reshma78611/Forecasting-using-Python

Forecasting using Python

Forecasting

Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends.

Forecasting methods:-

1. If there are no data available, or if the data available are not relevant to the forecasts, then qualitative forecasting methods must be used.
2. Quantitative forecasting can be applied when two conditions are satisfied:
   a) numerical information about the past is available
   b) it is reasonable to assume that some aspects of the past patterns will continue into the future.

Forecasting model building methods:-

1. Linear model
2. Exponential model
3. Quadratic model
4. Additive seasonality
5. Additive seasonality with quadratic trend
6. Multiplicative Seasonality

Data Used :

          Airlines dataset :- Forecast the passengers in the airlines depending on past and present data
          Coca cola sales raw dataset : Forecast cococola sales depending on past and present data
          Plastic sales dataset : Forecast sales of plastic depending on past and present data
          Amtrak dataset: Forecast Ridership depending on past and present data
          Footfalls: Forecast the number of foot falls depending on past and present data

Programming:-

              Python

The Codes regarding Forecasting to Forecast the passengers in the airlines with airlines dataset,Forecast cococola sales with cococola sales dataset, Forecast sales of plastic with plastic sales dataset,Forecast Ridership with Amtrak dataset and Forecast the number of foot falls with footfalls dataset are present in this Repository in detail.