This paper is based on data analysis by python programming language on google collaborator platform, model used as recurrent neural network, to predict the seasonal rainfall total during monsoon season ,for near future years for the period June to September. Other than prediction of seasonal total rainfall for future years ,a study with data analysis in python had been done also for understanding  the deviation of seasonal total for meteorological monsoon season in comparison with historical record of normal. The source of data is online data collection platform ‘INDIA METEOROLOGICAL DEPARTMENT, PUNE’. The surface data for Alipore (42807) as available there, had been collected in csv file format, then uploading the csv file in google collaborator platform, executed analysis by python recurrent neural network model technique, in keras, tensorflow environment to get the predicted output for future years for the dependent variable, in this study which was ‘total seasonal rainfall’ within meteorological monsoon period. Trend of deviation of rainfall seasonal total for the meteorological monsoon season, in comparison with recorded normal  data of the same was also studied since historical period, 1969 to present years, along with trend of deviation of the same for predicted future value for future years. One new column was created to define derived data for year wise seasonal total for meteorological monsoon season and performed the data analysis to find the result. From analysis of big data, determined predicted output for monsoon period seasonal total rainfall for near future which is the span of 2025 to 2030, with the help of recurrent neural network, with train-test split ratio 80%-20% and minimum loss.