Implementation of Exploratory Data Analysis on Weather Data

This paper presents the Exploratory Data Analysis on the climate data of the city of Mumbai. The climate variables are closely associated with each other. Exploratory Data Analysis helps to understand the data in a better way so that the predictions of any particular weather phenomenon are done prop...

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Bibliographic Details
Published in:	2023 International Conference on Communication System, Computing and IT Applications (CSCITA) pp. 21 - 25
Main Authors:	Adivarekar, Sahil, Nanwani, Shruti, Mandal, Nabanita, Sarode, Tanuja
Format:	Conference Proceeding
Language:	English
Published:	IEEE 31-03-2023
Subjects:	Climate Data analysis EDA Heat engines Histograms Loss Function Mean square error methods Random Forest Standardization Urban areas Visualization Weather
Online Access:	Get full text
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Summary:	This paper presents the Exploratory Data Analysis on the climate data of the city of Mumbai. The climate variables are closely associated with each other. Exploratory Data Analysis helps to understand the data in a better way so that the predictions of any particular weather phenomenon are done properly. Random forest has been used to for prediction. Standardization and Normalization has been used and the results are shown. The validation techniques used are Mean Square Error, Root Mean Square Error and Mean Absolute Error.
DOI:	10.1109/CSCITA55725.2023.10104864