seaborn绘图

散点图：

import seaborn as sns
import pandas as pd
from matplotlib import pyplot as plt

file_path = 'iris.csv'
iris = pd.read_csv(file_path)

# print(iris.info())
print(iris.loc[:,'Name'].unique())


# hue 关于那一列数据进行区分  fit_reg 回归线
sns.lmplot(x='SepalLength',y='PetalLength',data=iris,hue='Name',fit_reg=False)

plt.show()

直方图：

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

s1 = pd.Series(np.random.randn(1000))

print(s1)

# 直方图
# plt.hist(s1)

# kde 密度图  hist 直方图
# kde = False 只显示直方图 hist = False 只显示核密度图  rug = True 显示观察条
sns.distplot(s1,kde=False)

# sns.kdeplot(s1,shade=True,color='r')



plt.show()

柱状图：

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

# 加载官方的在线数据

df = sns.load_dataset('flights')


df1 = df.pivot(index='month',columns='year',values='passengers')

# 柱状图
s = df1.sum()

_x = s.index
_y = s.values

sns.barplot(_x,_y)


plt.show()

热力图：

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

# 加载官方的在线数据

df = sns.load_dataset('flights')


df1 = df.pivot(index='month',columns='year',values='passengers')
# print(df1.head())
# 热力图

# annot = True 显示value   fmt = 'd' 整数  cmap='颜色'
# sns.heatmap(df1,annot=True,fmt='d')

plt.show()