code: def fftfreq(n: int, d: float = 1.0) -> np.ndarray:
      """
      Return the Discrete Fourier Transform sample frequencies.
  
      Args:
          n : int
              Window length.
          d : scalar, optional
              Sample spacing (inverse of the sampling rate). Defaults to 1.
  
      Returns:
          f : ndarray
              Array of length `n` containing the sample frequencies.
      """
      val = 1.0 / (n * d)
      results = np.empty(n, int)
      N = (n - 1) // 2 + 1
      p1 = np.arange(0, N, dtype=int)
      results[:N] = p1
      p2 = np.arange(-(n // 2), 0, dtype=int)
      results[N:] = p2
      return results * val
  
file_path: ydata-profiling/src/ydata_profiling/model/pandas/describe_timeseries_pandas.py
imports: from typing import Any, Dict, Tuple
  import numpy
  import pandas
  from scipy.fft import _pocketfft
  from scipy.signal import find_peaks
  from statsmodels.tsa.stattools import adfuller
  from ydata_profiling.config import Settings
  from ydata_profiling.model.summary_algorithms import describe_numeric_1d, describe_timeseries_1d, series_handle_nulls, series_hashable
label_desc: Use image node_id 2 for calling a global function with example usage: fftfreq(n, d) and returns: unknown