import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
data=np.random.randn(5,2)*10
df=pd.DataFrame(np.abs(data),index=[1,2,3,4,5],columns=[1,2])
df.plot()
plt.show()

條形圖

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
data=np.random.randn(5,2)*10
df=pd.DataFrame(np.abs(data),index=[1,2,3,4,5],columns=[1,2])
df.plot(kind='bar')
plt.show()

水平條形圖

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
data=np.random.randn(5,2)*10
df=pd.DataFrame(np.abs(data),index=[1,2,3,4,5],columns=[1,2])
df.plot(kind='barh')
plt.show()

堆積圖

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
data=np.random.randn(5,2)*10
df=pd.DataFrame(np.abs(data),index=[1,2,3,4,5],columns=[1,2])
df.plot(kind='bar',stacked=True)
plt.show()

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
data=np.random.randn(5,2)*10
df=pd.DataFrame(np.abs(data),index=[1,2,3,4,5],columns=[1,2])
df.plot(kind='barh',stacked=True)
plt.show()

散點圖

數(shù)據(jù)通常是一些點的集合

常用來繪制各種相關性，適合研究不同變量間的關系

x:x坐標位置
y:y坐標位置
s:散點的大小
c:散點顏色

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
data=np.random.randn(5,2)*10
df=pd.DataFrame(np.abs(data),index=[1,2,3,4,5],columns=['A','B'])
df.plot(kind='scatter',x='A',y='B',s=df.A*100,c='red')
plt.show()

餅圖

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df=pd.Series(3*np.random.rand(4),index=['a','b','c','d'])
df.plot.pie(figsize=(6,6))
plt.show()

蜂巢圖

體現(xiàn)數(shù)據(jù)出現(xiàn)的次數(shù)

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df=pd.DataFrame(np.random.randn(1000,2),columns=['a','b'])
df.plot.hexbin(x='a',y='b',sharex=False,gridsize=30)
plt.show()

箱線圖

基于最小值、上四分位、中位數(shù)、下四分位和最大值5個數(shù)值特征展示數(shù)據(jù)分布的標準方式，可以看出數(shù)據(jù)是否具有對稱性，適用于展示一組數(shù)據(jù)的分布情況

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df=pd.DataFrame(np.random.randn(1000,2),columns=['a','b'])
df.plot(y=df.columns,kind='box',vert=False)
plt.show()

繪制子圖

subplots:默認False 若每列繪制子圖就為True

layout:子圖布局

figsize:畫布大小

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df=pd.DataFrame(np.random.randn(5,2),columns=['a','b'])
df.plot(subplots=True,layout=(2,3),figsize=(10,10),kind='bar')
plt.show()