image_output_1.png
import numpy as np

import os

import pandas as pd

def preDot(text):
    return text.rsplit('.', 1)[0]
np.random.seed(73)
pd.options.mode.chained_assignment = None
dataDict = {}
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))
        with ZipFile(os.path.join(dirname, filename), 'r') as zipf:
            unzipped_fn = preDot(filename)
            with zipf.open(unzipped_fn) as f:
                dataDict[preDot(unzipped_fn)] = pd.read_csv(f)
train_orders = dataDict['orders'][dataDict['orders']['eval_set'] == 'train'].drop('eval_set', axis=1)
prior_orders = dataDict['orders'][dataDict['orders']['eval_set'] == 'prior'].drop('eval_set', axis=1)
test_orders = dataDict['orders'][dataDict['orders']['eval_set'] == 'test'].drop('eval_set', axis=1)