README.md

metadata

dataset_info:
  features:
    - name: Temperature
      dtype: float64
    - name: Humidity
      dtype: float64
    - name: Wind_Speed
      dtype: float64
    - name: Cloud_Cover
      dtype: float64
    - name: Pressure
      dtype: float64
    - name: Rain
      dtype: string
  splits:
    - name: train
      num_bytes: 126558
      num_examples: 2500
  download_size: 120963
  dataset_size: 126558
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Weather Forecast Dataset

Description

This dataset contains weather-related data collected for forecasting purposes. It includes various meteorological parameters that can be used for climate analysis, weather prediction models, and machine learning applications in forecasting.

Dataset Details

Columns:

• Temperature: Measured in degrees Celsius.
• Humidity: Percentage of atmospheric humidity.
• Wind_Speed: Speed of wind in meters per second.
• Cloud_Cover: Percentage of sky covered by clouds.
• Pressure: Atmospheric pressure in hPa (hectopascal).
• Rain: Categorical label indicating whether it rained (rain) or not (no rain).

Notes:

• The dataset contains 2,500 entries.
• The Rain column is categorical, making it useful for classification models.
• This dataset can be used for time-series analysis and supervised learning tasks.

Use Cases

• Predicting rainfall using meteorological data.
• Weather forecasting using machine learning models.
• Studying correlations between temperature, humidity, and pressure.

How to Use

You can load the dataset using the datasets library:

from datasets import load_dataset

dataset = load_dataset("Tarakeshwaran/Hackathon_Weather_Forcast")
print(dataset)