# Sample Realistic Data

Create realistic synthetic data data that follows the same format and mathematical properties as the real data.

### sample

Use this function to create synthetic data that follows the same format and mathematical properties as the real data.

```python
synthetic_data = synthesizer.sample(
    num_rows=1_000_000,
    batch_size=1_000
)
```

**Parameters**

* (required) `num_rows`: An integer >0 that specifies the number of rows to synthesize
* `batch_size`: An integer >0, describing the number of rows to sample at a time. If you are sampling a large number of rows, setting a smaller batch size allows you to see and save incremental progress. Defaults to the same as `num_rows`.
* `max_tries_per_batch`: An integer >0, describing the number of sampling attempts to make per batch. If you have included constraints, it may take multiple batches to create valid data. Defaults to `100`.
* `output_file_path`: A string describing a CSV filepath for writing the synthetic data. Specify to `None` to skip writing to a file. Defaults to `None`.

**Returns** A [pandas DataFrame](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html) object with synthetic data. The synthetic data mimics the real data.

### reset\_sampling

Use this function to reset any randomization in sampling. After calling this, your synthesizer will generate the same data as before. For example in the code below, `synthetic_data1` and `synthetic_data2` are the same.

```python
synthesizer.reset_sampling()
synthetic_data1 = synthesizer.sample(num_rows=10)

synthesizer.reset_sampling()
synthetic_data2 = synthesizer.sample(num_rows=10)
```

**Parameters** None

**Returns** None. Resets the synthesizer.

{% hint style="info" %}
If you have your synthesizer, it will reset sampling automatically for you. The next time you load and sample, you will receive the same synthetic data.
{% endhint %}


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