# Import libraries
import functools as ft
import pandas as pd

# Set file paths
file_path = '<YOUR_DATA_PATH>/'
input_file_path = file_path + 'data_for_model_e_columns/'


def read_data(file):
    """
    Read in data source
    --------
    :param file: string filename
    :return: dataframe
    """
    df = pd.read_csv(file)
    return df


def main():
    # Read in data
    RC_SU1_IDs_file = input_file_path + "RC_SU1_IDs.csv"
    steps_file = input_file_path + "step_groupings.csv"
    hr_file = input_file_path + "hr_groupings.csv"
    awake_asleep_file = input_file_path + "awake_asleep_groupings.csv"
    steps_2000_file = input_file_path + "steps_2000.csv"

    RC_SU1_IDs = read_data(RC_SU1_IDs_file)
    Steps = read_data(steps_file)
    hr_file = read_data(hr_file)
    awake_asleep = read_data(awake_asleep_file)
    steps_2000 = read_data(steps_2000_file)

    # Merge groupings columns and RC_IDs
    dfs = [RC_SU1_IDs, Steps, hr_file, awake_asleep, steps_2000]
    df_final = ft.reduce(lambda left, right: pd.merge(left, right, on='Study_ID', how="outer"), dfs)
    
    # Save this dataframe as a csv file
    df_final.to_csv(file_path + 'Fitbit_groups.csv')


main()