python樹狀結構

① python中用字典寫出樹形數據結構並在控制台中列印樹形數據結構

#!/usr/bin/python
importos,sys,string
classXXTree:
	def__init__(self):
		pass
	
	defprintHelp(self,cmd):
		print'Pleaseusethefollowingcmd:'
		print''+cmd+'dir'
		print'e.g.'
		print''+cmd+'/home/fkong/tmp'

	defgetTree(self,dir,op):
		list=self.getList(dir,0,op)
		treelist=[]
		
		foriinrange(0,len(list)):
			fullpath=list[i]
			parpath=os.path.dirname(list[i])
			filename=os.path.basename(list[i])
			if(fullpath==dir):
				treelist.append(fullpath)
				continue
				
			path=fullpath.replace(dir,"")
			names=path.split("/")
			name="`---"+names[len(names)-1]
			forjinrange(1,len(names)-1):
				name=""+name
			treelist.append(name)
			
			pos=name.index("`")
			j=i-1
			whilej>0:
				name=treelist[j]
				if(name[pos]=='`'orname[pos]==''):
					name=name[0:pos]+"|"+name[pos+1:len(name)]
					treelist[j]=name
				else:
					break
				j=j-1
		
		foriinrange(0,len(treelist)):
			printtreelist[i]
		
	defgetList(self,dir,layer,op):
		list=[]
		iflayer==0:list.append(dir)
		files=os.listdir(dir)
		forfileinfiles:
			file=os.path.join(dir,file)
			ifos.path.isdir(file):
				list.append(file)
				list+=self.getList(file,layer+1,op)
			elifop=='-d':
				pass
			else:
				list.append(file)
		returnlist

iflen(sys.argv)<2:
	t=XXTree()
	t.printHelp(sys.argv[0])
else:
	t=XXTree()

	dir=None
	iflen(sys.argv)==2:
		dir=sys.argv[1]

	op=None
	iflen(sys.argv)==3:
		op=sys.argv[1]
		dir=sys.argv[2]

	t.getTree(dir,op)

② python中樹結構使用什麼實現的

這是數據結構的問題，按照數據結構中樹的實現即可，當然，要是圖方便也可以使用dict來模擬

③ 如何用python將幾個列表轉換成樹形結構

不要費那個勁了，直接用pathlib

④ python連接到資料庫如圖所示，把資料庫中的數據做成圖形，類似這種條形樹狀的。

可以用record這個庫，支持sql結果轉dataframe，然後就可以用matplot這個庫畫圖了

⑤ 請教一下python qt treewidget的樹狀結構怎麼向指定節點插入內容

1. 樹形結構實現 qt gui中有treewidget部件,將該...同時還有刪除指定節點(父節點和子節點同時刪除)的...c c++ javascript

⑥ python怎麼做聚類樹狀圖

#-*-coding:utf-8-*-importmathimportpylabaspl#數據集：每三個是一組分別是西瓜的編號，密度，含糖量data="""
1,0.697,0.46,2,0.774,0.376,3,0.634,0.264,4,0.608,0.318,5,0.556,0.215,
6,0.403,0.237,7,0.481,0.149,8,0.437,0.211,9,0.666,0.091,10,0.243,0.267,
11,0.245,0.057,12,0.343,0.099,13,0.639,0.161,14,0.657,0.198,15,0.36,0.37,
16,0.593,0.042,17,0.719,0.103,18,0.359,0.188,19,0.339,0.241,20,0.282,0.257,
21,0.748,0.232,22,0.714,0.346,23,0.483,0.312,24,0.478,0.437,25,0.525,0.369,
26,0.751,0.489,27,0.532,0.472,28,0.473,0.376,29,0.725,0.445,30,0.446,0.459"""#數據處理dataset是30個樣本（密度，含糖量）的列表a=data.split(',')
dataset=[(float(a[i]),float(a[i+1]))foriinrange(1,len(a)-1,3)]#計算歐幾里得距離,a,b分別為兩個元組defdist(a,b):
returnmath.sqrt(math.pow(a[0]-b[0],2)+math.pow(a[1]-b[1],2))#dist_mindefdist_min(Ci,Cj):
returnmin(dist(i,j)foriinCiforjinCj)#dist_maxdefdist_max(Ci,Cj):
returnmax(dist(i,j)foriinCiforjinCj)#dist_avgdefdist_avg(Ci,Cj):
returnsum(dist(i,j)foriinCiforjinCj)/(len(Ci)*len(Cj))#找到距離最小的下標deffind_Min(M):
min=1000
x=0;y=0
foriinrange(len(M)):forjinrange(len(M[i])):ifi!=jandM[i][j]<min:
min=M[i][j];x=i;y=jreturn(x,y,min)#演算法模型：defAGNES(dataset,dist,k):
#初始化C和M
C=[];M=[]foriindataset:
Ci=[]
Ci.append(i)
C.append(Ci)foriinC:
Mi=[]forjinC:
Mi.append(dist(i,j))
M.append(Mi)
q=len(dataset)#合並更新
whileq>k:
x,y,min=find_Min(M)
C[x].extend(C[y])
C.remove(C[y])
M=[]foriinC:
Mi=[]forjinC:
Mi.append(dist(i,j))
M.append(Mi)
q-=1
returnC#畫圖defdraw(C):
colValue=['r','y','g','b','c','k','m']foriinrange(len(C)):
coo_X=[]#x坐標列表
coo_Y=[]#y坐標列表
forjinrange(len(C[i])):
coo_X.append(C[i][j][0])
coo_Y.append(C[i][j][1])
pl.scatter(coo_X,coo_Y,marker='x',color=colValue[i%len(colValue)],label=i)

pl.legend(loc='upperright')
pl.show()

C=AGNES(dataset,dist_avg,3)
draw(C)