%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")
Anscombe's quartet comprises of four datasets, and is rather famous. Why? You'll find out in this exercise.
anascombe = pd.read_csv('data/anscombe.csv')
anascombe.head()
dataset | x | y | |
---|---|---|---|
0 | I | 10 | 8.04 |
1 | I | 8 | 6.95 |
2 | I | 13 | 7.58 |
3 | I | 9 | 8.81 |
4 | I | 11 | 8.33 |
For each of the four datasets...
# your code here
Using Seaborn, visualize all four datasets.
hint: use sns.FacetGrid combined with plt.scatter
# your code here