This paper is based on data analysis by python programming language code, data executed on google collaborator platform associated with the study of ground water level, data collected from the site of WRIS, “INDIA WATER RESOURCES INFORMATION SYSYEM”. From the site searching for ground water level data, the historical data since 1990 to recent past as available there was collected for data analysis. The data collected was of different stations, different districts under the state Orissa as available there and also data with different data type, either manual observation or GPRS data. All these collected data files were then merged into one single file, data from 1990 to 2024. The rows with GPRS observational data were discarded, on account of considering only the manual observational data for analysis, otherwise analysis could generate error having problem of data divergence. Then created one new data column with year wise average value for ground water level data. All the locations of observation as collected were considered as same location for the purpose of having sufficient large data set without any missing year as well as the reason behind that all locations are in the same state Orissa and so could be considered as same data source. The main objective of data analysis was to monitor year wise change of average value of level of ground water for Orissa state. Apart from this study another aim was to determine the trend of yearly average value of ground water level of Orissa for future few years by neural network model. Visualization by bar plot was made to get insights of status of annual average of ground level water for the state Orissa along with future trend for few years.