摘要：
import pandas as pd import numpy as np A=pd.DataFrame(np.random.randint(0,20,(2,2)),columns=list("ab"))#生成0-20随机数，两行两列 B=pd.DataFrame(np.random.randin 阅读全文
摘要：
import pandas as pd #1. columns=["数学","英语","语文","理科综合","文科综合"] index=["top2","c9","985","211","1本","2本","3本","大专"] data={ "数学":[145,140,135,130,125,12 阅读全文
摘要：
import pandas as pd from pandas import Series import numpy as np from pandas import DataFrame obj=Series([1,2,3,4,5])#Series包含行索引，列索引。默认0，1，2，3，4 obj2 阅读全文
摘要：
import pandas as pd face =pd.read_table(r"Y:\Workplace\大数据相关\face.txt") print(face.shape)#查看多少行多少列 #print(face.head(10))#在jupter notebook里面可以显示完全表格 pr 阅读全文
摘要：
import numpy as np import numpy.matlib arr1=np.array([[1,2],[3,4]]) arr2=np.array([[11,12],[13,14]]) np.dot(arr1,arr2)#返回两个数组的点积，对于二维向量等效于矩阵乘法，对于一维向量相 阅读全文
摘要：
import numpy as np import numpy.matlib#数学计算 import numpy.matrixlib#矩阵 marr1=np.matlib.empty((3,3))#填充随机数 marr1=np.matlib.ones((3,3))#全部修改为一 marr2=np.m 阅读全文
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import numpy as np arr1=np.array([[0,1,2],[3,4,5]]) arr2=arr1#视图，同一片内存 arr3=arr1.view()#数据改变一起改变，形状改变ta不变 arr4=arr1.copy()#深复制，副本，原本的改变不影响 阅读全文
摘要：
import numpy as np arr1=np.array([[3,9,0],[1,8,2]]) np.sort(arr1)#按照行排序 np.sort(arr1,axis=0)#按照列排序 dt=np.dtype([("name","S10"),("age",int),("tall",int 阅读全文
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import numpy as np arr1=np.arange(16,dtype=float).reshape(4,4) arr2=np.array([10,20,30,40]) arr3=np.array([[10,20,30,40],[10,20,30,40],[10,20,30,40],[ 阅读全文
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import numpy as np arr=np.array([0,30,60,45,90,150,180,360]) a=np.sin(arr*np.pi/180) b=np.arcsin(0.5) c=np.degrees(a)#转化为角度 arr2=np.array([1.1,3.3,5.5 阅读全文
摘要：
# coding: utf-8 #1.算法 import csv from igraph import Graph as IGraph path="net.data" edges=[]#边长集合 with open(path,"r") as file: for row in csv.reader(f 阅读全文