Pandas笔记11----------Pandas绘图

1.折线图

• Series折线图

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
s = pd.Series([100,200,300,200,150,100])
s.plot()
plt.show()

• DataFrame折线图

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = np.random.randint(50,100,size=(5,6))
index = ['1st','2nd','3th','4th','5th']
columns = ['Jeff','Jack','Rose','Lucy','Liy','Bob']
df = pd.DataFrame(data=data,index=index,columns=columns)
print(df)
df.plot()
plt.show

2.条形图和柱状图

• Series柱状图和条形图

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
s = pd.Series(data=[100,200,300,200])
s.index = ['Lily','Lucy','Jack','Rose']
#两种图形同时打印会重叠在一张图中
s.plot.bar() #柱状图
s.plot.barh() #条形图

柱状图

条形图

• DataFrame柱状图和条形图

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = np.random.randint(0,100,size=(4,3))
index = list('ABCD')
columns = ['Python','C','Java']
df = pd.DataFrame(data=data,index=index,columns=columns)
df.plot(kind='bar')
df.plot(kind='barh')

柱状图

条形图

2.直方图 

• 柱高表示数据的频数，柱宽表示各组数据的组距
• 参数bins：设置直方图方柱的个数上线，值越大柱宽越小，数据分组越细致
• 参数density：默认值False，值为True时把频数转换为概率

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
s = pd.Series([1,2,2,2,2,2,3,3,4,4,4,5,6,6])
s.plot(kind='hist')
s.plot(kind='hist',bins=5)

无参数

 

带参数bins

带参数density

3.kde图：核密度估计，用于弥补直方图由于参数bins设置的不合理导致的精度缺失问题

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
s = pd.Series([1,2,2,2,2,2,3,3,4,4,4,5,6,6])
s.plot(kind='hist',bins=5)
s.plot(kind='kde')

4.饼图 

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame(
    data = np.random.rand(4,2),
    index = list('ABCD'),
    columns = ['Python','Java']
)
df['Python'].plot(kind='pie',autopct='%.1f%%')
#subplots子图
df.plot.pie(subplots=True)

df['Python'].plot(kind='pie',autopct='%.1f%%')标题

df.plot.pie(subplots=True)标题

5.散点图

• 散点图是观察两个一维数据数列之间的关系，DataFrame对象可用
• 需要指定x，y参数

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = np.random.normal(size=(1000,2))
df = pd.DataFrame(data=data,columns=list('AB'))
df.plot(kind='scatter',x='A',y='B')

 

6.面积图 

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame(data=np.random.rand(10,4),columns=list('ABCD'))
df.plot(kind='area')

7.箱型图

• 图中每一个箱型图从上到下的横线表示：最大值，75%，50%，25%，最小值
• 空心圆：异常值，离群点

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame(data=np.random.rand(10,4),columns=list('ABCD'))
df.plot(kind='box')

 知识点为听课总结笔记，课程为B站“千锋教育Pandas数据分析从入门到实战，零基础小白保姆级Python数据分析教程”：001_Pandas_Pandas介绍_哔哩哔哩_bilibili

Pandas学习完结撒花！！！！！！！！！！！！