
import pandas as pd


def prep_data(binned=False):
    url = "https://archive.ics.uci.edu/ml/machine-learning-databases/00374/energydata_complete.csv"

    dta = pd.read_csv(url,
                      header=0,
                      skipinitialspace=True)

    dta = dta.drop(["date", "rv1", "rv2"], axis=1)
    dta.Appliances.describe()

    bins = [0, 60, 2000]
    labels = [0, 1]
    dta['Appliances'] = pd.cut(dta['Appliances'], bins=bins, labels=labels)
    dta['Appliances'] = dta['Appliances'].astype("int64")

    if binned:
        for col in list(dta)[1:]:
            dta[col] = pd.qcut(dta[col], q=4, labels=False, duplicates='drop')
            dta[col] = dta[col].astype("int64")

        # dta.to_pickle("dta_binned.pkl")

    return dta

# dta.to_pickle("dta.pkl")
