code: def _return_fft(data: pd.Series) -> Tuple[np.ndarray, np.ndarray]:
      """Returns the FFT data corresponding to the `data`
  
      Parameters
      ----------
      data : pd.Series
          Data for which the FFT data must be obtained
  
      Returns
      -------
      Tuple[np.ndarray, np.ndarray]
          Frequency, Amplitude
      """
      sample_spacing = 1
      fft_values = fft(data.values)
      psd_values = np.abs(fft_values) ** 2
      fft_frequencies = fftfreq(len(psd_values), 1.0 / sample_spacing)
      pos_freq_ix = fft_frequencies > 0
      freq = fft_frequencies[pos_freq_ix]
      ampl = 10 * np.log10(psd_values[pos_freq_ix])
      return freq, ampl
  
imports: from math import ceil
  from typing import Any, Dict, List, Optional, Tuple, Union
  import matplotlib
  import matplotlib.pyplot
  import numpy
  import pandas
  import plotly.express
  import plotly.graph_objects
  import plotly.io
  from plotly.colors import DEFAULT_PLOTLY_COLORS
  from plotly.subplots import make_subplots
  from scipy.fft import fft, fftfreq
  from scipy.signal import periodogram
  from statsmodels.graphics.gofplots import qqplot
  from statsmodels.tsa.seasonal import STL, seasonal_decompose
  from statsmodels.tsa.stattools import acf, ccf, pacf
  from pycaret.internal.logging import get_logger
  from pycaret.utils.generic import _resolve_dict_keys
  from pycaret.utils.time_series import TSAllowedPlotDataTypes
label_desc: Use image node_id 10 for calling a global function with example usage: _return_fft(data) and returns: freq,  ampl