# Stats for `stanfordnlp/sst2`

Generated by [`dataset-stats.py`](https://github.com/tcondello/uv-scripts-colab/blob/main/recipes/dataset-stats.py) over the `train` split.

- **Total rows in split:** 67,349
- **Rows profiled:** 5,000
- **Columns:** 3

## Column overview

| column | type | kind | null % | highlights |
|---|---|---|---:|---|
| `idx` | `Value(int32)` | numeric | 0.0% | min=0.00 · p50=2,499.50 · max=4,999.00 · distinct=5000 |
| `sentence` | `Value(string)` | string | 0.0% | distinct=4,999 · len p50=39 · max=255 |
| `label` | `ClassLabel` | class_label | 0.0% | `positive`=2758 · `negative`=2242 |

## Per-column detail

### `idx`

- **type:** `Value(int32)`  •  **kind:** numeric  •  **null:** 0 / 5,000 (0.0%)

```json
{
  "kind": "numeric",
  "n": 5000,
  "min": 0.0,
  "p1": 49.99,
  "p25": 1249.75,
  "p50": 2499.5,
  "p75": 3749.25,
  "p99": 4949.01,
  "max": 4999.0,
  "mean": 2499.5,
  "std": 1443.3756441065507,
  "distinct": 5000
}
```

### `sentence`

- **type:** `Value(string)`  •  **kind:** string  •  **null:** 0 / 5,000 (0.0%)

```json
{
  "kind": "string",
  "n": 5000,
  "distinct": 4999,
  "len_min": 2,
  "len_p50": 39,
  "len_mean": 53.479,
  "len_p99": 194,
  "len_max": 255,
  "top_values": [
    {
      "value": "unfunny ",
      "count": 2
    },
    {
      "value": "hide new secretions from the parental units ",
      "count": 1
    },
    {
      "value": "contains no wit , only labored gags ",
      "count": 1
    },
    {
      "value": "that loves its characters and communicates something rather beautiful about human nature ",
      "count": 1
    },
    {
      "value": "remains utterly satisfied to remain the same throughout ",
      "count": 1
    },
    {
      "value": "on the worst revenge-of-the-nerds clichés the filmmakers could dredge up ",
      "count": 1
    },
    {
      "value": "that 's far too tragic to merit such superficial treatment ",
      "count": 1
    },
    {
      "value": "demonstrates that the director of such hollywood blockbusters as patriot games can still turn out a ",
      "count": 1
    },
    {
      "value": "of saucy ",
      "count": 1
    },
    {
      "value": "a depressed fifteen-year-old 's suicidal poetry ",
      "count": 1
    }
  ],
  "samples": {
    "shortest": "( ",
    "median": "piece , a model of menacing atmosphere ",
    "longest": "director george hickenlooper has had some success with documentaries , but here his sense of story and his juvenile camera movements smack of a film school undergrad , and his maudlin ending might not"
  }
}
```

### `label`

- **type:** `ClassLabel`  •  **kind:** class_label  •  **null:** 0 / 5,000 (0.0%)

```json
{
  "kind": "class_label",
  "n": 5000,
  "num_classes": 2,
  "value_counts": [
    {
      "id": 1,
      "name": "positive",
      "count": 2758,
      "pct": 55.16
    },
    {
      "id": 0,
      "name": "negative",
      "count": 2242,
      "pct": 44.84
    }
  ]
}
```

## Reproduce

```bash
INPUT_DATASET=stanfordnlp/sst2 \
OUTPUT_DATASET=Tim-Pinecone/sst2-stats \
SPLIT=train LIMIT=5000 \
  bin/colab-hf-run recipes/dataset-stats.py
```

## Machine-readable

Per-column rows live in the dataset's `train` split: one row per column with `column`, `feature_type`, `kind`, `n_total`, `n_null`, `null_pct`, and `stats_json` (full per-kind detail).