class_docstr: Object that can be rendered by HiPlot. It essential contains a list of metrics, but also some options on how to render it.
  
  See :meth:`Experiment.display` to display an :class:`Experiment` in an ipython notebook.
  
  :ivar datapoints: All the measurements we have. One datapoint corresponds to one line in the parallel plot and to one line in the table.
  :ivar parameters_definition: Characteristics of the columns (ordering, type, etc...)
  :ivar colormap: Colormap to use
  :ivar colorby: Default column to color by
  :ivar weightcolumn: If rows have different weights, use this column as the weight (default to 1 if not specified)
  :ivar enabledDisplays: Ordered displays to enable (by default all are enabled)
  
  :Example:
  
  .. code-block:: python
  
      import hiplot as hip
      data = [{'param': 1, 'loss': 10, 'hidden_field': 'value1', 'c': 'red'},
          {'param': 2, 'loss': 5, 'hidden_field': 'value2', 'c': 'black'}]
      exp = hip.Experiment.from_iterable(data)
docstr: Displays an experiment in an ipython notebook.
  
  :param force_full_width: allows to force to have 100% width on Jupyter Notebooks only.
  :param store_state_key: a string identifier for the HiPlot instance.
      If not ``None``, HiPlot will store dynamic modifications (removing/reordering columns...)
      in the URL, and restore them when calling ``display`` with the same value for ``store_state_key`` - see :ref:`tutoNotebookState`
  :returns: An :class:`ExperimentDisplayed` object that can be used to interact with the visualization
      - only implemented for Jupyter notebook.
      See :ref:`tutonotebookdisplayedexperiment`
docstr_tok: ["Displays","an","experiment","in","an","ipython","notebook",".",":","param","force_full_width",":","allows","to","force","to","have","100","%","width","on","Jupyter","Notebooks","only",".",":","param","store_state_key",":","a","string","identifier","for","the","HiPlot","instance",".","If","not","``","None","``",",","HiPlot","will","store","dynamic","modifications","(","removing\/reordering","columns","...",")","in","the","URL",",","and","restore","them","when","calling","``","display","``","with","the","same","value","for","``","store_state_key","``","-","see",":","ref",":","`","tutoNotebookState","`",":","returns",":","An",":","class",":","`","ExperimentDisplayed","`","object","that","can","be","used","to","interact","with","the","visualization","-","only","implemented","for","Jupyter","notebook",".","See",":","ref",":","`","tutonotebookdisplayedexperiment","`"]
code: def display(
      self,
      force_full_width: bool = False,
      store_state_key: tp.Optional[str] = None,
      **kwargs: tp.Any,
  ) -> "ExperimentDisplayed":
      """
      Displays an experiment in an ipython notebook.
  
      :param force_full_width: allows to force to have 100% width on Jupyter Notebooks only.
      :param store_state_key: a string identifier for the HiPlot instance.
          If not ``None``, HiPlot will store dynamic modifications (removing/reordering columns...)
          in the URL, and restore them when calling ``display`` with the same value for ``store_state_key`` - see :ref:`tutoNotebookState`
      :returns: An :class:`ExperimentDisplayed` object that can be used to interact with the visualization
          - only implemented for Jupyter notebook.
          See :ref:`tutonotebookdisplayedexperiment`
      """
      from .streamlit_helpers import (
          _StreamlitHelpers,
      )  # pylint: disable=cyclic-import
  
      if not _is_running_ipython():
          if _StreamlitHelpers.is_running_within_streamlit():
              raise RuntimeError(
                  r"""`experiment.display` can only be called with ipython.
  It appears that you are trying to create a HiPlot visualization in Streamlit: you should use `display_st`"""
              )
          raise RuntimeError(
              r"""`display` can only be called on an ipython context. Are you in a notebook?
  - To render an experiment to HTML, use `experiment.to_html(file_name)` or `html_page = experiment.to_html()`
  - To render an experiment in Streamlit, use `experiment.display_st`"""
          )
      from .ipython import display_exp  # pylint: disable=cyclic-import
  
      self.validate()
      return display_exp(
          self,
          force_full_width=force_full_width,
          store_state_url=store_state_key,
          **kwargs,
      )
  
imports: import csv
  import uuid
  import json
  import codecs
  import warnings
  from abc import ABCMeta, abstractmethod
  from enum import Enum
  from collections import defaultdict
  from pathlib import Path
  import typing
label_desc: Use image node_id 3 for calling the Experiment obj's underlying member method code with example usage: obj.display(force_full_width, store_state_key) and returns: display_exp