# Path: insults/util.py
# def data_file(category, name=None):
#     """
#     Create a filename within Data
#     """
#     if name == None:
#         return os.path.join(os.path.dirname(__file__), 'data', category)
#     else:
#         return os.path.join(os.path.dirname(__file__), 'data', category, name)


import pandas as pd
import numpy as np
import re
from insults.util import data_file
from insults.nn_model.util import binarize, binarize_outshape, strip_html, clean



def load_data(data_fp,  delimiter="\t"):
    return pd.read_csv(data_fp, header=0, delimiter=delimiter, quoting=3)

def load_insults_data(train, test):
    df1 = pd.read_table(data_file('Inputs','train.csv'), sep=',')

# Path: insults/util.py
# def data_file(category, name=None):
#     """
#     Create a filename within Data
#     """
#     if name == None:
#         return os.path.join(os.path.dirname(__file__), 'data', category)
#     else:
#         return os.path.join(os.path.dirname(__file__), 'data', category, name)


# Path: insults/models/nn_model/plumbing.py
import pandas as pd
import numpy as np
import re
from insults.util import data_file
from insults.nn_model.util import binarize, binarize_outshape, strip_html, clean




def load_data(data_fp,  delimiter="\t"):
    return pd.read_csv(data_fp, header=0, delimiter=delimiter, quoting=3)

def load_insults_data(train, test):
    df1 = pd.read_table(data_file('Inputs','train.csv'), sep=',')

    df2 = pd.read_table(data_file('Inputs','test_with_solutions.csv'), sep=',')