The Python Toolbox for Neurophysiological Signal Processing
NeuroKit
The Python Toolbox for Neurophysiological Signal Processing
This package is the continuation of NeuroKit 1. It’s a user-friendly package providing easy access to advanced biosignal processing routines. Researchers and clinicians without extensive knowledge of programming or biomedical signal processing can analyze physiological data with only two lines of code.
Quick Example
import neurokit2 as nk
# Download example data
data = nk.data("bio_eventrelated_100hz")
# Preprocess the data (filter, find peaks, etc.)
processed_data, info = nk.bio_process(ecg=data["ECG"], rsp=data["RSP"], eda=data["EDA"], sampling_rate=100)
# Compute relevant features
results = nk.bio_analyze(processed_data, sampling_rate=100)
And boom  your analysis is done 
Installation
You can install NeuroKit2 from PyPI
pip install neurokit2
or conda-forge
conda install -c conda-forge neurokit2
If you’re not sure what to do,