class_docstr: Series/Frames plotting accessor and method.
  
  Uses the backend specified by the
  option ``plotting.backend``. By default, plotly is used.
  
  Plotting methods can also be accessed by calling the accessor as a method
  with the ``kind`` argument:
  ``s.plot(kind='hist')`` is equivalent to ``s.plot.hist()``
docstr: Draw one histogram of the DataFrame’s columns.
  A `histogram`_ is a representation of the distribution of data.
  This function calls :meth:`plotting.backend.plot`,
  on each series in the DataFrame, resulting in one histogram per column.
  
  .. _histogram: https://en.wikipedia.org/wiki/Histogram
  
  Parameters
  ----------
  bins : integer or sequence, default 10
      Number of histogram bins to be used. If an integer is given, bins + 1
      bin edges are calculated and returned. If bins is a sequence, it gives
      bin edges, including left edge of first bin and right edge of last
      bin. In this case, bins are returned unmodified.
  **kwds
      All other plotting keyword arguments to be passed to
      plotting backend.
  
  Returns
  -------
  :class:`plotly.graph_objs.Figure`
      Return an custom object when ``backend!=plotly``.
      Return an ndarray when ``subplots=True`` (matplotlib-only).
  
  Examples
  --------
  Basic plot.
  
  For Series:
  
  .. plotly::
  
      >>> s = ps.Series([1, 3, 2])
      >>> s.plot.hist()  # doctest: +SKIP
  
  For DataFrame:
  
  .. plotly::
  
      >>> df = pd.DataFrame(
      ...     np.random.randint(1, 7, 6000),
      ...     columns=['one'])
      >>> df['two'] = df['one'] + np.random.randint(1, 7, 6000)
      >>> df = ps.from_pandas(df)
      >>> df.plot.hist(bins=12, alpha=0.5)  # doctest: +SKIP
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code: def hist(self, bins=10, **kwds):
      """
      Draw one histogram of the DataFrame’s columns.
      A `histogram`_ is a representation of the distribution of data.
      This function calls :meth:`plotting.backend.plot`,
      on each series in the DataFrame, resulting in one histogram per column.
  
      .. _histogram: https://en.wikipedia.org/wiki/Histogram
  
      Parameters
      ----------
      bins : integer or sequence, default 10
          Number of histogram bins to be used. If an integer is given, bins + 1
          bin edges are calculated and returned. If bins is a sequence, it gives
          bin edges, including left edge of first bin and right edge of last
          bin. In this case, bins are returned unmodified.
      **kwds
          All other plotting keyword arguments to be passed to
          plotting backend.
  
      Returns
      -------
      :class:`plotly.graph_objs.Figure`
          Return an custom object when ``backend!=plotly``.
          Return an ndarray when ``subplots=True`` (matplotlib-only).
  
      Examples
      --------
      Basic plot.
  
      For Series:
  
      .. plotly::
  
          >>> s = ps.Series([1, 3, 2])
          >>> s.plot.hist()  # doctest: +SKIP
  
      For DataFrame:
  
      .. plotly::
  
          >>> df = pd.DataFrame(
          ...     np.random.randint(1, 7, 6000),
          ...     columns=['one'])
          >>> df['two'] = df['one'] + np.random.randint(1, 7, 6000)
          >>> df = ps.from_pandas(df)
          >>> df.plot.hist(bins=12, alpha=0.5)  # doctest: +SKIP
      """
      return self(kind="hist", bins=bins, **kwds)
  
imports: import importlib
  import pandas
  import numpy
  from pandas.core.base import PandasObject
  from pandas.core.dtypes.inference import is_integer
  from pyspark.ml.feature import Bucketizer
  from pyspark.mllib.stat import KernelDensity
  from pyspark.sql import functions
  from pyspark.pandas.missing import unsupported_function
  from pyspark.pandas.config import get_option
  from pyspark.pandas.utils import name_like_string
label_desc: Use image node_id 9 for calling the PandasOnSparkPlotAccessor obj's underlying member method code with example usage: obj.hist(bins) and returns: self