### Why are these changes needed?

When `fit()` is called multiple times on a `Preprocessor`, the `stats_`
dict was not being reset before computing new stats. This caused stale
stats from previous `fit()` calls to persist when stat keys are
data-dependent (e.g., when columns are auto-detected from the data).

This violates the documented behavior in the `fit()` docstring:

> Calling it more than once will overwrite all previously fitted state:
> `preprocessor.fit(A).fit(B)` is equivalent to `preprocessor.fit(B)`.

**Example of the bug:**

```python
# Preprocessor that auto-detects columns from data
preprocessor = DataDependentPreprocessor()

# Dataset A has columns: a, b
dataset_a = ray.data.from_items([{"a": 1.0, "b": 10.0}, ...])
preprocessor.fit(dataset_a)
# stats_ = {"mean(a)": 2.0, "mean(b)": 20.0}

# Dataset B has columns: b, c (no "a" column)
dataset_b = ray.data.from_items([{"b": 100.0, "c": 1000.0}, ...])
preprocessor.fit(dataset_b)

# BUG: stats_ = {"mean(a)": 2.0, "mean(b)": 200.0, "mean(c)": 2000.0}
#      "mean(a)" is STALE - it should not exist!
# EXPECTED: stats_ = {"mean(b)": 200.0, "mean(c)": 2000.0}
```

---------

Signed-off-by: Xinyuan <43737116+xinyuangui2@users.noreply.github.com>
Signed-off-by: xgui <xgui@anyscale.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

### Why are these changes needed?

When `fit()` is called multiple times on a `Preprocessor`, the `stats_`
dict was not being reset before computing new stats. This caused stale
stats from previous `fit()` calls to persist when stat keys are
data-dependent (e.g., when columns are auto-detected from the data).

This violates the documented behavior in the `fit()` docstring:

> Calling it more than once will overwrite all previously fitted state:
> `preprocessor.fit(A).fit(B)` is equivalent to `preprocessor.fit(B)`.

**Example of the bug:**

```python
# Preprocessor that auto-detects columns from data
preprocessor = DataDependentPreprocessor()

# Dataset A has columns: a, b
dataset_a = ray.data.from_items([{"a": 1.0, "b": 10.0}, ...])
preprocessor.fit(dataset_a)
# stats_ = {"mean(a)": 2.0, "mean(b)": 20.0}

# Dataset B has columns: b, c (no "a" column)
dataset_b = ray.data.from_items([{"b": 100.0, "c": 1000.0}, ...])
preprocessor.fit(dataset_b)

# BUG: stats_ = {"mean(a)": 2.0, "mean(b)": 200.0, "mean(c)": 2000.0}
#      "mean(a)" is STALE - it should not exist!
# EXPECTED: stats_ = {"mean(b)": 200.0, "mean(c)": 2000.0}
```

---------

Signed-off-by: Xinyuan <43737116+xinyuangui2@users.noreply.github.com>
Signed-off-by: xgui <xgui@anyscale.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Signed-off-by: jeffery4011 <jefferyshen1015@gmail.com>

### Why are these changes needed?

When `fit()` is called multiple times on a `Preprocessor`, the `stats_`
dict was not being reset before computing new stats. This caused stale
stats from previous `fit()` calls to persist when stat keys are
data-dependent (e.g., when columns are auto-detected from the data).

This violates the documented behavior in the `fit()` docstring:

> Calling it more than once will overwrite all previously fitted state:
> `preprocessor.fit(A).fit(B)` is equivalent to `preprocessor.fit(B)`.

**Example of the bug:**

```python
# Preprocessor that auto-detects columns from data
preprocessor = DataDependentPreprocessor()

# Dataset A has columns: a, b
dataset_a = ray.data.from_items([{"a": 1.0, "b": 10.0}, ...])
preprocessor.fit(dataset_a)
# stats_ = {"mean(a)": 2.0, "mean(b)": 20.0}

# Dataset B has columns: b, c (no "a" column)
dataset_b = ray.data.from_items([{"b": 100.0, "c": 1000.0}, ...])
preprocessor.fit(dataset_b)

# BUG: stats_ = {"mean(a)": 2.0, "mean(b)": 200.0, "mean(c)": 2000.0}
#      "mean(a)" is STALE - it should not exist!
# EXPECTED: stats_ = {"mean(b)": 200.0, "mean(c)": 2000.0}
```

---------

Signed-off-by: Xinyuan <43737116+xinyuangui2@users.noreply.github.com>
Signed-off-by: xgui <xgui@anyscale.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

### Why are these changes needed?

When `fit()` is called multiple times on a `Preprocessor`, the `stats_`
dict was not being reset before computing new stats. This caused stale
stats from previous `fit()` calls to persist when stat keys are
data-dependent (e.g., when columns are auto-detected from the data).

This violates the documented behavior in the `fit()` docstring:

> Calling it more than once will overwrite all previously fitted state:
> `preprocessor.fit(A).fit(B)` is equivalent to `preprocessor.fit(B)`.

**Example of the bug:**

```python
# Preprocessor that auto-detects columns from data
preprocessor = DataDependentPreprocessor()

# Dataset A has columns: a, b
dataset_a = ray.data.from_items([{"a": 1.0, "b": 10.0}, ...])
preprocessor.fit(dataset_a)
# stats_ = {"mean(a)": 2.0, "mean(b)": 20.0}

# Dataset B has columns: b, c (no "a" column)
dataset_b = ray.data.from_items([{"b": 100.0, "c": 1000.0}, ...])
preprocessor.fit(dataset_b)

# BUG: stats_ = {"mean(a)": 2.0, "mean(b)": 200.0, "mean(c)": 2000.0}
#      "mean(a)" is STALE - it should not exist!
# EXPECTED: stats_ = {"mean(b)": 200.0, "mean(c)": 2000.0}
```

---------

Signed-off-by: Xinyuan <43737116+xinyuangui2@users.noreply.github.com>
Signed-off-by: xgui <xgui@anyscale.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Signed-off-by: peterxcli <peterxcli@gmail.com>

### Why are these changes needed?

When `fit()` is called multiple times on a `Preprocessor`, the `stats_`
dict was not being reset before computing new stats. This caused stale
stats from previous `fit()` calls to persist when stat keys are
data-dependent (e.g., when columns are auto-detected from the data).

This violates the documented behavior in the `fit()` docstring:

> Calling it more than once will overwrite all previously fitted state:
> `preprocessor.fit(A).fit(B)` is equivalent to `preprocessor.fit(B)`.

**Example of the bug:**

```python
# Preprocessor that auto-detects columns from data
preprocessor = DataDependentPreprocessor()

# Dataset A has columns: a, b
dataset_a = ray.data.from_items([{"a": 1.0, "b": 10.0}, ...])
preprocessor.fit(dataset_a)
# stats_ = {"mean(a)": 2.0, "mean(b)": 20.0}

# Dataset B has columns: b, c (no "a" column)
dataset_b = ray.data.from_items([{"b": 100.0, "c": 1000.0}, ...])
preprocessor.fit(dataset_b)

# BUG: stats_ = {"mean(a)": 2.0, "mean(b)": 200.0, "mean(c)": 2000.0}
#      "mean(a)" is STALE - it should not exist!
# EXPECTED: stats_ = {"mean(b)": 200.0, "mean(c)": 2000.0}
```

---------

Signed-off-by: Xinyuan <43737116+xinyuangui2@users.noreply.github.com>
Signed-off-by: xgui <xgui@anyscale.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Signed-off-by: peterxcli <peterxcli@gmail.com>