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import numpy as np

import numpy as np # linear algebra

import pandas as pd

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

import seaborn as sns

data = pd.read_csv('../input/used-car-dataset-ford-and-mercedes/ford.csv')

DuplicatedDataSum = data.duplicated().sum()

DuplicatedData = data.duplicated()

data = data.drop_duplicates()
DuplicatedDataSum = data.duplicated().sum()

corr = data.corr()
corr

mask = np.triu(np.ones_like(corr, dtype=bool))
f, ax = plt.subplots(figsize=(11, 9))
cmap = sns.diverging_palette(230, 20, as_cmap=True)
sns.heatmap(corr, mask=mask, cmap=cmap, vmax=0.3, center=0, square=True, linewidths=0.5, cbar_kws={'shrink': 0.5})