# Add extra data like weather or prices

> For AI agents: the complete documentation index is at
> [https://docs.retrocast.com/llms.txt](https://docs.retrocast.com/llms.txt) — every page is also available as
> markdown by appending `.md` to its URL.

Other series affect your target: weather, promotions, prices. They usually
live in a separate table. `covariates` attaches that table to your input and
matches its rows to yours by key, so you don't have to join them yourself:

```json
{
  "input": {
    "source": {
      "inline": {
        "date":  ["2024-01-01", "2024-01-02", "2024-01-03"],
        "sales": [142, 137, 145]
      }
    },
    "columns": {
      "date":  { "kind": "time", "frequency": "1d" },
      "sales": { "kind": "target" }
    },
    "covariates": [
      {
        "schema": {
          "version": "0.3",
          "source": {
            "inline": {
              "date":        ["2024-01-01", "2024-01-02", "2024-01-03"],
              "temperature": [4.5, 3.1, 6.0]
            }
          },
          "columns": {
            "date":        { "kind": "time", "frequency": "1d" },
            "temperature": "historical"
          }
        },
        "on": [{ "base": "date", "attached": "date" }]
      }
    ]
  },
  "prediction_length": "1w"
}
```

Post it to `https://api.retrocast.com/v1-beta/forecast?model=t0-alpha`.
`model` names the forecasting model and is required — without it the
request is rejected with `missing field "model"`.

`on` lists the columns to match on — here the base `date` against the
attached `date`. `temperature` then behaves like a column of the base
series.

Two things to watch:

- `on: []` matches every attached row to every base row.
- Leaving `on` out is not the same as `on: []`. The request is rejected, so
  always list the pairs.

Use `only` to keep a subset of the attached columns, or `rename` to rename
them.

Each extra table stays where it is. Attach weather, prices and promotions
separately instead of maintaining one wide pre-joined table.

## What comes back

Only your targets. The attached columns change the forecast but are not
echoed back:

```json
{
  "data": {
    "time":      ["2024-01-04T00:00:00Z", "2024-01-05T00:00:00Z"],
    "cutoff":    ["2024-01-03T00:00:00Z", "2024-01-03T00:00:00Z"],
    "lead_time": ["PT0S", "P1D"],
    "span":      ["P1D", "P1D"],
    "identifiers": {},
    "targets": {
      "sales": {
        "quantiles": {
          "0.1":  [137.6, 137.5],
          "0.5":  [141.0, 140.5],
          "0.9":  [147.4, 146.1],
          "mean": [141.6, 141.0]
        }
      }
    }
  }
}
```

There is no `temperature` entry — it was an input, not something to
forecast. To get a forecast for it too, make it a column of your base series
with the `"target"` kind instead. See
[Forecast several columns at once](/api-v1/contents/cookbook/multiple-targets).