ASSIGNMENT INSTRUCTIONS Need To Create a solution to forecast the account payables using ARIMA, SARIMA and FBProphet 1. The solution should be in Python 2. The solution should use the Account Payables data available at https://data.oxnard.org/Financial-Data-and-Reports/Accounts-Payable-Transactions/ay6a-gmt6/ about_data 3.The solution should analyze the time series signal for seasonality, trends, cyclical and irregular components. 4.The solution should identify noise and find techniques to separate noise from the time series data. 5.The solution should identify whether the time series data is stationary or not. 6.The solution should validate if the time series data can be used for forecasting future values. 7.The solution leverages any smoothing techniques to make sure the signal is good enough for forecasting. 8.Create new data suitable for forecasting the future signals in case the signal as such is not valid to forecast. 9. Split the data into Train data and Test data; Predict values for Test data; Compare the predicted values with the actual values. 10. Create plots showing analysis of time signal, train data, test data and predicted data; plot showing train and test data in different colors; plot showing predicted and test data values with different colors;

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