Data
Historical-Weather-data-of-Goa-India

Historical-Weather-data-of-Goa-India

active ARFF Database: Open Database, Contents: Database Contents Visibility: public Uploaded 23-03-2022 by Dustin Carrion
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Context I am currently building a short term (one-day ahead) electric load forecasting model for Goa. A good chunk of it is domestic household load. Temperature and Humidity can be used to estimate the heat index which can be used as one of the input variables for the model. Hence, future temperature and humidity predictions are essential. Content Contains following data from 01 July'16 - 31 July'19 with 15 minute resolution Temperature (K);Temperature at 2 m above ground Relative humidity ();Relative humidity at 2 m above ground Pressure (hPa);Pressure at ground level Wind speed (m/s);Wind speed at 10 m above ground Wind direction (deg);Wind direction at 10 m above ground (0 means from North 90 from East) Rainfall (kg/m2);Rainfall mass density per m2 area Short-wave irradiation (Wh/m2);Surface incoming shortwave irradiation (broadband) Acknowledgements Data downloaded from: http://www.soda-pro.com/web-services/meteo-data/merra Provider: National Aeronautics and Space Administration (NASA) / Goddard Space Flight Center More information at; http://gmao.gsfc.nasa.gov/reanalysis/MERRA-2 Licenses: http://www.soda-pro.com/documents/10157/326300/CAMS-data-license.pdf http://www.soda-pro.com/documents/10157/326300/SoDa-license.pdf Inspiration Future prediction of humidity and temperature using the available past data.

9 features

Datestring1126 unique values
0 missing
UT_timestring97 unique values
0 missing
Temperature_(K)numeric1627 unique values
0 missing
Relative_Humidity_(%)numeric6830 unique values
0 missing
Pressure_(hPa)numeric1708 unique values
0 missing
Wind_speed_(m/s)numeric1000 unique values
0 missing
Wind_directionnumeric28793 unique values
0 missing
Rainfall_(kg/m2)numeric48561 unique values
0 missing
Short-wave_irradiation_(Wh/m2)numeric54542 unique values
0 missing

19 properties

108096
Number of instances (rows) of the dataset.
9
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
7
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
Average class difference between consecutive instances.
77.78
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

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