Key Components in Time Series Analysis

1.Trend Analysis

2.Data Visualizations

3.Stationary Testing

4.Seasoonality detection

5.Forecasting Models

6.Evaluation Using Metrics

First convert the time series data into Date time and year is most appeared case in time series analysis. Preparing Visualization with respect to time vs key feature in dataset. Observing the stationarity of the series using Acf , Pacf plots and checking trend and seasonality also involves in checking data is stationary or not .if its not stationary developing charts to understand its nature. Model building – AR, MA, ARMA and ARIMA and the final step is Extracting insights from prediction.