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Australia Climate Forecasting Data
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About
This dataset provides a detailed collection of daily weather observations across various locations in Australia, spanning approximately 10 years. Its primary purpose is to facilitate the development of predictive classifiers, specifically to forecast the likelihood of rain on the following day, denoted by the 'RainTomorrow' variable. It serves as a foundational resource for data mining efforts focused on weather pattern analysis and future precipitation predictions.
Columns
- row ID: A unique identifier for each observation record.
- Location: The name of the city in Australia where the observation was made.
- MinTemp: The minimum temperature recorded during a particular day, measured in degrees Celsius.
- MaxTemp: The maximum temperature recorded during a particular day, measured in degrees Celsius.
- Rainfall: The amount of rainfall observed during a particular day, measured in millimetres.
- Evaporation: The amount of evaporation during a particular day, measured in millimetres.
- Sunshine: The duration of bright sunshine during a particular day, measured in hours.
- WindGustDir: The direction from which the strongest wind gust blew during a particular day, represented by 16 compass points.
- WindGustSpeed: The speed of the strongest wind gust during a particular day, measured in kilometres per hour.
- WindDir9am: The direction of the wind for 10 minutes prior to 9 am, represented by compass points.
- WindDir3pm: The direction of the wind for 10 minutes prior to 3 pm, represented by compass points.
- WindSpeed9am: The speed of the wind for 10 minutes prior to 9 am, measured in kilometres per hour.
- WindSpeed3pm: The speed of the wind for 10 minutes prior to 3 pm, measured in kilometres per hour.
- Humidity9am: The humidity level at 9 am, expressed as a percentage.
- Humidity3pm: The humidity level at 3 pm, expressed as a percentage.
- Pressure9am: The atmospheric pressure at 9 am, measured in hectopascals.
- Pressure3pm: The atmospheric pressure at 3 pm, measured in hectopascals.
- Cloud9am: The proportion of the sky obscured by clouds at 9 am, measured in eighths.
- Cloud3pm: The proportion of the sky obscured by clouds at 3 pm, measured in eighths.
- Temp9am: The temperature at 9 am, measured in degrees Celsius.
- Temp3pm: The temperature at 3 pm, measured in degrees Celsius.
- RainToday: A binary indicator ('Yes' or 'No') specifying if rain occurred on the observation day.
- RainTomorrow: A binary target variable (1 for 'Yes', 0 for 'No') indicating if rain is expected on the following day.
Distribution
The dataset is typically provided in CSV format, with a sample file named
Weather Test Data.csv approximately 4.24 MB in size. It contains 22 columns and includes 42,677 unique observation records. Some columns like Evaporation, Sunshine, Pressure9am, Pressure3pm, Cloud9am, and Cloud3pm have a noticeable percentage of missing values.Usage
This dataset is ideal for:
- Developing and evaluating machine learning models for weather prediction.
- Building predictive classifiers to forecast next-day rain.
- Conducting research in atmospheric science and meteorology.
- Supporting agricultural planning and decision-making based on weather forecasts.
- Analysing climate patterns and trends in Australia.
- Educational purposes, particularly in data mining and classification tasks.
Coverage
The dataset covers daily weather observations from numerous locations across Australia. It spans a time range of approximately 10 years. There is no specific demographic scope as it pertains to environmental data. While most columns are well-populated, certain weather variables such as evaporation, sunshine, and cloud cover at specific times of the day have a number of missing entries.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For building and refining predictive models for rain forecasting.
- Researchers: In fields such as meteorology, climate science, and environmental studies for in-depth analysis of Australian weather patterns.
- Agricultural Planners: To inform irrigation schedules, planting, and harvesting decisions.
- Educators and Students: As a practical case study for machine learning, data analysis, and statistical modelling.
Dataset Name Suggestions
- Australia Daily Weather Observations
- Australian Rain Prediction Dataset
- Australia Climate Forecasting Data
- Next-Day Rain in Australia
- Australian Weather Forecasting Records
Attributes
Original Data Source:Australia Climate Forecasting Data
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