV files, each representing a different set of measurements:

1. all_data_with_pressure.csv
2. all_data_without_pressure.csv

Description of the Data

Common Data Fields

Both CSV files contain the following common fields:

• EUI: Unique identifier for the weather station.
• Latitude: Geographic latitude of the weather station.
• Longitude: Geographic longitude of the weather station.
• Month: Month when the data was recorded.
• Daytime_hour: Hour of the day when the data was recorded.
• Temperature: Temperature recorded at the specified hour.
• Humidity: Humidity percentage recorded at the specified hour.
• Solar_irradiation: Solar irradiation measured at the specified hour.

Differences Between the Files

• all_data_with_pressure.csv: This file includes an additional field:

  • Pressure: Atmospheric pressure recorded at the specified hour (in Pascals).

• all_data_without_pressure.csv: This file does not include the pressure field.

Weather Stations Used

The data was collected from the following three weather stations:

1. Decentlab DL-ATM41

2. UBIQ WS-100

3. MeteoHelix IoT Pro

Technical Documentation

Detailed technical information and specifications for each weather station can be found in the manufacturer's web pages:

• Decentlab-DL-ATM41-datasheet.pdf
• UBIQ Weather Station.pdf
• MeteoHelix+IoT+Pro+DataSheet.pdf

These datasheets provide comprehensive details about the sensors, measurement capabilities, and technical specifications of each weather station.

Usage

These datasets can be used for various meteorological analyses, such as studying temperature trends, humidity variations, and solar radiation patterns. The additional pressure data in all_data_with_pressure.csv allows for more comprehensive atmospheric studies.

Example Usage

To load and explore the data in Python, you can use the following code snippet:

import pandas as pd

# Load the CSV files
data_with_pressure = pd.read_csv('path/to/all_data_with_pressure.csv')
data_without_pressure = pd.read_csv('path/to/all_data_without_pressure.csv')

# Display the first few rows of each dataframe
print(data_with_pressure.head())
print(data_without_pressure.head())

For any questions or further information, please contact [josip.spisic@ferit.hr].