rows

问题 I need your help, if the following code below counts every table row in a table, how can it be amended such that the code won't count the <th></th> as a row itself? var rows = document.getElementById("data").rows.length; 回答1: You should be using thead and tbody HTML: <table id="data"> <thead> <tr><th>Hz</th></tr> </thead> <tbody> <tr><td>1</td></tr> <tr><td>2</td></tr> <tr><td>3</td></tr> </tbody> </table> JavaScript: var rows = document.getElementById("data").getElementsByTagName("tbody")[0]

问题 Let's say I have table data similar to the following: 123456 John Doe 1 Green 2001 234567 Jane Doe 1 Yellow 2001 234567 Jane Doe 2 Red 2001 345678 Jim Doe 1 Red 2001 What I am attempting to do is only isolate the records for Jane Doe based upon the fact that she has more than one row in this table. (More that one sequence number) I cannot isolate based upon ID, names, colors, years, etc... The number 1 in the sequence tells me that is the first record and I need to be able to display that

问题 I'm trying to highlight the rows of the data.frame (testdf) according to the value in the column with the text values ("Type") testdf<-data.frame(Type=c("NON_BRAND", "BRAND", "BRAND", "NON_BRAND"),CA=c(500,890,780,240), Campaign=c("A", "B", "A", "B")) I can't achieve this using heatmap, as I need to color the whole row according to the word in the column "Type". (NON_BRAND rows color in blue and BRAND rows in yellow, for example). My output is a pdf or html file using R Markdown. Does anyone

问题 I have a table that looks like this: ID AMID DESC value ----------------------------------------------------------------- 100 type A AMID type A 10 101 type B AMID type B 18 102 type C AMID type C 34 101 null null 4 102 null null 19 103 type D AMID type D 6 103 type E null 7 The table contains around 6 million rows. Now I want to have the result like this ID AMID DESC value ------------------------------------------------------------- 100 type A AMID type A 10 101 type B AMID type B 18 102

问题 I want to eliminate repeated rows in my dataframe. I know that that drop_duplicates() method works for dropping rows with identical subcolumn values. However I want to drop rows that aren't identical but similar. For example, I have the following two rows: Title | Area | Price Apartment at Boston 100 150000 Apt at Boston 105 149000 I want to be able to eliminate these two columns based on some similarity measure, such as if Title, Area, and Price differ by less than 5%. Say, I could delete

问题 I have trouble solving the following problem concerning the (simplified by limiting number of columns) data frame 'annotations' below. require(irr) # data annotations <- read.table(text = "Obj1 Obj2 Obj3 Rater1 a b c Rater2 a b b Rater3 a b c", header = TRUE, stringsAsFactors = FALSE) I would like to apply the function agree from the irr package to all combinations (not permutations) of rows, resulting in the following. Agreement rater 1-2: 67% Agreement rater 1-3: 100% Agreement rater 2-3:

问题 I work with a data.frame like this: Country Date balance_of_payment business_confidence_indicator consumer_confidence_indicator CPI Crisis_IMF 1 Australia 1980-01-01 -0.87 100.215 99.780 25.4 0 2 Australia 1980-04-01 -1.62 100.061 99.746 26.2 0 3 Australia 1980-07-01 -3.70 100.599 100.049 26.6 0 4 Australia 1980-10-01 -3.13 100.597 100.735 27.2 0 5 Australia 1981-01-01 -2.73 101.149 101.016 27.8 0 6 Australia 1981-04-01 -4.11 100.936 100.150 28.4 0 I want to create a summary statistic with

问题 I have this cell array: levelx= 'GO:0016787' 'GO:0006412' 'GO:0030533' 'GO:0008150' 'GO:0006412' 'GO:0030533' 'GO:0006810' 'GO:0006412' 'GO:0030533' 'GO:0016787' 'GO:0006412' 'GO:0030533' 'GO:0008150' 'GO:0006412' 'GO:0030533' 'GO:0006810' 'GO:0006412' 'GO:0030533' 'GO:0016787' 'GO:0006412' 'GO:0030533' 'GO:0008150' 'GO:0006412' 'GO:0030533' 'GO:0006810' 'GO:0006412' 'GO:0030533' 'GO:0016787' 'GO:0006412' 'GO:0030533' I need to delete the repeated rows but without changing the order of the

问题 In the following data frame, col1 <- c("g1","g2","g3",NA,"g4",NA) col2 <- c(NA,"a1","a2",NA,"a3","a4") df1 <-data.frame(col1,col2) I would like to replace the rows with NA in col1 with corresponding rows of col2. Is it correct to proceed by extracting the rows containing NA by row <- which(is.na(col1)) and then extract the characters from col2 by extract <- df1$col2[row] After this I have no clue how to replace the NAs in col1 with the extracted characters. Please help! 回答1: You don't need

问题 I want to multiply rows of a matrix by EACH row (element) of a vector, not the entire vector (as the other question already posted talks about.) for example, I want to use these two matrices (or oo is a vector, since it's one column) oo=matrix(1:3,3,1) oop=matrix(1:9,3,3,byrow=TRUE) to output 1 2 3 8 10 12 21 24 27 I need to do this VERY efficiently, as I need to do it with massive amounts of data thousands of times. I used diag(as.vector(oo))%*%oop but this is much too slow. 回答1: R>oop*drop