mbencherif / time-series-analysis-python Goto Github PK

The Problem:

The specific problem in this project is about the time-series data trend prediction. The specific application scenario is in e-commerce. You are given a real dataset obtained from a real-world e-commerce application where there were 1000 products and 31490 customers (i.e., buyers) who bought these products. Of these 1000 products there are 100 key products (popular products). Also these 1000 products are in 15 categories. The specific data are given in the seven files and the specific details of these files are given below. The time window of this dataset is in 118 days with data documentation for each day. Hence, the time unit is one day where the timeline goes from the 0-th day to the 117-th day (17 weeks less one day in total). Now you are asked to do the sale quantity prediction for the 100 key products for each day between the 118-th day and the 146-th day (29 days).



- Python version used - 2.7.11.Pandas,Numpy and Matplotlib are the libraries used in the project.
- Specify the path of "product_distribution_training_set.txt" in the variable path.
- Uncomment certain portions of code to check for plot graphs.
- ARIMA has been used for analyzing and forecasting time series data.
- The "output.txt" file has the output matrix with the prediction results.It is created in the 
  same directory where the project resides.