class_docstr: Time Series tab: Smoothing
class_docstr_tok: ["Time","Series","tab",":","Smoothing"]
code: def __init__(
      self, name: str, result: Dict[str, Any], ser: pd.Series
  ) -> None:
      _ = (name, ser)
      for var in ["rolling_avg", "supsmu", "lowess"]:
          df = result.get(var, None)
          if df is None:
              plot = None
          else:
              plot = TS(
                  df=df,
                  figsize=(6.8, 2),
                  line_width=[3],
                  colors=["#cecce0"] + TS.PALETTE[1:],
              )
          setattr(self, f"plot_{var}", plot)
  
imports: from typing import Dict, Any, Optional
  from pprint import pformat
  import pandas
  import yaml
  import tslumen
  from tslumen.misc import lazyproperty
  from tslumen.scheduling import Scheduler
  from tslumen.profile import BundledResult
  from tslumen import jinja_utils
  from tslumen.report.html.base import HtmlBlock
  from tslumen.plot.static import TS, TSStack, Distribution, BoxPlot, LagCorrelation, LagMatrix, Radar, Heatmap, ScatterMatrix, GrangerMatrix, GrangerGraph
label_desc: Use image node_id 1 to create a new TabTSSmoothing object from inherited base classes: HtmlBlock with example: obj = TabTSSmoothing(name, result, ser)