Seaborn draws 11 histograms

This article introduces how to use seaborn To draw various histogram

• Basic histogram

• Horizontal histogram

• Title Setting

• be based on DataFrame mapping

• hue Parameter setting

• Color treatment

• Multidimensional processing

One I like very much Seaborn Drawn graphics ：

Import library

Seaborn yes matplotlib The advanced packaging of , therefore matplotlib You still need to import at the same time ：

In [1]:

import pandas as pd
import numpy as np

import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

sns.set_theme(style="whitegrid")
sns.set_style('darkgrid')

Import built-in data

It uses seaborn A built-in consumption tips Data sets ：

In [2]:

tips = sns.load_dataset("tips")
tips.head()

Basic histogram

In [3]:

x = ["A","B","C"]
y = [1, 2, 3]

sns.barplot(x, y)
plt.show()

Draw a horizontal histogram ：

#  Horizontal histogram 

x = ["A","B","C"]
y = [1, 2, 3]

sns.barplot(y, x)
plt.show()

Set title

In [14]:

x = ["A","B","C"]
y = [1, 2, 3]

fig = sns.barplot(x, y)
fig.set_title('title of seaborn')

plt.show()

Appoint x-y-data

In [5]:

#  adopt DataFrame To specify the 

ax = sns.barplot(x="day", y="tip", data=tips)
plt.show()

hue Parameters

Implemented grouped display data

In [6]:

ax = sns.barplot(x="day", 
        y="total_bill", 
        hue="sex", 
        data=tips)

Horizontal histogram

In [7]:

ax = sns.barplot(x="total_bill", 
                 y="day", 
                 data=tips)

Custom order

In [8]:

ax = sns.barplot(x="total_bill", 
                 y="day", 
                 #  add to order Parameters , order of appointment 
                 order=["Sat","Fri","Sun","Thur"],  #  Customize 
                 data=tips)

Color treatment

Use a color

In [9]:

ax = sns.barplot(x="size", 
                 y="total_bill", 
                 data=tips,
                 color="salmon", 
                 saturation=.5)

Color gradient

In [10]:

ax = sns.barplot(x="size", 
                 y="tip", 
                 data=tips,
                 palette="Blues")

Multidimensional grouping

In [11]:

g = sns.catplot(x="sex", 
                y="total_bill",
                hue="smoker", 
                col="time",
                data=tips, 
                kind="bar",
                height=4, 
                aspect=.7)

True/False grouping

In [12]:

tips["weekend"] = tips["day"].isin(["Sat", "Sun"])
tips

Out[12]:

In [13]:

ax = sns.barplot(x="day", 
                 y="tip", 
                 hue="weekend",
                 data=tips, 
                 dodge=False)

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