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I have a data frame with the following format: name workplace a A b B c A d C e D .... I would like to convert this data frame into an affiliation network in R with the format A B C D ... a 1 0 0 0 b 0 1 0 0 c 1 0 0 0 d 0 0 1 0 e 0 0 0 1 ... and I used the following program: for (i in 1:nrow(A1)) { a1[rownames(a1) == A1$name[i], colnames(a1) == A1$workplace[i]] <- 1 } where A1 is the data frame, and a1 is the affiliation network. However, since I have a large data frame, the above program runs very slow. Is there an efficient way that avoids looping in data conversion? Thank you very much! If

I am new to NetworkX. Right now, I manage to connect all the nodes to this particular node. What I want to do next it to make it interactive e.g. able to make each of the node move by dragging using cursor. I know I have to make use of matplotlib, but I am not sure how to use it. Can anyone help me? My codes are: import matplotlib.pyplot as plt import networkx as nx import itertools d = [name of nodes] f = [number per nodes] for i in d: G.add_edge('"' + i + '"',b) pos=nx.fruchterman_reingold_layout(G, k=0.5, iterations=5) nx.draw_networkx_nodes(G,pos,node_size=130, node_color="white") nx.draw

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I have a Canvas onto which I draw a Path : Even though the StrokeThickness is set to 1, the vertical part of the path is drawn across 2 pixels and in a lighter color. I know that WPF has the SnapsToDevicePixels property that would fix it, and I read that in Silverlight there is a UseLayoutRounding property that you can use in some cases to have the same effect, however it does not seem to apply to Path . Is there anything I can do to get that line drawn properly? 回答1: There is a pixel snapper class over at MSDN on Dave Relyea's Silverlight

APP 反馈的三种形式：toast、snackbar、dialog 聪明的产品会在恰当的时间给予恰当的反馈，不反馈、反馈不及时、反馈不对都会让用户反感你的产品，从而失去用户。 现在的公司是做软硬件一体化，我负责OS层面的交互方案，这里会遇到要制定一些设计原则，从而让产品体验更统一。我们都知道，针对信息提醒，有一种设计形式叫toast，如何对toast进行规范，引发了我写这篇文章。 1.反馈 互联网产品存在两套反馈机制，一套是有明显界面变动的反馈，例如你点击淘宝列表页，立马就进入了商品详情页，页面的及时跳转是明显的视觉反馈；再比如你输入完账号密码，点击登录，登录成功，并进入了APP首页，这也是很明显的视觉反馈。 但，如果某种反馈不明显该怎么办？例如，你登录的时候你输错了账号密码，点击登录，是进入不了APP的，这个时候大部分产品都会给予toast提示用户：密码或账号输入错误，请重试。你看到这个提示之后，就会知道自己改怎么做了。这就是反馈的第二套机制：通过设计不同的形式来提示用户。 常见的反馈有三种样式：toast、snackbar、dialog。 2.Toast toast属于一种轻量级的反馈，常常以小弹框的形式出现，一般出现1到2秒会自动消失，可以出现在屏幕上中下任意位置，但同个产品会模块尽量使用同一位置，让用户产生统一认知。 在样式上，尽量和产品整体风格保持一致，这样会更和谐

I have a data frame of 205,000+ rows formatted as follows: df <- data.frame(project.id = c('SP001', 'SP001', 'SP001', 'SP017', 'SP018', 'SP017'), supplier.id = c('1224', '5542', '7741', '1224', '2020', '9122')) In the actual data frame there are 6700+ unique values of project.id . I would like to create an edge list that pairs suppliers who have worked on the same project. Desired end result for project.id = SP001 : to from 1224 5542 1224 7741 5542 7741 So far I've tried using split to create a list by project.id and then running lapply+combn to generate all possible combinations of supplier

My problem is very simple: I need to create an adjacency list/matrix from a list of edges. I have an edge list stored in a csv document with column1 = node1 and column2 = node2 and I would like to convert this to a weighted adjacency list or a weighted adjacency matrix. To be more precise, here's how the data looks like -where the numbers are simply node ids: node1,node2 551,548 510,512 548,553 505,504 510,512 552,543 512,510 512,510 551,548 548,543 543,547 543,548 548,543 548,542 Any tips on how to achieve the conversion from this to a weighted adjacency list/matrix? This is how I resolved to