count

来源： https://stackoverflow.com/questions/63231136/formula-to-ignore-hidden-columns

来源： https://stackoverflow.com/questions/63231136/formula-to-ignore-hidden-columns

问题 I have a data frame df . df <- data.frame(shop = c("A", "A", "A", "B", "B", "B", "C", "C", "C"), product = c(1,2,3,4,5,1,5,2,4)) For every pair of shops i.e AB , AC and BC , I wish to count the number of common product. The expected output is as follows pair common_product AB 1 # Because 1 is common AC 1 # Because 2 is common BC 2 # Because 5 and 4 is common 回答1: A base R option would be : pair <- combn(unique(df$shop), 2, paste0, collapse = "") commmon_product <- combn(unique(df$shop), 2,

问题 Apologies if this is a duplicate of anything, I wasn't finding answers which particularly did what I wanted. I'm trying to write a SQL query which will return the count of rows which contain a positive, negative or neutral sentiment on one of the candidates in the dataset. Here is a screenshot for reference Sentiment is one column but the values in it define the tweet to be positive, negative, or neutral. my goal is to have the query return something like this if anyone could give me an

问题 I'm trying to understand what the -c and -F options of perf record really do but I cannot explain what I'm seeing. I'm running these commands: perf record -a -F <frequency> sleep 1 and perf record -a -c <count> sleep 1 trying different values of frequency and count . The results I get are the following In the first table I set the frequency and in the second one the count. How do frequency and count affect the number of events? I thought the number of events was independent on the frequency

问题 I am trying to create a sequential number of equal values, a count of occurrences. However, I want the count to reset once a new ID is introduced even if the the row remains sequential. Example of what my data looks like: dataset <- data.frame(ID = c("a","a","a","a","a","a","a","b","b","b","b","b","b","b") dataset$YesNO <- c(1,1,0,0,0,1,1,1,1,1,0,0,0,0) So I want to create a new column with the results in: c(1,2,1,2,3,1,2,1,2,3,1,2,3,4) I've used this code that I've found on this forum:

问题 Could you help me implementing a counter in order to generate an xml file with multiple element from a csv inside? Here is the csv file UCB63_DATENUM;U6618_FILENAME;UF6E8_CANAL;U65B8_IDRP 7/8/19 22:27;457E6659_ZN_LIQRLVPR_A_V_ML.pdf;ML;1367091 9/11/19 23:03;49453878_ZN_LIQRLVPR_A_V_ML.pdf;ML;106440 9/24/19 21:04;497E585B_ZN_LIQRLVPR_A_V_CS.pdf;CS;1536658 2/12/20 22:12;58453B75_ZN_LIQRLVPR_A_V_ML.pdf;ML;1406091 and the code My return on the screen is good but as I am not calling the value, it

问题 Could you help me implementing a counter in order to generate an xml file with multiple element from a csv inside? Here is the csv file UCB63_DATENUM;U6618_FILENAME;UF6E8_CANAL;U65B8_IDRP 7/8/19 22:27;457E6659_ZN_LIQRLVPR_A_V_ML.pdf;ML;1367091 9/11/19 23:03;49453878_ZN_LIQRLVPR_A_V_ML.pdf;ML;106440 9/24/19 21:04;497E585B_ZN_LIQRLVPR_A_V_CS.pdf;CS;1536658 2/12/20 22:12;58453B75_ZN_LIQRLVPR_A_V_ML.pdf;ML;1406091 and the code My return on the screen is good but as I am not calling the value, it

问题 Could you help me implementing a counter in order to generate an xml file with multiple element from a csv inside? Here is the csv file UCB63_DATENUM;U6618_FILENAME;UF6E8_CANAL;U65B8_IDRP 7/8/19 22:27;457E6659_ZN_LIQRLVPR_A_V_ML.pdf;ML;1367091 9/11/19 23:03;49453878_ZN_LIQRLVPR_A_V_ML.pdf;ML;106440 9/24/19 21:04;497E585B_ZN_LIQRLVPR_A_V_CS.pdf;CS;1536658 2/12/20 22:12;58453B75_ZN_LIQRLVPR_A_V_ML.pdf;ML;1406091 and the code My return on the screen is good but as I am not calling the value, it

问题 Background I have a table set up in a SQL Server environment that contains a log of various activity that I'm tracking. Particular log items use unique codes to categorize what activity is taking place and a datetime field tracks when that activity occurred. Problem I would like to, using either a single query or a stored procedure, get an average of hourly counts of activity, grouped by day of the week. Example: Day | Hour | Average Count ------------------------------- Monday | 8 | 5 Monday