Electroencephalography (EEG) has been used to determine how nerve impulses impact the chemical variations in the brain. The feature extraction and classification approaches to detecting and foreseeing various brain illnesses heavily rely on the EEG analysis. Electroencephalogram systems and pattern analysis originated as a result of detecting the electrical potentials of the brain, a technique that was presumably primarily motivated by epileptic seizures. Seizures may be predicted, which is crucial since it enables medical professionals to treat epileptic patients in a timely manner and improves quality of life. Epileptic seizures are identified as the abrupt aberrant electrical impulses in the cerebral cortex that set regular EEG waves apart from epileptic EEG waves. This paper’s objective is to identify a key characteristic of both pre-ictal (before) and ictal (during) seizures, compare those traits, and analyze them. The Neurology & Sleep Centre in Hauz Khas, New Delhi, EEG dataset has also been used in trials to compare 19 features for EEG epileptic before and through seizure signals. EEG signals during seizure outbreaks show huge feature values; of particular note are the 12 large feature values from the ictal2 seizure stage, which were close to 63.15%, and the 4 high feature values from the ictal3 epilepsy stage, which were 21%.