text_plain_output_1.png
import matplotlib.pyplot as plt

import numpy as np # linear algebra

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

import seaborn as sns

wine = pd.read_csv('../input/red-wine-quality-cortez-et-al-2009/winequality-red.csv')

wine.columns

#getting the histograms of the data
fig = plt.figure(figsize=(30, 20))
plt.suptitle('Histograms of the respective columns', fontsize=20)
for i in range(wine.shape[1]):
    plt.subplot(6, 3, i + 1)
    f = plt.gca()
    f.set_title(wine.columns.values[i])

    vals = np.size(wine.iloc[:, i].unique())
    if vals >= 100:
        vals = 100
    
    plt.hist(wine.iloc[:, i], bins=vals, color='#5D2A4C')
plt.tight_layout(rect=[0, 0.03, 1, 0.95])

wine.isna().any()

sns.set(style='white')
corr = wine.corr()

corr.head()