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Rainfall-prediction-in-Australia

Rain in Australia

Description

This dataset contains daily weather observations from numerous Australian weather stations.

Features description

Date---The date of observation

Location---The common name of the location of the weather station

MinTemp---The minimum temperature in degrees celsius

MaxTemp---The maximum temperature in degrees celsius

Rainfall---The amount of rainfall recorded for the day in mm

Evaporation---The so-called Class A pan evaporation (mm) in the 24 hours to 9am

Sunshine---The number of hours of bright sunshine in the day.

WindGustDir---The direction of the strongest wind gust in the 24 hours to midnight

WindGustSpeed---The speed (km/h) of the strongest wind gust in the 24 hours to midnight

WindDir9am---Direction of the wind at 9am

WindDir3pm---Direction of the wind at 3pm

WindSpeed9am---Wind speed (km/hr) averaged over 10 minutes prior to 9am

WindSpeed3pm---Wind speed (km/hr) averaged over 10 minutes prior to 3pm

Humidity9am---Humidity (percent) at 9am

Humidity3pm---Humidity (percent) at 3pm

Pressure9am---Atmospheric pressure (hpa) reduced to mean sea level at 9am

Pressure3pm---Atmospheric pressure (hpa) reduced to mean sea level at 3pm

Cloud9am---Fraction of sky obscured by cloud at 9am. This is measured in "oktas", which are a unit of eigths. It records how many eigths of the sky are obscured by cloud. A 0 measure indicates completely clear sky whilst an 8 indicates that it is completely overcast.

Cloud3pm---Fraction of sky obscured by cloud (in "oktas": eighths) at 3pm. See Cload9am for a description of the values

Temp9am---Temperature (degrees C) at 9am

Temp3pm---Temperature (degrees C) at 3pm

RainToday---Boolean: 1 if precipitation (mm) in the 24 hours to 9am exceeds 1mm, otherwise 0

RISK_MM---The amount of next day rain in mm. Used to create response variable RainTomorrow. A kind of measure of the "risk".

RainTomorrow---The target variable. Did it rain tomorrow? References This total dataset is taken from following kaggle reference.

https://www.kaggle.com/jsphyg/weather-dataset-rattle-package

Source & Acknowledgements

Observations were drawn from numerous weather stations. The daily observations are available from http://www.bom.gov.au/climate/data. Copyright Commonwealth of Australia 2010, Bureau of Meteorology.

Definitions adapted from http://www.bom.gov.au/climate/dwo/IDCJDW0000.shtml

This dataset is also available via the R package rattle.data and at https://rattle.togaware.com/weatherAUS.csv. Package home page: http://rattle.togaware.com. Data source: http://www.bom.gov.au/climate/dwo/ and http://www.bom.gov.au/climate/data.

And to see some great examples of how to use this data: https://togaware.com/onepager/

Objective

Predict whether or not it will rain tomorrow by training a binary classification model on target RainTomorrow.

The target variable RainTomorrow means: Did it rain the next day? Yes or No.

About

This is the code example that I have explained in this blog https://medium.com/@pothabattula.kumar

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