code: def series_corr(series, other, method="pearson", min_periods=None):
      """
      Compute correlation with `other` Series, excluding missing values.
  
      Parameters
      ----------
      other : Series
          Series with which to compute the correlation.
      method : {'pearson', 'kendall', 'spearman'} or callable
          Method used to compute correlation:
  
          - pearson : Standard correlation coefficient
          - kendall : Kendall Tau correlation coefficient
          - spearman : Spearman rank correlation
          - callable: Callable with input two 1d ndarrays and returning a float.
  
          .. note::
              kendall, spearman and callables not supported on multiple chunks yet.
  
      min_periods : int, optional
          Minimum number of observations needed to have a valid result.
  
      Returns
      -------
      float
          Correlation with other.
  
      See Also
      --------
      DataFrame.corr : Compute pairwise correlation between columns.
      DataFrame.corrwith : Compute pairwise correlation with another
          DataFrame or Series.
  
      Examples
      --------
      >>> import mars.dataframe as md
      >>> s1 = md.Series([.2, .0, .6, .2])
      >>> s2 = md.Series([.3, .6, .0, .1])
      >>> s1.corr(s2, method='pearson').execute()
      -0.8510644963469898
      """
      op = DataFrameCorr(
          other=other, method=method, min_periods=min_periods
      )
      return op(series)
  
imports: import numpy
  import pandas
  from ...None import opcodes
  from ...core import ENTITY_TYPE, recursive_tile
  from ...serialization.serializables import BoolField, AnyField, KeyField, Int32Field
  from ...tensor.utils import filter_inputs
  from ...utils import has_unknown_shape
  from ..core import SERIES_TYPE, DATAFRAME_TYPE
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import build_empty_df, validate_axis, parse_index
label_desc: Use image node_id 4 for calling a global function with example usage: series_corr(series, other, method, min_periods) and returns: op