[docs][python] update types in docstring (#6897)

* Update basic.py

* Update sklearn.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update sklearn.py

* Update sklearn.py

* Update sklearn.py

python-package/lightgbm/basic.py

@@ -1100,7 +1100,7 @@ class _InnerPredictor:
 
         Parameters
         ----------
-        data : str, pathlib.Path, numpy array, pandas DataFrame, pyarrow Table or scipy.sparse
+        data : str, pathlib.Path, numpy array, pandas DataFrame, scipy.sparse or pyarrow Table
             Data source for prediction.
             If str or pathlib.Path, it represents the path to a text file (CSV, TSV, or LibSVM).
         start_iteration : int, optional (default=0)
@@ -2596,7 +2596,7 @@ class Dataset:
 
         Parameters
         ----------
-        data : str, pathlib.Path, numpy array, pandas DataFrame, scipy.sparse, Sequence, list of Sequence or list of numpy array
+        data : str, pathlib.Path, numpy array, pandas DataFrame, scipy.sparse, Sequence, list of Sequence, list of numpy array or pyarrow Table
             Data source of Dataset.
             If str or pathlib.Path, it represents the path to a text file (CSV, TSV, or LibSVM) or a LightGBM Dataset binary file.
         label : list, numpy 1-D array, pandas Series / one-column DataFrame, pyarrow Array, pyarrow ChunkedArray or None, optional (default=None)
@@ -2741,7 +2741,7 @@ class Dataset:
         ----------
         field_name : str
             The field name of the information.
-        data : list, list of lists (for multi-class task), numpy array, pandas Series, pandas DataFrame (for multi-class task), pyarrow Array, pyarrow ChunkedArray or None
+        data : list, list of lists (for multi-class task), numpy array, pandas Series, pandas DataFrame (for multi-class task), pyarrow Array, pyarrow ChunkedArray, pyarrow Table (for multi-class task) or None
             The data to be set.
 
         Returns
@@ -3214,7 +3214,7 @@ class Dataset:
 
         Returns
         -------
-        label : list, numpy 1-D array, pandas Series / one-column DataFrame or None
+        label : list, numpy 1-D array, pandas Series / one-column DataFrame, pyarrow Array, pyarrow ChunkedArray or None
             The label information from the Dataset.
             For a constructed ``Dataset``, this will only return a numpy array.
         """
@@ -3227,7 +3227,7 @@ class Dataset:
 
         Returns
         -------
-        weight : list, numpy 1-D array, pandas Series or None
+        weight : list, numpy 1-D array, pandas Series, pyarrow Array, pyarrow ChunkedArray or None
             Weight for each data point from the Dataset. Weights should be non-negative.
             For a constructed ``Dataset``, this will only return ``None`` or a numpy array.
         """
@@ -3240,7 +3240,7 @@ class Dataset:
 
         Returns
         -------
-        init_score : list, list of lists (for multi-class task), numpy array, pandas Series, pandas DataFrame (for multi-class task), or None
+        init_score : list, list of lists (for multi-class task), numpy array, pandas Series, pandas DataFrame (for multi-class task), pyarrow Array, pyarrow ChunkedArray, pyarrow Table (for multi-class task) or None
             Init score of Booster.
             For a constructed ``Dataset``, this will only return ``None`` or a numpy array.
         """
@@ -3253,7 +3253,7 @@ class Dataset:
 
         Returns
         -------
-        data : str, pathlib.Path, numpy array, pandas DataFrame, scipy.sparse, Sequence, list of Sequence or list of numpy array or None
+        data : str, pathlib.Path, numpy array, pandas DataFrame, scipy.sparse, Sequence, list of Sequence, list of numpy array, pyarrow Table or None
             Raw data used in the Dataset construction.
         """
         if self._handle is None:
@@ -3286,7 +3286,7 @@ class Dataset:
 
         Returns
         -------
-        group : list, numpy 1-D array, pandas Series or None
+        group : list, numpy 1-D array, pandas Series, pyarrow Array, pyarrow ChunkedArray or None
             Group/query data.
             Only used in the learning-to-rank task.
             sum(group) = n_samples.
@@ -4670,7 +4670,7 @@ class Booster:
 
         Parameters
         ----------
-        data : str, pathlib.Path, numpy array, pandas DataFrame, pyarrow Table or scipy.sparse
+        data : str, pathlib.Path, numpy array, pandas DataFrame, scipy.sparse or pyarrow Table
             Data source for prediction.
             If str or pathlib.Path, it represents the path to a text file (CSV, TSV, or LibSVM).
         start_iteration : int, optional (default=0)
@@ -4751,7 +4751,7 @@ class Booster:
 
         Parameters
         ----------
-        data : str, pathlib.Path, numpy array, pandas DataFrame, scipy.sparse, Sequence, list of Sequence or list of numpy array
+        data : str, pathlib.Path, numpy array, pandas DataFrame, scipy.sparse, Sequence, list of Sequence, list of numpy array or pyarrow Table
             Data source for refit.
             If str or pathlib.Path, it represents the path to a text file (CSV, TSV, or LibSVM).
         label : list, numpy 1-D array, pandas Series / one-column DataFrame, pyarrow Array or pyarrow ChunkedArray

python-package/lightgbm/sklearn.py

@@ -1076,10 +1076,10 @@ class LGBMModel(_LGBMModelBase):
     fit.__doc__ = (
         _lgbmmodel_doc_fit.format(
             X_shape="numpy array, pandas DataFrame, scipy.sparse, list of lists of int or float of shape = [n_samples, n_features]",
-            y_shape="numpy array, pandas DataFrame, pandas Series, list of int or float of shape = [n_samples]",
-            sample_weight_shape="numpy array, pandas Series, list of int or float of shape = [n_samples] or None, optional (default=None)",
-            init_score_shape="numpy array, pandas DataFrame, pandas Series, list of int or float of shape = [n_samples] or shape = [n_samples * n_classes] (for multi-class task) or shape = [n_samples, n_classes] (for multi-class task) or None, optional (default=None)",
-            group_shape="numpy array, pandas Series, list of int or float, or None, optional (default=None)",
+            y_shape="numpy array, pandas DataFrame, pandas Series, list of int or float, pyarrow Array, pyarrow ChunkedArray of shape = [n_samples]",
+            sample_weight_shape="numpy array, pandas Series, list of int or float, pyarrow Array, pyarrow ChunkedArray of shape = [n_samples] or None, optional (default=None)",
+            init_score_shape="numpy array, pandas DataFrame, pandas Series, list of int or float, list of lists, pyarrow Array, pyarrow ChunkedArray, pyarrow Table of shape = [n_samples] or shape = [n_samples * n_classes] (for multi-class task) or shape = [n_samples, n_classes] (for multi-class task) or None, optional (default=None)",
+            group_shape="numpy array, pandas Series, pyarrow Array, pyarrow ChunkedArray, list of int or float, or None, optional (default=None)",
             eval_sample_weight_shape="list of array (same types as ``sample_weight`` supports), or None, optional (default=None)",
             eval_init_score_shape="list of array (same types as ``init_score`` supports), or None, optional (default=None)",
             eval_group_shape="list of array (same types as ``group`` supports), or None, optional (default=None)",