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Comparison Plots with pairplot() and jointplot()¶

Imports¶

In [1]:

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

In [2]:

df = pd.read_csv("StudentsPerformance.csv")

In [3]:

df.head()

Out[3]:

	gender	race/ethnicity	parental level of education	lunch	test preparation course	math score	reading score	writing score
0	female	group B	bachelor's degree	standard	none	72	72	74
1	female	group C	some college	standard	completed	69	90	88
2	female	group B	master's degree	standard	none	90	95	93
3	male	group A	associate's degree	free/reduced	none	47	57	44
4	male	group C	some college	standard	none	76	78	75

In [4]:

sns.jointplot(x='math score',y='reading score',data=df)

Out[4]:

<seaborn.axisgrid.JointGrid at 0x23f9ed8dd08>

In [5]:

sns.jointplot(x='math score',y='reading score',data=df,kind='hex')

Out[5]:

<seaborn.axisgrid.JointGrid at 0x23fa1027308>

In [6]:

sns.jointplot(x='math score',y='reading score',data=df,kind='kde')

Out[6]:

<seaborn.axisgrid.JointGrid at 0x23fa11d4108>

In [7]:

sns.pairplot(df)

Out[7]:

<seaborn.axisgrid.PairGrid at 0x23fa12eb608>

In [8]:

sns.pairplot(df,hue='gender',palette='viridis')

Out[8]:

<seaborn.axisgrid.PairGrid at 0x23fa18c8908>

In [9]:

sns.pairplot(df,hue='gender',palette='viridis',corner=True)

Out[9]:

<seaborn.axisgrid.PairGrid at 0x23fa1e07948>

In [10]:

sns.pairplot(df,hue='gender',palette='viridis',diag_kind='hist')

Out[10]:

<seaborn.axisgrid.PairGrid at 0x23fa190ef88>