need a solution in python using Python machine learning libraries to analyze a Time Series data - The solution should be in Python Should analyze the time series signal for seasonality, trends, cyclical and irregular components Should identify noise and find techniques to separate noise from the time series data Should identify whether the time series data is stationary or not Should validate if the time series data can be used for forecasting future values Should leverage any smoothing techniques to make sure the signal is good enough for forecasting Create new data suitable for forecasting the future signals in case if the signal as such is not valid to forecast. Note: you have to include all the points listed above

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