mean

add like/dislike to answer which is an ObjectId to a questionSchema.

由 感情迁移 提交于 2019-12-09 23:52:24
问题 my user schema has an array of answer likes and dislikes on a question by user. question schema has an ObjectId of answer in my html, when a user is displayed a list of answers for a particular question, if he likes or dislikes that answer.... the glyphicon should be updated instantly. the problem occurring is that: due to some reasons the update is taking time and user is able to double click on a glyphicon and increase the like/dislike 2 times. in console, i see that all answers of all

【Python还能干嘛】爬取微信好友头像完成马赛克拼图（千图成像）～

由 孤者浪人 提交于 2019-12-09 21:54:40
马赛克拼图 何谓马赛克拼图（千图成像），简单来说就是将若干小图片平凑成为一张大图，如下图路飞一样，如果放大看你会发现里面都是一些海贼王里面的图片。 Our Tragets 爬取所有微信好友的头像🕺🏻🕺🏻🕺🏻 将所有微信好友头像拼凑成一张图片🏙🏙🏙 然后就可以去朋友圈愉快的装逼了🤪🤪🤪 Requirements 其实整个项目很小，项目总共代码量不过100行左右。 爬取微信头像依赖第三方库 itchat ； 马赛克拼图依赖依赖 numpy 和 PIL 库。 Content 爬取微信好友头像 我这边是用的所有微信好友头像作为的数据源，你们如果有其他的数据源也可以的，可以直接跳过这步。 爬取微信好友头像我使用的是 itchat ，里面已经有封装好了的API，直接调用就可以，将所有的好友头像保存到一个文件夹供后期使用。 代码部分 #!/usr/bin/env python # -*- coding: utf-8 -*- # @Author : AwesomeTang # @File : Wechat_Icon.py # @Version : Python 3.7 # @Time : 2019-06-29 23:35 import os import itchat itchat.login() friends = itchat.get_friends(update=True) base

Combine multiple data frames and calculate average

由 丶灬走出姿态 提交于 2019-12-09 06:07:59
问题 I have three data frames as below. I wish to combine them into one data frame according to Lon & Lat, and average the 3 values for each 'cell'. I have read this (calculate average over multiple data frames) and attempted to utilise aggregate but to no avail....any pointers appreciated. > head(CSR.GRACE[,c(1:14)],10) Lon Lat January February March April May June July August September October November December 1 28.5 -4.5 17.710425 13.855327 12.385712 13.558101 12.789865 6.913783 1.03770075 -5

Double For Loop to calculate averages and store them in matrix

由 本秂侑毒 提交于 2019-12-08 20:48:39
I'm having trouble running this double for loop to properly store the calculated values into the matrix (mentioned below). The reason why I elected to use the double For Loop and not apply() or mean() is that I want to obtain the unique combinations of the two columns and eliminate redundancy (explained below). See below for an example: A<-c(1,2,3,4,5) B<-c(2,3,4,5,6) Q1<-data.frame(cbind(A,B)) mean<-matrix(nrow=5, ncol = 5) for(i in 1: length(Q1$A)){ for(j in 2: length(Q1$B)){ mean[i,j]<-sum(Q1$A[i]+Q1$B[j])/2 } } Here, I attempted to run the entire A vector through the entire B vector while

Resolving UnhandledPromiseRejectionWarning in express post request

由 爷，独闯天下 提交于 2019-12-08 11:35:05
问题 I am trying to make a post request to the server (mongodb) but I get this error: UnhandledPromiseRejectionWarning: TypeError: Cannot read property 'todo_description' of undefined I am running mongodb on my localhost // Require Express const express = require("express"); // Setting Express Routes const router = express.Router(); // Set Up Models const Todo = require("../models/todo"); // Get All Todos router.get("/", async (req, res) => { try { const todo = await Todo.find(); res.json(todo); }

Generate Cross-table in R with mean and SD

由 烂漫一生 提交于 2019-12-08 03:55:08
问题 I have a large dataset for which I need to generate multiple cross-tables. These are particularly two dimensional tables to generate frequencies along with mean and SD. So give an example I have the below data - City <- c("A","B","A","A","B","C","D","A","D","C") Q1 <- c("Agree","Agree","Agree","Agree","Agree","Neither","Neither","Disagree","Agree","Agree") df <- data.frame(City,Q1) Keeping the data in mind, I want to generate a cross-table with mean as below - City A B C D Agree 3 2 1 1

Double For Loop to calculate averages and store them in matrix

由 和自甴很熟 提交于 2019-12-08 03:38:01
问题 I'm having trouble running this double for loop to properly store the calculated values into the matrix (mentioned below). The reason why I elected to use the double For Loop and not apply() or mean() is that I want to obtain the unique combinations of the two columns and eliminate redundancy (explained below). See below for an example: A<-c(1,2,3,4,5) B<-c(2,3,4,5,6) Q1<-data.frame(cbind(A,B)) mean<-matrix(nrow=5, ncol = 5) for(i in 1: length(Q1$A)){ for(j in 2: length(Q1$B)){ mean[i,j]<-sum

R: Why does mean(NA, na.rm = TRUE) return NaN

由 我怕爱的太早我们不能终老 提交于 2019-12-07 20:09:54
问题 When estimating the mean with a vector of all NA's we get an NaN if na.rm = TRUE . Why is this, is this flawed logic or is there something I'm missing? Surely it would make more sense to use NA than NaN ? Quick example below mean(NA, na.rm = TRUE) #[1] NaN mean(rep(NA, 10), na.rm = TRUE) #[1] NaN 回答1: It is a bit pity that ?mean does not say anything about this. My comment only told you that applying mean on an empty "numeric" results in NaN without more reasoning. Rui Barradas's comment

Smoothing a 2D matrix with rollmean, filter, rollapply or other R facilities by moving average sliding window method

由 百般思念 提交于 2019-12-07 19:05:09
问题 I am trying to find a function in R which smooths a 2D matrix which is already padded by zero around the matrix depending on the length of the window. If the window size is 3 then we pas 3 zeros from the top, bottom, right and left and then we do the averaging to smooth it. I found rollmean in SO and other tutorials but it doesn't exactly do what I want. I need (say if the window size is 3) we consider a window of 3*3 and take the average and replace it by the current elements of the current

How to plot deviation from mean

由 半城伤御伤魂 提交于 2019-12-07 18:35:12
问题 In R I have created a simple matrix of one column yielding a list of numbers with a set mean and a given standard deviation. rnorm2 <- function(n,mean,sd) { mean+sd*scale(rnorm(n)) } r <- rnorm2(100,4,1) I now would like to plot how these numbers differ from the mean. I can do this in Excel as shown below: But I would like to use ggplot2 to create a graph in R. in the Excel graph I have cheated by using a line graph but if I could do this as columns it would be better. I have tried using a
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