Use seaborn to draw histograms

Public number: You Er Hut
Author: Peter
Editor: Peter

Hello everyone, my name is Peter~

This article describes how to use seaborn to draw various histograms

• Basic histogram
• horizontal histogram
• Title settings
• Drawing based on DataFrame
• hue parameter setting
• color processing
• multi-dimensional processing

A graph drawn by Seaborn that I like very much:

import library

Seaborn is an advanced package of matplotlib, so matplotlib still needs to be imported 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

Using a consumer tips dataset built into seaborn:

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()

Plot a horizontal histogram:

# 水平柱状图

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()

specify xy-data

In [5]:

# 通过DataFrame来指定

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

hue parameter

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", 
                 # 添加order参数，指定顺序
                 order=["Sat","Fri","Sun","Thur"],  # 自定义
                 data=tips)

color processing

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)