%matplotlib inline
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")
# your code here
# 计算均值
print("\n均值:")
print(anascombe.groupby('dataset')['x'].mean())
print(anascombe.groupby('dataset')['y'].mean())
# 计算方差
print("\n方差:")
print(anascombe.groupby('dataset')['x'].var())
print(anascombe.groupby('dataset')['y'].var())
# 计算相关系数
print("\n相关系数:")
print(anascombe.x.corr(anascombe.y))
# 计算线性回归
dataset = anascombe[(anascombe['dataset']=='I')].reset_index(drop=True)
result = smf.ols('y ~ x', dataset).fit()
print(result.summary())
dataset = anascombe[(anascombe['dataset']=='II')].reset_index(drop=True)
result = smf.ols('y ~ x', dataset).fit()
print(result.summary())
dataset = anascombe[(anascombe['dataset']=='III')].reset_index(drop=True)
result = smf.ols('y ~ x', dataset).fit()
print(result.summary())
dataset = anascombe[(anascombe['dataset']=='IV')].reset_index(drop=True)
result = smf.ols('y ~ x', dataset).fit()
print(result.summary())
以数据集1为例
# your code here
sns.set(style='whitegrid')
sns.FacetGrid(anascombe, col="dataset", hue="dataset", size=3) .map(plt.scatter, 'x', 'y')
