mean

问题 I have a React app that is trying to make an axios request to my Express server to find a user in a Mongo database. Before, I built the back-end on Rails and had a gem for CORS, and after trying to configure CORS on the Express side, I can't seem to find a solution. I want to be able to pass in a custom field in headers (i.e. username) so I can use that field to query against my database. Error I get in browser: XMLHttpRequest cannot load http://localhost:3000/api/users/test. Request header

问题 I have a React app that is trying to make an axios request to my Express server to find a user in a Mongo database. Before, I built the back-end on Rails and had a gem for CORS, and after trying to configure CORS on the Express side, I can't seem to find a solution. I want to be able to pass in a custom field in headers (i.e. username) so I can use that field to query against my database. Error I get in browser: XMLHttpRequest cannot load http://localhost:3000/api/users/test. Request header

问题 I have a React app that is trying to make an axios request to my Express server to find a user in a Mongo database. Before, I built the back-end on Rails and had a gem for CORS, and after trying to configure CORS on the Express side, I can't seem to find a solution. I want to be able to pass in a custom field in headers (i.e. username) so I can use that field to query against my database. Error I get in browser: XMLHttpRequest cannot load http://localhost:3000/api/users/test. Request header

问题 I have a dataset of 500 trials per participant that I want to sample from in various quantities (i.e. I want to sample the same number of trials from each participant) and then compute the mean for each participant. Instead of doing so, it is creating a file with a one mean for each participant separately for each "num", e.g. if the mean for participant 1 with 125 trials is 426 that will be the whole file, then another file for participant 1 with 150 trials with a single value, and that is

问题 I want to calculate the mean of column of all the csv in one directory, but when I run the function it give me the error of "Error in numeric(nc) : invalid 'length' argument". I believe that CSV files have n/a value but it shouldn't affect the calculate the number of column? pollutantmean <- function(directory, pollutant, id =1:332, removeNA = TRUE){ nc <- ncol(pollutant) means <- numeric(nc) for(i in 1:nc){ means[i] <- mean(pollutant[, i], na.rm = removeNA) } means } So here is my update

问题 I have a data frame DF <- data.frame(y1=c("AG","AG","AI","AI","AG","AI"), y0=c(2,2,1,1,2,1), y3=c(1994,1996,1997,1999,1994,1994),y4=c("AA","FB","AA","EB","AA","EB"), mw3wuus=c(26,34,22,21,65,78), Country_true=c("Antigua and Barbuda","Antigua and Barbuda","Anguilla","Anguilla","Antigua and Barbuda","Anguilla")) DF y1 y0 y3 y4 mw3wuus Country_true 1 AG 2 1994 AA 26 Antigua and Barbuda 2 AG 2 1996 FB 34 Antigua and Barbuda 3 AI 1 1997 AA 22 Anguilla 4 AI 1 1999 EB 21 Anguilla 5 AG 2 1994 AA 65

问题 I have a dataset where each species was mixed with a certain density (numeric) and type (numeric) of another species. I want to add two types of vertical lines to each of my facet_grid panels in ggplot: (a) A fixed line which dives the density/ type. e.g. 1000/1 = 1000, 1000/6 = 166.7, 10000/1 = 10000, 10000/6 = 1666.7 (b) The bootstrapped mean AND confidence interval for each treatment overlayed on the histogram. I tried adding the mean using geom_vline but it doesn't seem right. It looks

问题 I have a dataset where each species was mixed with a certain density (numeric) and type (numeric) of another species. I want to add two types of vertical lines to each of my facet_grid panels in ggplot: (a) A fixed line which dives the density/ type. e.g. 1000/1 = 1000, 1000/6 = 166.7, 10000/1 = 10000, 10000/6 = 1666.7 (b) The bootstrapped mean AND confidence interval for each treatment overlayed on the histogram. I tried adding the mean using geom_vline but it doesn't seem right. It looks

问题 I have a python pandas dataframe with several columns and one column has 0 values. I want to replace the 0 values with the median or mean of this column. data is my dataframe artist_hotness is the column mean_artist_hotness = data['artist_hotness'].dropna().mean() if len(data.artist_hotness[ data.artist_hotness.isnull() ]) > 0: data.artist_hotness.loc[ (data.artist_hotness.isnull()), 'artist_hotness'] = mean_artist_hotness I tried this, but it is not working. 回答1: I think you can use mask and

问题 I have a python pandas dataframe with several columns and one column has 0 values. I want to replace the 0 values with the median or mean of this column. data is my dataframe artist_hotness is the column mean_artist_hotness = data['artist_hotness'].dropna().mean() if len(data.artist_hotness[ data.artist_hotness.isnull() ]) > 0: data.artist_hotness.loc[ (data.artist_hotness.isnull()), 'artist_hotness'] = mean_artist_hotness I tried this, but it is not working. 回答1: I think you can use mask and