docstr: Convert strings in *value* to floats using mapping information stored
  in the *unit* object.
  
  Parameters
  ----------
  value : str or iterable
      Value or list of values to be converted.
  unit : `.UnitData`
      An object mapping strings to integers.
  axis : `~matplotlib.axis.Axis`
      The axis on which the converted value is plotted.
  
      .. note:: *axis* is unused.
  
  Returns
  -------
  float or `~numpy.ndarray` of float
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code: def convert(value, unit, axis):
      """
      Convert strings in *value* to floats using mapping information stored
      in the *unit* object.
  
      Parameters
      ----------
      value : str or iterable
          Value or list of values to be converted.
      unit : `.UnitData`
          An object mapping strings to integers.
      axis : `~matplotlib.axis.Axis`
          The axis on which the converted value is plotted.
  
          .. note:: *axis* is unused.
  
      Returns
      -------
      float or `~numpy.ndarray` of float
      """
      if unit is None:
          raise ValueError(
              "Missing category information for StrCategoryConverter; "
              "this might be caused by unintendedly mixing categorical and "
              "numeric data"
          )
      StrCategoryConverter._validate_unit(unit)
      # dtype = object preserves numerical pass throughs
      values = np.atleast_1d(np.array(value, dtype=object))
      # force an update so it also does type checking
      unit.update(values)
      return np.vectorize(unit._mapping.__getitem__, otypes=[float])(
          values
      )
  
imports: from collections import OrderedDict
  import dateutil.parser
  import itertools
  import logging
  import numpy
  from matplotlib import _api, ticker, units
label_desc: Use image node_id 1 for calling the StrCategoryConverter obj's underlying member method code with example usage: obj.convert(value, unit, axis) and returns: np