To include all the seasonality and trend columns, in the Forecast results line items:
- Select Map on names or codes.
- Select the Time tab and select Dates.
Ensure that the date format is Y-M-D. - Select Run import.
This screenshot shows the CSV file when you include all columns of seasonal trends. It also shows the timestamp.
The dropdown option Everyone is selected for the Default File.
In most cases, we recommend you select Everyone for the Set Default File. For more information see Private and shared imports.
This is an example of how mapping looks.
Optionally, add the following columns to include seasonal trends.
Note: Seasonality helps you spot demand spikes for regular time intervals. For example, if your daily data has a weekly seasonal pattern, you can view this with the data in the PlanIQ_Seasonality_Weekly line item.
You can use PlanIQ_Trend_Quarterly and PlanIQ_Trend_Yearly to discover trends over a broader period of time. Trend is calculated quarterly or yearly. It's useful to view the current trendline as well as to spot changes in a trend. The quarterly or yearly trends only display if there's enough data to generate them.
We recommend you include these column headers, so you can clearly identify patterns over time.
Mapping
The example below includes all seasonality columns.
| Source | Target |
| Column 1: timestamp | Time |
| Column 2: item_id | Item_id |
| Column 3: forecast_action | [If you decide to map the forecast action, map it to the forecast_action_name dimension in your forecast results module.] |
| Column 4: P1 | |
| Column 5: P2 | |
| Column 6: P3 | |
| Column 7: PlanIQ_Seasonality_Weekly | |
| Column 8: PlanIQ_Seasonality_Bi_weekly | |
| Column 9: PlanIQ_Seasonality_Monthly | |
| Column 10: PlanIQ_Seasonality_Quarterly | |
| Column 11: PlanIQ_Seasonality_Yearly | |
| Column 12: PlanIQ_Trend_Quarterly | |
| Column 13: PlanIQ_Trend_Yearly |