分类变量的可视化

分类变量的可视化

%matplotlib inline

import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt

import seaborn as sns
sns.set(style="whitegrid", color_codes=True)
sns.set(rc={
   
   "figure.figsize": (10, 5)})  # 调整图形大小，长10，高5；

np.random.seed(sum(map(ord, "categorical")))

titanic = sns.load_dataset("titanic")
tips = sns.load_dataset("tips")
iris = sns.load_dataset("iris")

print(titanic.dtypes, tips.dtypes, iris.dtypes, sep='\n\n')

survived          int64
pclass            int64
sex              object
age             float64
sibsp             int64
parch             int64
fare            float64
embarked         object
class          category
who              object
adult_male         bool
deck           category
embark_town      object
alive            object
alone              bool
dtype: object

total_bill     float64
tip            float64
sex           category
smoker        category
day           category
time          category
size             int64
dtype: object

sepal_length    float64
sepal_width     float64
petal_length    float64
petal_width     float64
species          object
dtype: object

tips.head()

	total_bill	tip	sex	smoker	day	time	size
0	16.99	1.01	Female	No	Sun	Dinner	2
1	10.34	1.66	Male	No	Sun	Dinner	3
2	21.01	3.50	Male	No	Sun	Dinner	3
3	23.68	3.31	Male	No	Sun	Dinner	2
4	24.59	3.61	Female	No	Sun	Dinner	4

tips.shape

(244, 7)

散点图

sns.stripplot(x="day", y="total_bill", data=tips);  # 散点会覆盖

[外链图片转存(img-8pOEoiA1-1562742490850)(output_10_0.png)]

设置调色板

# 当前调色板
current_palette = sns.color_palette()
sns.palplot(current_palette)

[外链图片转存(img-0nJoI2xC-1562742490852)(output_12_0.png)]

# 设置全局调色板
sns.set_palette("husl")
sns.stripplot(x="day", y="total_bill", data=tips);  # 散点会覆盖

[外链图片转存失败(img-EWNgTTXA-1562742490852)(output_13_0.png)]

sns.stripplot(x="day", y="total_bill", data=tips);  # 散点会覆盖

[外链图片转存失败(img-tX0PVwIU-1562742490853)(output_14_0.png)]

sns.set()  # 设置为默认色系
sns.stripplot(x="day", y="total_bill", data=tips);  # 散点会覆盖

[外链图片转存失败(img-3TSBN1dO-1562742490853)(output_15_0.png)]

# 自定义调色版
palette = sns.light_palette("navy", reverse=True)
sns.stripplot(x="day", y="total_bill", data=tips, palette=palette);  # 散点会覆盖

[外链图片转存失败(img-DnHULdO0-1562742490853)(output_16_0.png)]

palette=sns.cubehelix_palette(light=1)
sns.stripplot(x="day", y="total_bill", data=tips, palette=palette);