grouping

问题 I am currently working on UI Integration tests using Cypress. I am looking for ways to add test case grouping in cypress similar to the standard TestNG. I was not able to find any grouping features in cypress documentation. I did find this post: link where grouping is done using tags. I am looking for a simpler way for test case grouping. Here is my use case: I have tests for different features like feature1,2,3 in below example and each feature has different test cases. I would like to run

问题 I am currently working on UI Integration tests using Cypress. I am looking for ways to add test case grouping in cypress similar to the standard TestNG. I was not able to find any grouping features in cypress documentation. I did find this post: link where grouping is done using tags. I am looking for a simpler way for test case grouping. Here is my use case: I have tests for different features like feature1,2,3 in below example and each feature has different test cases. I would like to run

问题 I have a data table where each value for variables v1 and v2 has an associated "type", coded in a separate column. Here is a MWE: X <- data.table(id = 1:5, group = c(1,1,2,2,2), v1 = c(10,12,14,16,18), type_v1 = c("t1","t2","t1","t1","t2"), v2 = c(3,NA,NA,7,8), type_v2 = c("t2", "", "", "t3","t3")) print(X) id group v1 type_v1 v2 type_v2 1: 1 1 10 t1 3 t2 2: 2 1 12 t2 NA 3: 3 2 14 t1 NA 4: 4 2 16 t1 7 t3 5: 5 2 18 t2 8 t3 I want to sum up the values in columns v1 and v2 for each type by the

问题 I have a data table where each value for variables v1 and v2 has an associated "type", coded in a separate column. Here is a MWE: X <- data.table(id = 1:5, group = c(1,1,2,2,2), v1 = c(10,12,14,16,18), type_v1 = c("t1","t2","t1","t1","t2"), v2 = c(3,NA,NA,7,8), type_v2 = c("t2", "", "", "t3","t3")) print(X) id group v1 type_v1 v2 type_v2 1: 1 1 10 t1 3 t2 2: 2 1 12 t2 NA 3: 3 2 14 t1 NA 4: 4 2 16 t1 7 t3 5: 5 2 18 t2 8 t3 I want to sum up the values in columns v1 and v2 for each type by the

问题 I have a list : citylist = ['New York', 'San Francisco', 'Los Angeles', 'Chicago', 'Miami'] and a pandas Dataframe df1 with these values first last city email John Travis New York a@email.com Jim Perterson San Franciso, Los Angeles b@email.com Nancy Travis Chicago b1@email.com Jake Templeton Los Angeles b3@email.com John Myers New York b4@email.com Peter Johnson San Franciso, Chicago b5@email.com Aby Peters Los Angeles b6@email.com Amy Thomas San Franciso b7@email.com Jessica Thompson Los

问题 Is there a better way to add rows within group_by() groups than using bind_rows() ? Here's an example that's a little clunky: df <- data.frame(a=c(1,1,1,2,2), b=1:5) df %>% group_by(a) %>% do(bind_rows(data.frame(a=.$a[1], b=0), ., data.frame(a=.$a[1], b=10))) The idea is that columns that we're already grouping on could be inferred from the groups. I was wondering whether something like this could work instead: df %>% group_by(a) %>% insert(b=0, .at=0) %>% insert(b=10) Like append() , it

问题 Is there a better way to add rows within group_by() groups than using bind_rows() ? Here's an example that's a little clunky: df <- data.frame(a=c(1,1,1,2,2), b=1:5) df %>% group_by(a) %>% do(bind_rows(data.frame(a=.$a[1], b=0), ., data.frame(a=.$a[1], b=10))) The idea is that columns that we're already grouping on could be inferred from the groups. I was wondering whether something like this could work instead: df %>% group_by(a) %>% insert(b=0, .at=0) %>% insert(b=10) Like append() , it

问题 Is there a better way to add rows within group_by() groups than using bind_rows() ? Here's an example that's a little clunky: df <- data.frame(a=c(1,1,1,2,2), b=1:5) df %>% group_by(a) %>% do(bind_rows(data.frame(a=.$a[1], b=0), ., data.frame(a=.$a[1], b=10))) The idea is that columns that we're already grouping on could be inferred from the groups. I was wondering whether something like this could work instead: df %>% group_by(a) %>% insert(b=0, .at=0) %>% insert(b=10) Like append() , it

问题 Is there a better way to add rows within group_by() groups than using bind_rows() ? Here's an example that's a little clunky: df <- data.frame(a=c(1,1,1,2,2), b=1:5) df %>% group_by(a) %>% do(bind_rows(data.frame(a=.$a[1], b=0), ., data.frame(a=.$a[1], b=10))) The idea is that columns that we're already grouping on could be inferred from the groups. I was wondering whether something like this could work instead: df %>% group_by(a) %>% insert(b=0, .at=0) %>% insert(b=10) Like append() , it

问题 In a data frame, I have a column with Y and N values. This data frame also has an id column. I would like to create two columns, one with the total Y count and another with the total N count for each id. I tried doing this procedure with the dplyr summarise function group_by(id) %>% summarise(total_not = count(column_y_e_n == "N"), total_yes = count(column_y_e_n == "Y") but objected to the error message Error in summarise_impl(.data, dots) Any sugestion? 回答1: Slight variation on original