Hello Guys , I want to plot some EEG signal that I obtained from a data set. But I’m new in scipy so my task is:

- Preprocess the EEG recordings by applying a high-pass filter above 1 Hz and a low-pass filter below 50 Hz.
- Downsample the EEG signal from 256 Hz to 128 Hz to improve computational efficiency.
- Plot the spectrogram for channels TP9 and TP10.

But I have a error " ValueError: “Length of values does not match length of index.”

Code:

```
# Extract the desired channels (TP9 and TP10)
channels = ['TP9', 'TP10']
eeg_data = eeg_df[channels]
# Convert the timestamps to time in seconds
sampling_rate = 256 # Sampling rate of the EEG data in Hz
time_seconds = eeg_df['timestamps'] / sampling_rate
# Preprocess the EEG signals
for channel in channels:
# Apply high-pass filter above 1 Hz and low-pass filter below 50 Hz
b, a = signal.butter(4, [1, 50], btype='bandpass', fs=sampling_rate)
eeg_data[channel] = signal.filtfilt(b, a, eeg_data[channel])
# Downsample the signal from 256 to 128 Hz
new_length = len(eeg_data[channel]) // 2
eeg_data[channel] = signal.resample(eeg_data[channel], new_length)
# Define the parameters for the spectrogram
window = 'hann' # Windowing function
nperseg = 128 # Length of each segment
noverlap = 64 # Overlap between segments
nfft = 128 # Number of points for the FFT
# Compute the spectrogram for each channel
frequencies, times, spectrogram_TP9 = signal.spectrogram(eeg_data['TP9'], fs=sampling_rate / 2, window=window,
nperseg=nperseg, noverlap=noverlap, nfft=nfft)
_, _, spectrogram_TP10 = signal.spectrogram(eeg_data['TP10'], fs=sampling_rate / 2, window=window,
nperseg=nperseg, noverlap=noverlap, nfft=nfft)
```

So, i would like to know If I miss some step because when I want to implement my code it does not run and said the error that I mentioned before it.