diff --git a/.github/workflows/pypi-publish.yml b/.github/workflows/pypi-publish.yml
new file mode 100644
index 0000000..b8cf6b3
--- /dev/null
+++ b/.github/workflows/pypi-publish.yml
@@ -0,0 +1,22 @@
+name: Upload Python Package
+
+on:
+  release:
+    types: [published]
+
+jobs:
+  pypi-publish:
+    name: upload release to PyPI
+    runs-on: ubuntu-latest
+    permissions:
+      # This permission is needed for private repositories.
+      contents: read
+      # IMPORTANT: this permission is mandatory for trusted publishing
+      id-token: write
+    steps:
+      - uses: actions/checkout@v3
+
+      - uses: pdm-project/setup-pdm@v3
+
+      - name: Publish package distributions to PyPI
+        run: pdm publish
diff --git a/docs/api.md b/docs/api.md
index e69de29..91dff20 100644
--- a/docs/api.md
+++ b/docs/api.md
@@ -0,0 +1,591 @@
+# The API Documentation for `pearson3curve`
+
+## `pearson3curve` Module
+
+### `Data` Class
+
+```python
+class Data
+```
+
+The P-III distributed data class.
+
+---
+
+#### Methods
+
+```python
+def __init__(self, observed_data: list[float] | np.ndarray) -> None
+```
+
+Initialize the P-III distributed data from the observed data.
+
+- Parameters
+
+  - `observed_data` : `list[float] | np.ndarray`
+
+    The observed data, supporting either a list or a numpy array.
+
+---
+
+```python
+def set_history_data(
+    self,
+    history_data: list[float] | np.ndarray,
+    period_length: int,
+    *,
+    extreme_num: int | None = None,
+) -> None
+```
+
+Set the history data and the survey period length.
+
+- Parameters:
+
+  - `history_data` : `list[float] | np.ndarray`
+
+    The history data, supporting either a list or a numpy array.
+
+  - `period_length` : `int`
+
+    The survey period length.
+
+  - `extreme_num` : `int | None`, optional
+
+    The number of extreme data, by default None. If `None`, all the history data will be treated as extreme data.
+
+- Raises:
+
+  - `ValueError`
+
+    - If the period length is less than the sum of the lengths of the observed data and the history data.
+
+    - If the number of extreme data is less than the length of the history data.
+
+---
+
+```python
+def set_empirical_prob(self, empirical_prob: list[float] | np.ndarray) -> None
+```
+
+Set all the empirical probabilities for the data.
+
+- Parameters:
+
+  - `empirical_prob` : `list[float] | np.ndarray`
+
+    The total empirical probabilities, supporting either a list or a numpy array. The length should be the same as the length of the data. And the values should be in the range from 0 to 1.
+
+- Raises:
+
+  - `ValueError`
+
+    - If the length of the empirical probabilities is not the same as the length of the data.
+
+    - If any value in the empirical probabilities is out of the range from 0 to 1.
+
+---
+
+```python
+def set_empirical_prob_by_order(
+    self, order: int, prob: float, *, start_value=1
+) -> None
+```
+
+Set the empirical probability of the data by the order number.
+
+- Parameters:
+
+  - `order` : `int`
+
+    The order number of the data, starting from `start_value`, which is 1 by default. The data is sorted in descending order. Therefore, the first data is the largest one.
+
+  - `prob` : `float`
+
+    The empirical probability to be set. It should be in the range from 0 to 1.
+
+  - `start_value` : `int`, optional
+
+    The start number of the order, by default 1.
+
+- Raises:
+
+  - `IndexError`
+
+    If the order number is out of the range of the data.
+
+  - `ValueError`
+
+    If the empirical probability is out of the range from 0 to 1.
+
+---
+
+#### Properties
+
+```python
+@property
+def data(self) -> np.ndarray
+```
+
+The descending sorted data.
+
+---
+
+```python
+@property
+def extreme_data(self) -> np.ndarray
+```
+
+The descending sorted extreme data.
+
+---
+
+```python
+@property
+def ordinary_data(self) -> np.ndarray
+```
+
+The descending sorted ordinary data.
+
+---
+
+```python
+@property
+def period_length(self) -> int
+```
+
+The survey period length of the data.
+
+---
+
+```python
+@property
+def extreme_prob(self) -> np.ndarray
+```
+
+The empirical probabilities of the extreme data.
+
+---
+
+```python
+@property
+def ordinary_prob(self) -> np.ndarray
+```
+
+The empirical probabilities of the ordinary data.
+
+---
+
+```python
+@property
+def empirical_prob(self) -> np.ndarray
+```
+
+The empirical probabilities for the data.
+
+### `Curve` Class
+
+```python
+class Curve
+```
+
+The P-III distributed curve class.
+
+---
+
+#### Methods
+
+```python
+def __init__(self, ex: float, cv: float, cs: float) -> None
+```
+
+Initialize the P-III distributed curve from the moments.
+
+- Parameters
+
+  - `ex` : `float`
+
+    The mean of the distribution.
+
+  - `cv` : `float`
+
+    The coefficient of variation of the distribution.
+
+  - `cs` : `float`
+
+    The skewness of the distribution.
+
+---
+
+```python
+def get_value_from_prob(self, prob: float) -> float
+```
+
+Get the value from the probability.
+
+- Parameters
+
+  - `prob` : `float`
+
+    The probability, from 0 to 1.
+
+- Returns
+
+  - `float`
+
+    The value. `nan` if the probability is out of the range from 0 to 1.
+
+---
+
+```python
+def get_prob_from_value(self, value: float) -> float
+```
+
+Get the probability from the value.
+
+- Parameters
+
+  - `value` : `float`
+
+    The value.
+
+- Returns
+
+  - `float`
+
+    The probability, from 0 to 1.
+
+### `get_moments` Function
+
+```python
+def get_moments(data: Data) -> tuple[float, float, float]
+```
+
+Get the P-III distribution moments (mean, coefficient of variation, and skewness) of the data.
+
+- Parameters
+
+  - `data` : `Data`
+
+    The P-III distributed data.
+
+- Returns
+
+  - `tuple[float, float, float]`
+
+    The moments (ex, cv, cs) of the data.
+
+### `get_fitted_moments` Function
+
+```python
+def get_fitted_moments(
+    data: Data,
+    *,
+    sv_ratio: float | None = None,
+    fit_ex=True,
+    moments: tuple[float, float, float] | None = None,
+) -> tuple[float, float, float]
+```
+
+Get the fitted P-III distribution moments (mean, coefficient of variation, and skewness) of the data.
+
+- Parameters
+
+  - `data` : `Data`
+
+    The P-III distributed data.
+
+  - `sv_ratio` : `float | None`, optional
+
+    The skewness-to-variance ratio, by default `None`, which means the variance and skewness will be fitted separately. If set, the skewness will be the product of the variance and the ratio.
+
+  - `fit_ex` : `bool`, optional
+
+    Whether to fit the mean, by default True. If `False`, the mean will not be fitted.
+
+  - `moments` : `tuple[float, float, float] | None`, optional
+
+    The moments (ex, cv, cs) of the data. If `None`, the moments will be calculated from the data.
+
+- Returns
+
+  - `tuple[float, float, float]`
+
+    The fitted P-III moments (ex, cv, cs) of the data.
+
+## `pearson3curve.plot` and `pearson3curve.pgfplot` Modules
+
+The module for plotting the Pearson Type III distribution curve. The `pgfplot` module uses pgf
+backend for better multi-language text and math typesetting support.
+
+### `set_figsize` Function
+
+```python
+def set_figsize(width: float, height: float) -> None
+```
+
+Set the figure size.
+
+- Parameters
+
+  - `width` : `float`
+
+    The width of the figure in inches.
+
+  - `height` : `float`
+
+    The height of the figure in inches.
+
+### `set_font` Function
+
+```python
+def set_font(font: str) -> None
+```
+
+Set the font for the plot. Only available for the `plot` module.
+
+- Parameters
+
+  - `font` : `str`
+
+    The font name.
+
+### `set_tex_preamble` Function
+
+```python
+def set_tex_preamble(preamble: str) -> None
+```
+
+Set the TeX preamble. Only available for the `pgfplot` module.
+
+- Parameters
+
+  - `preamble` : `str`
+
+    The TeX preamble.
+
+### `set_title` Function
+
+```python
+def set_title(title: str, **kwargs) -> None
+```
+
+Set the title of the plot.
+
+- Parameters
+
+  - `title` : `str`
+
+    The title.
+
+  - `**kwargs`
+
+    Additional keyword arguments to be passed to the `matplotlib.axes.Axes.set_title` method.
+
+### `set_xlim` Function
+
+```python
+def set_xlim(left: float, right: float, **kwargs) -> None
+```
+
+Set the x-axis limits.
+
+- Parameters
+
+  - `left` : `float`
+
+    The left limit.
+
+  - `right` : `float`
+
+    The right limit.
+
+  - `**kwargs`
+
+    Additional keyword arguments to be passed to the `matplotlib.axes.Axes.set_xlim` method.
+
+### `set_xlabel` Function
+
+```python
+def set_xlabel(label: str, **kwargs) -> None
+```
+
+Set the x-axis label.
+
+- Parameters
+
+  - `label` : `str`
+
+    The label.
+
+  - `**kwargs`
+
+    Additional keyword arguments to be passed to the `matplotlib.axes.Axes.set_xlabel` method.
+
+### `set_ylabel` Function
+
+```python
+def set_ylabel(label: str, **kwargs) -> None
+```
+
+Set the y-axis label.
+
+- Parameters
+
+  - `label` : `str`
+
+    The label.
+
+  - `**kwargs`
+
+    Additional keyword arguments to be passed to the `matplotlib.axes.Axes.set_ylabel` method.
+
+### `grid` Function
+
+```python
+def grid(visible: bool, **kwargs) -> None
+```
+
+Set whether to show the grid.
+
+- Parameters
+
+  - `visible` : `bool`
+
+    Whether to show the grid.
+
+  - `**kwargs`
+
+    Additional keyword arguments to be passed to the `matplotlib.axes.Axes.grid` method.
+
+### `legend` Function
+
+```python
+def legend(**kwargs) -> None
+```
+
+Set whether to show the legend.
+
+- Parameters
+
+  - `**kwargs`
+
+    Additional keyword arguments to be passed to the `matplotlib.axes.Axes.legend` method.
+
+### `scatter` Function
+
+```python
+def scatter(
+    data: Data,
+    *,
+    extreme_label="Extreme data",
+    ordinary_label="Ordinary data",
+    extreme_kwargs: dict[str, Any] | None = None,
+    ordinary_kwargs: dict[str, Any] | None = None,
+    **kwargs,
+) -> None
+```
+
+Plot the scatter plot of the data.
+
+- Parameters
+
+  - `data` : `Data`
+
+    The data.
+
+  - `extreme_label` : `str`, optional
+
+    The label for the extreme data, by default "Extreme data".
+
+  - `ordinary_label` : `str`, optional
+
+    The label for the ordinary data, by default "Ordinary data".
+
+  - `extreme_kwargs` : `dict[str, Any] | None`, optional
+
+    Additional keyword arguments to be passed to the `matplotlib.pyplot.scatter` function for plotting the extreme data scatter points, by default None.
+
+  - `ordinary_kwargs` : `dict[str, Any] | None`, optional
+
+    Additional keyword arguments to be passed to the `matplotlib.pyplot.scatter` function for plotting the ordinary data scatter points, by default None.
+
+  - `**kwargs`
+
+    Additional keyword arguments to be passed to the `matplotlib.pyplot.scatter` function. If given, it will update both the `extreme_kwargs` and `ordinary_kwargs`.
+
+### `plot` Function
+
+```python
+def plot(
+    curve: Curve,
+    *,
+    label: str | None = None,
+    color: str | None = None,
+    linestyle: str | None = None,
+    linewidth: float | None = None,
+    **kwargs,
+) -> None
+```
+
+Plot the Pearson Type III distribution curve.
+
+- Parameters
+
+  - `curve` : `Curve`
+
+    The Pearson Type III distribution curve.
+
+  - `label` : `str | None`, optional
+
+    The label for the curve, by default None.
+
+  - `color` : `str | None`, optional
+
+    The color for the curve, by default None.
+
+  - `linestyle` : `str | None`, optional
+
+    The line style for the curve, by default None.
+
+  - `linewidth` : `float | None`, optional
+
+    The line width for the curve, by default None.
+
+  - `**kwargs`
+
+    Additional keyword arguments to be passed to the `matplotlib.pyplot.plot` function.
+
+### `show` Function
+
+```python
+def show() -> None
+```
+
+Show the plot. Only available for the `plot` module.
+
+### `save` Function
+
+```python
+def save(file_name: str, *, transparent=True, dpi=300, **kwargs) -> None
+```
+
+Save the plot to a file.
+
+- Parameters
+
+  - `file_name` : `str`
+
+    The file name.
+
+  - `transparent` : `bool`, optional
+
+    Whether to save the plot with a transparent background, by default True.
+
+  - `dpi` : `int`, optional
+
+    The resolution in dots per inch, by default 300. This will be omitted if saving to a vector format.
+
+  - `**kwargs`
+
+    Additional keyword arguments to be passed to the `matplotlib.figure.Figure.savefig` method.
diff --git a/pyproject.toml b/pyproject.toml
index fb656ff..3e3f1b1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "pearson3curve"
-version = "0.7.0"
+version = "1.0.0"
 description = "Pearson III curve fitting and plotting"
 authors = [{ name = "ListLee", email = "list.lee@outlook.com" }]
 dependencies = [
diff --git a/src/pearson3curve/curve.py b/src/pearson3curve/curve.py
index 492c569..562e9ad 100644
--- a/src/pearson3curve/curve.py
+++ b/src/pearson3curve/curve.py
@@ -6,7 +6,7 @@
 class Curve:
     """The P-III distribution curve class."""
 
-    def __init__(self, ex: float, cv: float, cs: float):
+    def __init__(self, ex: float, cv: float, cs: float) -> None:
         """Initialize the P-III distribution curve from the moments.
 
         Parameters
diff --git a/src/pearson3curve/data.py b/src/pearson3curve/data.py
index dda8ed6..7a4ce5f 100644
--- a/src/pearson3curve/data.py
+++ b/src/pearson3curve/data.py
@@ -185,8 +185,8 @@ def set_empirical_prob(self, empirical_prob: list[float] | np.ndarray) -> None:
         ----------
         empirical_prob : list[float] | np.ndarray
             The total empirical probabilities, supporting either a list or a
-            numpy array. The length should be the same as the length of the data
-            sequence. And the values should be in the range from 0 to 1.
+            numpy array. The length should be the same as the length of the
+            data. And the values should be in the range from 0 to 1.
 
         Raises
         ------
@@ -223,8 +223,8 @@ def set_empirical_prob_by_order(
         ----------
         order : int
             The order number of the data, starting from `start_value`, which is
-            1 by default. The data sequence is sorted in descending order.
-            Therefore, the first data is the largest one.
+            1 by default. The data is sorted in descending order. Therefore, the
+            first data is the largest one.
         prob : float
             The empirical probability to be set. It should be in the range from
             0 to 1.
diff --git a/src/pearson3curve/fitting.py b/src/pearson3curve/fitting.py
index 2cbd9f8..8ed28f1 100644
--- a/src/pearson3curve/fitting.py
+++ b/src/pearson3curve/fitting.py
@@ -82,7 +82,7 @@ def get_fitted_moments(
         variance and skewness will be fitted separately. If set, the skewness
         will be the product of the variance and the ratio.
     fit_ex : bool, optional
-        Whether to fit the mean, by default `True`. If `False`, the mean will
+        Whether to fit the mean, by default True. If `False`, the mean will
         not be fitted.
     moments : tuple[float, float, float] | None, optional
         The moments (ex, cv, cs) of the data. If `None`, the moments will be
@@ -91,7 +91,7 @@ def get_fitted_moments(
     Returns
     -------
     tuple[float, float, float]
-        The fitted P-III parameters (ex, cv, cs) of the data.
+        The fitted P-III moments (ex, cv, cs) of the data.
     """
 
     if moments is None:
diff --git a/src/pearson3curve/plot.py b/src/pearson3curve/plot.py
index fdd142e..bb1c498 100644
--- a/src/pearson3curve/plot.py
+++ b/src/pearson3curve/plot.py
@@ -43,7 +43,7 @@ def set_figsize(width: float, height: float) -> None:
 
 
 def set_font(font: str) -> None:
-    """Set the font for text.
+    """Set the font for the plot.
 
     Parameters
     ----------
@@ -62,8 +62,8 @@ def set_title(title: str, **kwargs) -> None:
     title : str
         The title.
     **kwargs
-        Additional keyword arguments to pass to the
-        `matplotlib.axes.Axes.set_title`
+        Additional keyword arguments to be passed to the
+        `matplotlib.axes.Axes.set_title` method.
     """
 
     _ax.set_title(title, **kwargs)
@@ -79,8 +79,8 @@ def set_xlim(left: float, right: float, **kwargs) -> None:
     right : float
         The right limit.
     **kwargs
-        Additional keyword arguments to pass to the
-        `matplotlib.axes.Axes.set_xlim`
+        Additional keyword arguments to be passed to the
+        `matplotlib.axes.Axes.set_xlim` method.
     """
 
     _ax.set_xlim(left, right, **kwargs)
@@ -95,8 +95,8 @@ def set_xlabel(label: str, **kwargs) -> None:
     label : str
         The label.
     **kwargs
-        Additional keyword arguments to pass to the
-        `matplotlib.axes.Axes.set_xlabel`
+        Additional keyword arguments to be passed to the
+        `matplotlib.axes.Axes.set_xlabel` method.
     """
 
     _ax.set_xlabel(label, **kwargs)
@@ -110,8 +110,8 @@ def set_ylabel(label: str, **kwargs) -> None:
     label : str
         The label.
     **kwargs
-        Additional keyword arguments to pass to the
-        `matplotlib.axes.Axes.set_ylabel`
+        Additional keyword arguments to be passed to the
+        `matplotlib.axes.Axes.set_ylabel` method.
     """
 
     _ax.set_ylabel(label, **kwargs)
@@ -125,8 +125,8 @@ def grid(visible: bool, **kwargs) -> None:
     visible : bool
         Whether to show the grid.
     **kwargs
-        Additional keyword arguments to pass to the
-        `matplotlib.axes.Axes.grid`
+        Additional keyword arguments to be passed to the
+        `matplotlib.axes.Axes.grid` method.
     """
 
     _ax.grid(visible, **kwargs)
@@ -138,8 +138,8 @@ def legend(**kwargs) -> None:
     Parameters
     ----------
     **kwargs
-        Additional keyword arguments to pass to the
-        `matplotlib.axes.Axes.legend`
+        Additional keyword arguments to be passed to the
+        `matplotlib.axes.Axes.legend` method.
     """
 
     _ax.legend(**kwargs)
@@ -154,7 +154,7 @@ def scatter(
     ordinary_kwargs: dict[str, Any] | None = None,
     **kwargs,
 ) -> None:
-    """Plot the data as a scatter plot.
+    """Plot the scatter plot of the data.
 
     Parameters
     ----------
@@ -164,15 +164,17 @@ def scatter(
         The label for the extreme data, by default "Extreme data".
     ordinary_label : str, optional
         The label for the ordinary data, by default "Ordinary data".
-    extreme_kwargs : dict[str, Any]
-        Additional keyword arguments to pass to the `matplotlib.pyplot.scatter`
-        for plotting the extreme data scatter points.
-    ordinary_kwargs : dict[str, Any]
-        Additional keyword arguments to pass to the `matplotlib.pyplot.scatter`
-        for plotting the ordinary data scatter points.
+    extreme_kwargs : dict[str, Any] | None, optional
+        Additional keyword arguments to be passed to the
+        `matplotlib.pyplot.scatter` function for plotting the extreme data
+        scatter points, by default None.
+    ordinary_kwargs : dict[str, Any] | None, optional
+        Additional keyword arguments to be passed to the
+        `matplotlib.pyplot.scatter` function for plotting the ordinary data
+        scatter points, by default None.
     **kwargs
-        Additional keyword arguments to pass to the `matplotlib.pyplot.scatter`
-        for plotting the scatter points. If given, it will update both the
+        Additional keyword arguments to be passed to the
+        `matplotlib.pyplot.scatter` function. If given, it will update both the
         `extreme_kwargs` and `ordinary_kwargs`.
     """
 
@@ -230,19 +232,16 @@ def plot(
     curve : Curve
         The Pearson Type III distribution curve.
     label : str | None, optional
-        The label for the curve, by default None. This will be passed to the
-        `matplotlib.pyplot.plot`.
+        The label for the curve, by default None.
     color : str | None, optional
-        The color of the curve, by default None. This will be passed to the
-        `matplotlib.pyplot.plot`.
+        The color of the curve, by default None.
     linestyle : str | None, optional
-        The line style of the curve, by default None. This will be passed to
-        the `matplotlib.pyplot.plot`.
+        The line style of the curve, by default None.
     linewidth : float | None, optional
-        The line width of the curve, by default None. This will be passed to
-        the `matplotlib.pyplot.plot`.
+        The line width of the curve, by default None.
     **kwargs
-        Additional keyword arguments to pass to the `matplotlib.pyplot.plot`.
+        Additional keyword arguments to be passed to the
+        `matplotlib.pyplot.plot` function.
     """
 
     kwargs.update(
@@ -287,7 +286,8 @@ def save(file_name: str, *, transparent=True, dpi=300, **kwargs) -> None:
         The resolution in dots per inch, by default 300. This will be omitted if
         saving to a vector format.
     **kwargs
-        Additional keyword arguments to pass to the `matplotlib.pyplot.savefig`
+        Additional keyword arguments to be passed to the
+        `matplotlib.figure.Figure.savefig` method.
     """
 
     kwargs.update({"transparent": transparent, "dpi": dpi})
diff --git a/tests/test_data.py b/tests/test_data.py
index b4d761b..a962e36 100644
--- a/tests/test_data.py
+++ b/tests/test_data.py
@@ -8,7 +8,7 @@ def d() -> Data:
     return Data([1, 2, 3])
 
 
-def test_data_sequence(d: Data) -> None:
+def test_data(d: Data) -> None:
     assert d.data == pytest.approx([3, 2, 1])