jupyter作业

import random

import numpy as np
import scipy as sp
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns


import statsmodels.api as sm
import statsmodels.formula.api as smf


sns.set_context("talk")
anascombe = pd.read_csv('anscombe.csv')

anascombe.head()

#part1

print(anascombe.groupby('dataset')['x'].mean())#x均值
print(anascombe.groupby('dataset')['x'].var())#x方差
print(anascombe.groupby('dataset')['y'].mean())#y均值
print(anascombe.groupby('dataset')['y'].var())#y方差
print(anascombe.groupby('dataset').corr())#相关系数
x = sm.add_constant(x)
L = sm.OLS(x,y)

print(L.fit().summary())

#part2

g = sns.FacetGrid(anascombe, col='dataset', size=5)

g = g.map(plt.scatter, "x", "y")
plt.show()

plt.show()