image_output_1.png
import matplotlib.pyplot as plt

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

"""
In this notebook I will see what I can do - EDA-wise without the additional data.
I do that because it is not available for us in the test,
might be we an regenaerate them - but for now, the basic data is what I want to focus on.
"""
test = pd.read_csv('../input/test.csv')
train = pd.read_csv('../input/train.csv')
structures = pd.read_csv('../input/structures.csv')

train.columns

Fig, axarr = plt.subplots(2, 2, figsize=(12, 8))
Plt1 = train['atom_index_0'].plot.hist(ax=axarr[0][0])
Plt2 = train['atom_index_1'].plot.hist(ax=axarr[0][1])
Plt3 = train['type'].value_counts().plot.hist(ax=axarr[1][0])
Plt3 = train['scalar_coupling_constant'].plot.hist(ax=axarr[1][1], bins=50)