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mean =[0,0] covariance = [[1,0],[0,100]] ds = np.random.multivariate_normal(mean,covariance,500) dframe = pd.DataFrame(ds, columns=['col1', 'col2']) fig = sns.kdeplot(dframe).get_figure() fig.savefig('kde1.png')

Comfortable Cod answered on May 11, 2020 Popularity 8/10 Helpfulness 2/10

answer mean =[0,0] covariance = [[1,0],[0,100]] ds = np.random.multivariate_normal(mean,covariance,500) dframe = pd.DataFrame(ds, columns=['col1', 'col2']) fig = sns.kdeplot(dframe).get_figure() fig.savefig('kde1.png')

mean =[0,0] covariance = [[1,0],[0,100]] ds = np.random.multivariate_normal(mean,covariance,500) dframe = pd.DataFrame(ds, columns=['col1', 'col2']) fig = sns.kdeplot(dframe).get_figure() fig.savefig('kde1.png')

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mean =[0,0]
covariance = [[1,0],[0,100]]

ds = np.random.multivariate_normal(mean,covariance,500)

dframe = pd.DataFrame(ds, columns=['col1', 'col2'])

fig = sns.kdeplot(dframe).get_figure()
fig.savefig('kde1.png')

Popularity 8/10 Helpfulness 2/10 Language python

Source: Grepper

Tags: covariance fig mean python

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Contributed on May 11 2020

Comfortable Cod

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mean =[0,0] covariance = [[1,0],[0,100]] ds = np.random.multivariate_normal(mean,covariance,500) dframe = pd.DataFrame(ds, columns=['col1', 'col2']) fig = sns.kdeplot(dframe).get_figure() fig.savefig('kde1.png')

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mean =[0,0] covariance = [[1,0],[0,100]] ds = np.random.multivariate_normal(mean,covariance,500) dframe = pd.DataFrame(ds, columns=['col1', 'col2']) fig = sns.kdeplot(dframe).get_figure() fig.savefig('kde1.png')

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