text_html_output_1.png
import numpy as np # linear algebra

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
from matplotlib import pyplot as plt
import seaborn as sns
import os
data_dir = '../input/champs-scalar-coupling' if 'champs-scalar-coupling' in os.listdir('../input/') else '../input'

train = pd.read_csv(f'{data_dir}/train.csv')
test = pd.read_csv(f'{data_dir}/test.csv')
sub = pd.read_csv(f'{data_dir}/sample_submission.csv')
structures = pd.read_csv(f'{data_dir}/structures.csv')

are_the_same_types = np.all(sorted(train['type'].unique()) == sorted(test['type'].unique()))

train.head()