arize-dataset

# Arize Dataset Skill

## Concepts

- **Dataset** = a versioned collection of examples used for evaluation and experimentation
- **Dataset Version** = a snapshot of a dataset at a point in time; updates can be in-place or create a new version
- **Example** = a single record in a dataset with arbitrary user-defined fields (e.g., `question`, `answer`, `context`)
- **Space** = an organizational container; datasets belong to a space

System-managed fields on examples (`id`, `created_at`, `updated_at`) are auto-generated by the server -- never include them in create or append payloads.

## Prerequisites

Proceed directly with the task — run the `ax` command you need. Do NOT check versions, env vars, or profiles upfront.

If an `ax` command fails, troubleshoot based on the error:
- `command not found` or version error → see references/ax-setup.md
- `401 Unauthorized` / missing API key → run `ax profiles show` to inspect the current profile. If the profile is missing or the API key is wrong: check `.env` for `ARIZE_API_KEY` and use it to create/update the profile via references/ax-profiles.md. If `.env` has no key either, ask the user for their Arize API key (https://app.arize.com/admin > API Keys)
- Space ID unknown → check `.env` for `ARIZE_SPACE_ID`, or run `ax spaces list -o json`, or ask the user
- Project unclear → check `.env` for `ARIZE_DEFAULT_PROJECT`, or ask, or run `ax projects list -o json --limit 100` and present as selectable options

## List Datasets: `ax datasets list`

Browse datasets in a space. Output goes to stdout.

```bash
ax datasets list
ax datasets list --space-id SPACE_ID --limit 20
ax datasets list --cursor CURSOR_TOKEN
ax datasets list -o json
```

### Flags

| Flag | Type | Default | Description |
|------|------|---------|-------------|
| `--space-id` | string | from profile | Filter by space |
| `--limit, -l` | int | 15 | Max results (1-100) |
| `--cursor` | string | none | Pagination cursor from previous response |
| `-o, --output` | string | table | Output format: table, json, csv, parquet, or file path |
| `-p, --profile` | string | default | Configuration profile |

## Get Dataset: `ax datasets get`

Quick metadata lookup -- returns dataset name, space, timestamps, and version list.

```bash
ax datasets get DATASET_ID
ax datasets get DATASET_ID -o json
```

### Flags

| Flag | Type | Default | Description |
|------|------|---------|-------------|
| `DATASET_ID` | string | required | Positional argument |
| `-o, --output` | string | table | Output format |
| `-p, --profile` | string | default | Configuration profile |

### Response fields

| Field | Type | Description |
|-------|------|-------------|
| `id` | string | Dataset ID |
| `name` | string | Dataset name |
| `space_id` | string | Space this dataset belongs to |
| `created_at` | datetime | When the dataset was created |
| `updated_at` | datetime | Last modification time |
| `versions` | array | List of dataset versions (id, name, dataset_id, created_at, updated_at) |

## Export Dataset: `ax datasets export`

Download all examples to a file. Use `--all` for datasets larger than 500 examples (unlimited bulk export).

```bash
ax datasets export DATASET_ID
# -> dataset_abc123_20260305_141500/examples.json

ax datasets export DATASET_ID --all
ax datasets export DATASET_ID --version-id VERSION_ID
ax datasets export DATASET_ID --output-dir ./data
ax datasets export DATASET_ID --stdout
ax datasets export DATASET_ID --stdout | jq '.[0]'
```

### Flags

| Flag | Type | Default | Description |
|------|------|---------|-------------|
| `DATASET_ID` | string | required | Positional argument |
| `--version-id` | string | latest | Export a specific dataset version |
| `--all` | bool | false | Unlimited bulk export (use for datasets > 500 examples) |
| `--output-dir` | string | `.` | Output directory |
| `--stdout` | bool | false | Print JSON to stdout instead of file |
| `-p, --profile` | string | default | Configuration profile |

**Agent auto-escalation rule:** If an export returns exactly 500 examples, the result is likely truncated — re-run with `--all` to get the full dataset.

**Export completeness verification:** After exporting, confirm the row count matches what the server reports:
```bash
# Get the server-reported count from dataset metadata
ax datasets get DATASET_ID -o json | jq '.versions[-1] | {version: .id, examples: .example_count}'

# Compare to what was exported
jq 'length' dataset_*/examples.json

# If counts differ, re-export with --all
```

Output is a JSON array of example objects. Each example has system fields (`id`, `created_at`, `updated_at`) plus all user-defined fields:

```json
[
  {
    "id": "ex_001",
    "created_at": "2026-01-15T10:00:00Z",
    "updated_at": "2026-01-15T10:00:00Z",
    "question": "What is 2+2?",
    "answer": "4",
    "topic": "math"
  }
]
```

## Create Dataset: `ax datasets create`

Create a new dataset from a data file.

```bash
ax datasets create --name "My Dataset" --space-id SPACE_ID --file data.csv
ax datasets create --name "My Dataset" --space-id SPACE_ID --file data.json
ax datasets create --name "My Dataset" --space-id SPACE_ID --file data.jsonl
ax datasets create --name "My Dataset" --space-id SPACE_ID --file data.parquet
```

### Flags

| Flag | Type | Required | Description |
|------|------|----------|-------------|
| `--name, -n` | string | yes | Dataset name |
| `--space-id` | string | yes | Space to create the dataset in |
| `--file, -f` | path | yes | Data file: CSV, JSON, JSONL, or Parquet |
| `-o, --output` | string | no | Output format for the returned dataset metadata |
| `-p, --profile` | string | no | Configuration profile |

### Passing data via stdin

Use `--file -` to pipe data directly — no temp file needed:

```bash
echo '[{"question": "What is 2+2?", "answer": "4"}]' | ax datasets create --name "my-dataset" --space-id SPACE_ID --file -

# Or with a heredoc
ax datasets create --name "my-dataset" --space-id SPACE_ID --file - << 'EOF'
[{"question": "What is 2+2?", "answer": "4"}]
EOF
```

To add rows to an existing dataset, use `ax datasets append --json '[...]'` instead — no file needed.

### Supported file formats

| Format | Extension | Notes |
|--------|-----------|-------|
| CSV | `.csv` | Column headers become field names |
| JSON | `.json` | Array of objects |
| JSON Lines | `.jsonl` | One object per line (NOT a JSON array) |
| Parquet | `.parquet` | Column names become field names; preserves types |

**Format gotchas:**
- **CSV**: Loses type information — dates become strings, `null` becomes empty string. Use JSON/Parquet to preserve types.
- **JSONL**: Each line is a separate JSON object. A JSON array (`[{...}, {...}]`) in a `.jsonl` file will fail — use `.json` extension instead.
- **Parquet**: Preserves column types. Requires `pandas`/`pyarrow` to read locally: `pd.read_parquet("examples.parquet")`.

## Append Examples: `ax datasets append`

Add examples to an existing dataset. Two input modes -- use whichever fits.

### Inline JSON (agent-friendly)

Generate the payload directly -- no temp files needed:

```bash
ax datasets append DATASET_ID --json '[{"question": "What is 2+2?", "answer": "4"}]'

ax datasets append DATASET_ID --json '[
  {"question": "What is gravity?", "answer": "A fundamental force..."},
  {"question": "What is light?", "answer": "Electromagnetic radiation..."}
]'
```

### From a file

```bash
ax datasets append DATASET_ID --file new_examples.csv
ax datasets append DATASET_ID --file additions.json
```

### To a specific version

```bash
ax datasets append DATASET_ID --json '[{"q": "..."}]' --version-id VERSION_ID
```

### Flags

| Flag | Type | Required | Description |
|------|------|----------|-------------|
| `DATASET_ID` | string | yes | Positional argument |
| `--json` | string | mutex | JSON array of example objects |
| `--file, -f` | path | mutex | Data file (CSV, JSON, JSONL, Parquet) |
| `--version-id` | string | no | Append to a specific version (default: latest) |
| `-o, --output` | string | no | Output format for the returned dataset metadata |
| `-p, --profile` | string | no | Configuration profile |

Exactly one of `--json` or `--file` is required.

### Validation

- Each example must be a JSON object with at least one user-defined field
- Maximum 100,000 examples per request

**Schema validation before append:** If the dataset already has examples, inspect its schema before appending to avoid silent field mismatches:

```bash
# Check existing field names in the dataset
ax datasets export DATASET_ID --stdout | jq '.[0] | keys'

# Verify your new data has matching field names
echo '[{"question": "..."}]' | jq '.[0] | keys'

# Both outputs should show the same user-defined fields
```

Fields are free-form: extra fields in new examples are added, and missing fields become null. However, typos in field names (e.g., `queston` vs `question`) create new columns silently -- verify spelling before appending.

## Delete Dataset: `ax datasets delete`

```bash
ax datasets delete DATASET_ID
ax datasets delete DATASET_ID --force   # skip confirmation prompt
```

### Flags

| Flag | Type | Default | Description |
|------|------|---------|-------------|
| `DATASET_ID` | string | required | Positional argument |
| `--force, -f` | bool | false | Skip confirmation prompt |
| `-p, --profile` | string | default | Configuration profile |

## Workflows

### Find a dataset by name

Users often refer to datasets by name rather than ID. Resolve a name to an ID before running other commands:

```bash
# Find dataset ID by name
ax datasets list -o json | jq '.[] | select(.name == "eval-set-v1") | .id'

# If the list is paginated, fetch more
ax datasets list -o json --limit 100 | jq '.[] | select(.name | test("eval-set")) | {id, name}'
```

### Create a dataset from file for evaluation

1. Prepare a CSV/JSON/Parquet file with your evaluation columns (e.g., `input`, `expected_output`)
   - If generating data inline, pipe it via stdin using `--file -` (see the Create Dataset section)
2. `ax datasets create --name "eval-set-v1" --space-id SPACE_ID --file eval_data.csv`
3. Verify: `ax datasets get DATASET_ID`
4. Use the dataset ID to run experiments

### Add examples to an existing dataset

```bash
# Find the dataset
ax datasets list

# Append inline or from a file (see Append Examples section for full syntax)
ax datasets append DATASET_ID --json '[{"question": "...", "answer": "..."}]'
ax datasets append DATASET_ID --file additional_examples.csv
```

### Download dataset for offline analysis

1. `ax datasets list` -- find the dataset
2. `ax datasets export DATASET_ID` -- download to file
3. Parse the JSON: `jq '.[] | .question' dataset_*/examples.json`

### Export a specific version

```bash
# List versions
ax datasets get DATASET_ID -o json | jq '.versions'

# Export that version
ax datasets export DATASET_ID --version-id VERSION_ID
```

### Iterate on a dataset

1. Export current version: `ax datasets export DATASET_ID`
2. Modify the examples locally
3. Append new rows: `ax datasets append DATASET_ID --file new_rows.csv`
4. Or create a fresh version: `ax datasets create --name "eval-set-v2" --space-id SPACE_ID --file updated_data.json`

### Pipe export to other tools

```bash
# Count examples
ax datasets export DATASET_ID --stdout | jq 'length'

# Extract a single field
ax datasets export DATASET_ID --stdout | jq '.[].question'

# Convert to CSV with jq
ax datasets export DATASET_ID --stdout | jq -r '.[] | [.question, .answer] | @csv'
```

## Dataset Example Schema

Examples are free-form JSON objects. There is no fixed schema -- columns are whatever fields you provide. System-managed fields are added by the server:

| Field | Type | Managed by | Notes |
|-------|------|-----------|-------|
| `id` | string | server | Auto-generated UUID. Required on update, forbidden on create/append |
| `created_at` | datetime | server | Immutable creation timestamp |
| `updated_at` | datetime | server | Auto-updated on modification |
| *(any user field)* | any JSON type | user | String, number, boolean, null, nested object, array |


## Related Skills

- **arize-trace**: Export production spans to understand what data to put in datasets → use `arize-trace`
- **arize-experiment**: Run evaluations against this dataset → next step is `arize-experiment`
- **arize-prompt-optimization**: Use dataset + experiment results to improve prompts → use `arize-prompt-optimization`

## Troubleshooting

| Problem | Solution |
|---------|----------|
| `ax: command not found` | See references/ax-setup.md |
| `401 Unauthorized` | API key is wrong, expired, or doesn't have access to this space. Fix the profile using references/ax-profiles.md. |
| `No profile found` | No profile is configured. See references/ax-profiles.md to create one. |
| `Dataset not found` | Verify dataset ID with `ax datasets list` |
| `File format error` | Supported: CSV, JSON, JSONL, Parquet. Use `--file -` to read from stdin. |
| `platform-managed column` | Remove `id`, `created_at`, `updated_at` from create/append payloads |
| `reserved column` | Remove `time`, `count`, or any `source_record_*` field |
| `Provide either --json or --file` | Append requires exactly one input source |
| `Examples array is empty` | Ensure your JSON array or file contains at least one example |
| `not a JSON object` | Each element in the `--json` array must be a `{...}` object, not a string or number |

## Save Credentials for Future Use

See references/ax-profiles.md § Save Credentials for Future Use.