Non Linear, Regression, Data Science, Python, Least Squares.
a cross-sectional data, we will randomly select 90% of the data rows as our training data and the remaining 10% as our test data: mask = np.random.rand(len(df)) < 0.9 df_train = df[mask] df_test = df[~mask] print('Training data set length='+str(len(df_train))) print('Testing data set