data.qmd

---
title: "Data"
---

{{< include _load-data.qmd >}}

Below we show metadata for the entire IRW, an example dataset, and illustrations of how to access the data programmatically. You can also explore the data [here](https://redivis.com/datasets/as2e-cv7jb41fd/tables).

## Metadata

<iframe width="800" height="500" allowfullscreen src="https://redivis.com/embed/tables/mikabr.irw:qa4k.metadata_output:vvkq#cells" style="border:0;"></iframe>


## Individual dataset


```{ojs}
summaries_map = new Map(Object.entries(summaries))
viewof dataset = Inputs.select(summaries_map, {label: 'Dataset'})

// Function to find the key that corresponds to the selected dataset
function findDatasetNameFromMap(map, selectedDataset) {
  for (let [key, value] of map.entries()) {
    if (value === selectedDataset) {
      return key; 
    }
  }
  return null;
}

// Look up the name of the dataset and set up the URL
dataset_name = findDatasetNameFromMap(summaries_map, dataset);
dataset_url = "https://redivis.com/embed/tables/datapages.item_response_warehouse:as2e:current." + dataset_name

html`<iframe id="myIframe" width="800" height="500" allowfullscreen style="border:0;" src = "${dataset_url}"></iframe>`
```

## Programmatic access

You can also access IRW data programmatically using the Redivis API for [R](https://apidocs.redivis.com/client-libraries/redivis-r) or [Python](https://apidocs.redivis.com/client-libraries/redivis-python) (**note** that you will first need to [generate and set an API token](https://apidocs.redivis.com/client-libraries/redivis-r/getting-started)). For example:

::: {.panel-tabset}
## R

```{r}
#| eval: false
#| echo: true

# first install redivis package: devtools::install_github("redivis/redivis-r", ref="main")

# individual dataset
dataset <- redivis::user("datapages")$dataset("item_response_warehouse")
df <- dataset$table("4thgrade_math_sirt")$to_tibble()

# metadata
project <- redivis::user("mikabr")$project("irw")
metadata <- project$table("metadata_output")$to_tibble()
```

## Python

```{python}
#| eval: false
#| echo: true
#| python.reticulate: false
import redivis

# individual dataset
dataset = redivis.user('datapages').dataset('item_response_warehouse')
df = dataset.table('4thgrade_math_sirt').to_pandas_dataframe()

# metadata
project = redivis.user('mikabr').project('irw')
metadata = project.table('metadata_output').to_pandas_dataframe()
```
:::