class_docstr: TimeSeries plot, displaying each column in the input dataframe as a curve over time.
class_docstr_tok: ["TimeSeries","plot",",","displaying","each","column","in","the","input","dataframe","as","a","curve","over","time","."]
code: def _create_figure(self) -> Any:
      pfix = self._pfix
      df = (
          self.df if isinstance(self.df, pd.DataFrame) else self.df.data
      )
      columns = pfix(self.columns, df.columns)
      ncols = len(columns)
      labels = pfix(self.labels, columns, fill=columns)
      colors = pfix(
          self.colors, self.PALETTE, None, self.PALETTE, ncols
      )
      line = [1.5] * ncols
      line = pfix(self.line_width, line, None, line, ncols)
      fig = go.Figure()
      for col, label, color, l_width in zip(
          columns, labels, colors, line
      ):
          fig.add_trace(
              go.Scatter(
                  x=df.index.tolist(),
                  y=df[col].tolist(),
                  name=label,
                  meta={
                      "label_xaxis": self.label_xaxis or "Date",
                      "label_yaxis": self.label_yaxis,
                      "column": col,
                      "label": label,
                      "color": color,
                  },
                  mode="lines",
                  line={"color": color, "width": l_width},
                  hovertemplate=self.hovertemplate,
              )
          )
  
      return fig
  
file_path: tslumen/tslumen/plot/interactive/line.py
imports: from typing import Union, Optional, Any
  import pandas
  from tslumen.plot.interactive.base import VizBase, go, make_subplots
label_desc: Use image node_id 3 for calling the TS obj's underlying member method code with example usage: obj._create_figure() and returns: fig