application_vnd.jupyter.stderr_output_1.png
import os

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import numpy as np
import pandas as pd
import os

def getFiles():
    """ Dictonary to get the right Files"""
    dict = {}
    for dirname, _, filenames in os.walk('/kaggle/input'):
        for filename in filenames:
            dict[filename[0:filename.find('.')]] = pd.read_csv(os.path.join(dirname, filename))
    return dict

def preprocessing():
    """ Provide the training data for the model. Define the features (X) and the target(y) 'target'."""
    dict = getFiles()
    train_data = dict['train']
    y = train_data.target
    train_features = train_data.columns[1:-1]
    X = train_data[train_features]
    return (X, y)

train_data.head()