code: def _pandas(mode, trendline_options, x_raw, y, non_missing):
      modes = dict(
          rolling="Rolling",
          ewm="Exponentially Weighted",
          expanding="Expanding",
      )
      trendline_options = trendline_options.copy()
      function_name = trendline_options.pop("function", "mean")
      function_args = trendline_options.pop("function_args", dict())
      series = pd.Series(y, index=x_raw)
      agg = getattr(series, mode)  # e.g. series.rolling
      agg_obj = agg(**trendline_options)  # e.g. series.rolling(**opts)
      function = getattr(
          agg_obj, function_name
      )  # e.g. series.rolling(**opts).mean
      y_out = function(
          **function_args
      )  # e.g. series.rolling(**opts).mean(**opts)
      y_out = y_out[non_missing]
      hover_header = "<b>%s %s trendline</b><br><br>" % (
          modes[mode],
          function_name,
      )
      return y_out, hover_header, None
  
imports: import pandas
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: _pandas(mode, trendline_options, x_raw, y, non_missing) and returns: y_out,  hover_header,  None