import pandas
df = pandas.read_csv("https://vincentarelbundock.github.io/Rdatasets/csv/carData/Quartet.csv")
df
Unnamed: 0 | x | y1 | y2 | y3 | x4 | y4 | |
---|---|---|---|---|---|---|---|
0 | 1 | 10 | 8.04 | 9.14 | 7.46 | 8 | 6.58 |
1 | 2 | 8 | 6.95 | 8.14 | 6.77 | 8 | 5.76 |
2 | 3 | 13 | 7.58 | 8.74 | 12.74 | 8 | 7.71 |
3 | 4 | 9 | 8.81 | 8.77 | 7.11 | 8 | 8.84 |
4 | 5 | 11 | 8.33 | 9.26 | 7.81 | 8 | 8.47 |
5 | 6 | 14 | 9.96 | 8.10 | 8.84 | 8 | 7.04 |
6 | 7 | 6 | 7.24 | 6.13 | 6.08 | 8 | 5.25 |
7 | 8 | 4 | 4.26 | 3.10 | 5.39 | 19 | 12.50 |
8 | 9 | 12 | 10.84 | 9.13 | 8.15 | 8 | 5.56 |
9 | 10 | 7 | 4.82 | 7.26 | 6.42 | 8 | 7.91 |
10 | 11 | 5 | 5.68 | 4.74 | 5.73 | 8 | 6.89 |
df.drop('Unnamed: 0', axis=1)
x | y1 | y2 | y3 | x4 | y4 | |
---|---|---|---|---|---|---|
0 | 10 | 8.04 | 9.14 | 7.46 | 8 | 6.58 |
1 | 8 | 6.95 | 8.14 | 6.77 | 8 | 5.76 |
2 | 13 | 7.58 | 8.74 | 12.74 | 8 | 7.71 |
3 | 9 | 8.81 | 8.77 | 7.11 | 8 | 8.84 |
4 | 11 | 8.33 | 9.26 | 7.81 | 8 | 8.47 |
5 | 14 | 9.96 | 8.10 | 8.84 | 8 | 7.04 |
6 | 6 | 7.24 | 6.13 | 6.08 | 8 | 5.25 |
7 | 4 | 4.26 | 3.10 | 5.39 | 19 | 12.50 |
8 | 12 | 10.84 | 9.13 | 8.15 | 8 | 5.56 |
9 | 7 | 4.82 | 7.26 | 6.42 | 8 | 7.91 |
10 | 5 | 5.68 | 4.74 | 5.73 | 8 | 6.89 |
import matplotlib.pyplot as pl
pl.plot(df['x'], df['y1'], '.')
[<matplotlib.lines.Line2D at 0x1a50e6edda0>]
pl.plot(df['x'], df['y2'], '.')
[<matplotlib.lines.Line2D at 0x1a50e7592b0>]
pl.plot(df['x'], df['y3'], '.')
[<matplotlib.lines.Line2D at 0x1a50e7b9278>]
pl.plot(df['x'], df['y4'], '.')
[<matplotlib.lines.Line2D at 0x1a50e819898>]
import seaborn as sns
sns.set(style="ticks")
# Load the example dataset for Anscombe's quartet
df = sns.load_dataset("anscombe")
# Show the results of a linear regression within each dataset
sns.lmplot(x="x", y="y", col="dataset", hue="dataset", data=df,
col_wrap=2, ci=None, palette="muted",
scatter_kws={"s": 50, "alpha": 1})
<seaborn.axisgrid.FacetGrid at 0x1a50f7e22b0>