Graphing Anscombe's quartet

Anscombe's quartet is a classic example that illustrates why visualizing data is important. The quartet consists of four datasets with similar statistical properties. Each dataset has a series of x values and dependent y values. We will tabulate these metrics in an IPython notebook. However, if you plot the datasets, they look surprisingly different compared to each other.

How to do it...

For this recipe, you need to perform the following steps:

1. Start with the following imports:

   import pandas as pd
   import seaborn as sns
   import matplotlib.pyplot as plt
   import matplotlib as mpl
   from dautil import report
   from dautil import plotting
   import numpy as np
   from tabulate import tabulate

2. Define the following function to compute the mean, variance, and correlation of x and y within a dataset, the slope, and the intercept of a linear fit for each of the datasets:

   df = sns.load_dataset("anscombe")
   
       agg = df.groupby('dataset')\
                .agg([np.mean, np.var])\
            ...