code: def _concat_sparse(to_concat, axis=0, typs=None):
      """
      provide concatenation of an sparse/dense array of arrays each of which is a
      single dtype
  
      Parameters
      ----------
      to_concat : array of arrays
      axis : axis to provide concatenation
      typs : set of to_concat dtypes
  
      Returns
      -------
      a single array, preserving the combined dtypes
      """
  
      from pandas.core.arrays import SparseArray
  
      fill_values = [
          x.fill_value for x in to_concat if isinstance(x, SparseArray)
      ]
      fill_value = fill_values[0]
  
      # TODO: Fix join unit generation so we aren't passed this.
      to_concat = [
          x
          if isinstance(x, SparseArray)
          else SparseArray(x.squeeze(), fill_value=fill_value)
          for x in to_concat
      ]
  
      return SparseArray._concat_same_type(to_concat)
  
file_path: catboost/contrib/python/pandas/py2/pandas/core/dtypes/concat.py
imports: import numpy
  from pandas._libs import tslib, tslibs
  from pandas.core.dtypes.common import _NS_DTYPE, _TD_DTYPE, is_bool_dtype, is_categorical_dtype, is_datetime64_dtype, is_datetime64tz_dtype, is_dtype_equal, is_extension_array_dtype, is_object_dtype, is_sparse, is_timedelta64_dtype
  from pandas.core.dtypes.generic import ABCDatetimeArray, ABCDatetimeIndex, ABCIndexClass, ABCPeriodIndex, ABCRangeIndex, ABCSparseDataFrame, ABCTimedeltaIndex
  from pandas import compat
label_desc: Use image node_id 13 for calling a global function with example usage: _concat_sparse(to_concat, axis, typs) and returns: SparseArray