text_plain_output_1.png image_output_1.png
from sklearn.utils import shuffle

import pandas as pd

import seaborn as sns

df = pd.read_csv('../input/glass.csv')

from sklearn.utils import shuffle
df = shuffle(df)

X = df.ix[:, :-1]
Y = df.ix[:, -1]

df1 = df.corr()
df1 = df1[df1 < 1]

df.groupby(by='Type').mean()

sns.countplot(data=df, x='Type')