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Sagot :
Answer:
Here the answer is given as follows,
Explanation:
import seaborn as sns
import pandas as pd
df = {'country': ['US', 'US', 'US', 'US', 'UK', 'UK', 'UK'],
'year': [2008, 2009, 2010, 2011, 2008, 2009, 2010],
'Happiness': [4.64, 4.42, 3.25, 3.08, 3.66, 4.08, 4.09],
'Positive': [0.85, 0.7, 0.54, 0.07, 0.1, 0.92, 0.94],
'Negative': [0.49, 0.09, 0.12, 0.32, 0.43, 0.21, 0.31],
'LogGDP': [8.66, 8.23, 7.29, 8.3, 8.27, 6.38, 6.09],
'Support': [0.24, 0.92, 0.54, 0.55, 0.6, 0.38, 0.63],
'Life': [51.95, 55.54, 52.48, 53.71, 50.18, 49.12, 55.84],
'Freedom': [0.65, 0.44, 0.06, 0.5, 0.52, 0.79, 0.63, ],
'Generosity': [0.07, 0.01, 0.06, 0.28, 0.36, 0.33, 0.26],
'Corruption': [0.97, 0.23, 0.66, 0.12, 0.06, 0.87, 0.53]}
dataFrame = pd.DataFrame.from_dict(df)
explanatory_vars = ['LogGDP', 'Support', 'Life', 'Freedom', 'Generosity', 'Corruption']
plot_vars = ['Happiness'] + explanatory_vars
sns.pairplot(dataFrame,
x_vars = explanatory_vars,
dropna=True,
palette="Blues")




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