class_docstr: KeltnerChannel
  
  Keltner Channels are a trend following indicator used to identify reversals with channel breakouts and
  channel direction. Channels can also be used to identify overbought and oversold levels when the trend
  is flat.
  
  https://school.stockcharts.com/doku.php?id=technical_indicators:keltner_channels
  
  Args:
      high(pandas.Series): dataset 'High' column.
      low(pandas.Series): dataset 'Low' column.
      close(pandas.Series): dataset 'Close' column.
      window(int): n period.
      window_atr(int): n atr period. Only valid if original_version param is False.
      fillna(bool): if True, fill nan values.
      original_version(bool): if True, use original version as the centerline (SMA of typical price)
          if False, use EMA of close as the centerline. More info:
          https://school.stockcharts.com/doku.php?id=technical_indicators:keltner_channels
      multiplier(int): The multiplier has the most effect on the channel width. default is 2
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docstr: Keltner Channel Low Band
  
  Returns:
      pandas.Series: New feature generated.
docstr_tok: ["Keltner","Channel","Low","Band","Returns",":","pandas.Series",":","New","feature","generated","."]
code: def keltner_channel_lband(self) -> pd.Series:
      """Keltner Channel Low Band
  
      Returns:
          pandas.Series: New feature generated.
      """
      tp_low = self._check_fillna(self._tp_low, value=-1)
      return pd.Series(tp_low, name="kc_lband")
  
imports: import numpy
  import pandas
  from ta.utils import IndicatorMixin
label_desc: Use image node_id 5 for calling the KeltnerChannel obj's underlying member method code with example usage: obj.keltner_channel_lband() and returns: pd