text_plain_output_1.png
import matplotlib.pyplot as plt # visualization

import pandas as pd  # read and wrangle dataframes

import seaborn as sns # statistical visualizations and aesthetics

df = pd.read_csv('../input/glass/glass.csv')
features = df.columns[:-1].tolist()

df.dtypes

for feat in features:
    skew = df[feat].skew()
    sns.distplot(df[feat], kde=False, label='Skew = %.3f' % skew, bins=30)
    plt.legend(loc='best')
    plt.show()