# Preprocess your csv files:

Step:

read the csv file, and transform into a pandas DataFrame
regex the dataframe, format the string
split the dataframe, remove useless columns (col_to_remove is a parameter), split into x, and y dataframes
fill the dataframe, fill the NaN value using a clustering approach
dummify the dataframe, transform categorics variables into dummies
datify the dataframe, build new columns based on the datetime
featurize the dataframe, make feature engineering like ploynomial featuring, derivate featuring, and transform featuring
then scale the dataframe