code: def nanpercentile(
      values, q, axis, na_value, mask, ndim, interpolation
  ):
      """
      Wraper for np.percentile that skips missing values.
  
      Parameters
      ----------
      values : array over which to find quantiles
      q : scalar or array of quantile indices to find
      axis : {0, 1}
      na_value : scalar
          value to return for empty or all-null values
      mask : ndarray[bool]
          locations in values that should be considered missing
      ndim : {1, 2}
      interpolation : str
  
      Returns
      -------
      quantiles : scalar or array
      """
      if not lib.is_scalar(mask) and mask.any():
          if ndim == 1:
              return _nanpercentile_1d(
                  values, mask, q, na_value, interpolation=interpolation
              )
          else:
              # for nonconsolidatable blocks mask is 1D, but values 2D
              if mask.ndim < values.ndim:
                  mask = mask.reshape(values.shape)
              if axis == 0:
                  values = values.T
                  mask = mask.T
              result = [
                  _nanpercentile_1d(
                      val, m, q, na_value, interpolation=interpolation
                  )
                  for (val, m) in zip(list(values), list(mask))
              ]
              result = np.array(
                  result, dtype=values.dtype, copy=False
              ).T
              return result
      else:
          return np.percentile(
              values, q, axis=axis, interpolation=interpolation
          )
  
imports: from distutils.version import LooseVersion
  import functools
  import itertools
  import operator
  import warnings
  import numpy
  from pandas._libs import iNaT, lib, tslibs
  import pandas.compat
  from pandas.core.dtypes.cast import _int64_max, maybe_upcast_putmask
  from pandas.core.dtypes.common import _get_dtype, is_any_int_dtype, is_bool_dtype, is_complex, is_complex_dtype, is_datetime64_dtype, is_datetime64tz_dtype, is_datetime_or_timedelta_dtype, is_float, is_float_dtype, is_integer, is_integer_dtype, is_numeric_dtype, is_object_dtype, is_scalar, is_timedelta64_dtype, pandas_dtype
  from pandas.core.dtypes.dtypes import DatetimeTZDtype
  from pandas.core.dtypes.missing import isna, na_value_for_dtype, notna
  import pandas.core.common
  from pandas.core.config import get_option
label_desc: Use image node_id 35 for calling a global function with example usage: nanpercentile(values, q, axis, na_value, mask, ndim, interpolation) and returns: np, _nanpercentile_1d, result