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书中代码:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
arr=np.random.randn(1000,2)
df=pd.DataFrame(arr,columns=['B','C']).cumsum()
df['A']=pd.Series(list(range(len(df))))
# plt.figure()
df.plot()
df.plot(x='A')
plt.show()

 参考代码 0:

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

df = pd.DataFrame(np.random.random(size=(4, 5)))
print(df)
fig = df.plot()
fig.figure.savefig('pic.png')

 

参考代码1:

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

stuDict={
"zs":[90,87,98,67,98,56],
"wang":[56,90,45,33,90,78],
"guo":[56,90,45,33,90,78],
"li":[56,90,45,33,90,78],    
}
df=pd.DataFrame(stuDict,index=['Term 1','Term 2','Term 3','Term 4','Term 5','Term 6'])
print(df)
df.plot(kind='bar')
df.plot()
plt.show()

参考代码2:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
listData=[[1,2,3],[2,2,2],[8,9,10]]
df=pd.DataFrame(listData,columns=['A','B','C'])
print("原始\n",df,"\n\n")
df2=df.cumsum()
print("列累加\n",df2,"\n\n")
df3=df.cumprod()
print("列累积\n",df3,"\n\n")
df4=df.cumsum(axis=1)
print("行累加\n",df4,"\n\n")
df5=df.cumprod(axis=1)
print("行累积\n",df5,"\n\n")
df.plot()
df2.plot()
df3.plot()
df4.plot()
df5.plot()
plt.show()

参考代码3:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
listData=[[1,2,3],[2,2,2],[8,9,10]]
df=pd.DataFrame(listData,columns=['A','B','C'])
print("原始\n",df,"\n\n")

df2=df.cumsum(axis=0)
df3=df2.rename(columns={"A": "AA", "B": "BB","C":"CC"})
print("累加\n",df3,"\n\n")
df4=pd.concat([df,df3],axis=1)
print("合并\n",df4)
df5=df4.reindex(columns=['A','AA','B','BB','C','CC'])
print("整理\n",df5)
df5.plot()
plt.show()

 参考代码4:

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

stuDict={
"zs":[90,87,98,67,98,56],
"wang":[56,90,45,33,90,78],
"guo":[56,90,45,33,90,78],
"li":[56,90,45,33,90,78],    
}
df=pd.DataFrame(stuDict,index=['Term 1','Term 2','Term 3','Term 4','Term 5','Term 6'])
print(df)
df.plot(kind='bar')
df.plot()
plt.show()

参考代码4b:

import numpy as np
import pandas as  pd
import matplotlib.pyplot as plt
stuDict={
"zs":[90,87,98,67,98,56],
"wang":[56,90,45,33,90,78],
"guo":[56,90,45,33,90,78],
"li":[56,90,45,33,90,78],    
}
df=pd.DataFrame(stuDict,index=['Term 1','Term 2','Term 3','Term 4','Term 5','Term 6'])
print(df)
plt.figure(1)
ax1=plt.subplot(2,2,1)
ax2=plt.subplot(2,2,2)
ax3=plt.subplot(2,1,2)
plt.sca(ax1)
plt.plot(df["zs"])
plt.ylabel("zs")
plt.sca(ax2)
plt.plot(df["wang"],c=u'r')
plt.ylabel("wang")
plt.sca(ax3)
plt.plot(df["guo"],c=u'b')
plt.ylabel("guo")
plt.show()

源码A下载 >>

源码B下载 >>

posted on 2022-03-25 14:14  e媒网络技术团队  阅读(29)  评论(0编辑  收藏  举报