code: def _sequence_of_pandas_to_pydf(
      first_element: pd.Series[Any] | pd.DatetimeIndex,
      data: Sequence[Any],
      schema: SchemaDefinition | None,
      schema_overrides: SchemaDict | None,
      **kwargs: Any,
  ) -> PyDataFrame:
      if schema is None:
          column_names: list[str] = []
      else:
          column_names, schema_overrides = _unpack_schema(
              schema, schema_overrides=schema_overrides, n_expected=1
          )
  
      schema_overrides = schema_overrides or {}
      data_series: list[PySeries] = []
      for i, s in enumerate(data):
          name = column_names[i] if column_names else s.name
          dtype = schema_overrides.get(name, None)
          pyseries = pandas_to_pyseries(name=name, values=s)
          if dtype is not None and dtype != pyseries.dtype():
              pyseries = pyseries.cast(dtype, strict=True)
          data_series.append(pyseries)
  
      return PyDataFrame(data_series)
  
imports: from __future__ import annotations
  import contextlib
  import warnings
  from datetime import date, datetime, time, timedelta
  from decimal import Decimal
  from functools import lru_cache, singledispatch
  from itertools import islice, zip_longest
  from operator import itemgetter
  from sys import version_info
  from typing import TYPE_CHECKING, Any, Callable, Generator, Iterable, Iterator, Mapping, MutableMapping, Sequence, get_type_hints
  import polars._reexport
  from polars import functions
  from polars.datatypes import INTEGER_DTYPES, N_INFER_DEFAULT, TEMPORAL_DTYPES, Boolean, Categorical, Date, Datetime, Duration, Enum, List, Null, Object, String, Struct, Time, UInt32, Unknown, dtype_to_py_type, is_polars_dtype, numpy_char_code_to_dtype, py_type_to_dtype
  from polars.datatypes.constructor import numpy_type_to_constructor, numpy_values_and_dtype, polars_type_to_constructor, py_type_to_constructor
  from polars.dependencies import _NUMPY_AVAILABLE, _check_for_numpy, _check_for_pandas, _check_for_pydantic, dataclasses, pydantic
  from polars.dependencies import numpy
  from polars.dependencies import pandas
  from polars.dependencies import pyarrow
  from polars.exceptions import ComputeError, ShapeError, TimeZoneAwareConstructorWarning
  from polars.utils._wrap import wrap_df, wrap_s
  from polars.utils.meta import get_index_type, threadpool_size
  from polars.utils.various import _is_generator, arrlen, find_stacklevel, parse_version, range_to_series
label_desc: Use image node_id 32 for calling a global function with example usage: _sequence_of_pandas_to_pydf(first_element, data, schema, schema_overrides) and returns: PyDataFrame