v Using Seaborn To Visualize A Pandas Dataframe - Python

Using Seaborn To Visualize A Pandas Dataframe

Preliminaries

import pandas as pd
%matplotlib inline
import random
import matplotlib.pyplot as plt
import seaborn as sns
df = pd.DataFrame()

df['x'] = random.sample(range(1, 100), 25)
df['y'] = random.sample(range(1, 100), 25)
df.head()
x y
0 18 25
1 42 67
2 52 77
3 4 34
4 14 69

Scatterplot

sns.lmplot('x', 'y', data=df, fit_reg=False)
<seaborn.axisgrid.FacetGrid at 0x114563b00>

png

Density Plot

sns.kdeplot(df.y)
<matplotlib.axes._subplots.AxesSubplot at 0x113ea2ef0>

png

sns.kdeplot(df.y, df.x)
<matplotlib.axes._subplots.AxesSubplot at 0x113d7fef0>

png

sns.distplot(df.x)
<matplotlib.axes._subplots.AxesSubplot at 0x114294160>

png

Histogram

plt.hist(df.x, alpha=.3)
sns.rugplot(df.x);

png

Boxplot

sns.boxplot([df.y, df.x])
<matplotlib.axes._subplots.AxesSubplot at 0x1142b8b38>

png

Violin Plot

sns.violinplot([df.y, df.x])
<matplotlib.axes._subplots.AxesSubplot at 0x114444a58>

png

Heatmap

sns.heatmap([df.y, df.x], annot=True, fmt="d")
<matplotlib.axes._subplots.AxesSubplot at 0x114530c88>

png

Clustermap

sns.clustermap(df)
<seaborn.matrix.ClusterGrid at 0x116f313c8>

png