data-manipulation

问题 I have a table: Table_Name: price_list --------------------------------------------------- | id | price_type_a | price_type_b | price_type_c | --------------------------------------------------- | 1 | 1234 | 5678 | 9012 | | 2 | 3456 | 7890 | 1234 | | 3 | 5678 | 9012 | 3456 | --------------------------------------------------- I need a select query in Postgres which gives result like this: --------------------------- | id | price_type | price | --------------------------- | 1 | type_a | 1234 |

问题 This is a follow-up question from Extract multiple data.frames from one with selection criteria. Let's say the data is the same as in above example df <- data.frame(x1 = runif(1000), x2 = runif(1000), x3 = runif(1000), split = sample( c('SPLITMEHERE', 'OBS'), 1000, replace=TRUE, prob=c(0.1, 0.9) )) Basically, I need more general solution than the one in the quoted example. Namely, some counties in some months (every month is a .txt file) have only 1 table, and therefore only one 'SPLITMEHERE'

问题 Think of a picture of Sunrise where a red circle is surrounded by yellow thick ring and then blue background. Take red as 3 then yellow as 2 and blue as 1. 11111111111 11111211111 11112221111 11222322211 22223332222 11222322221 11112221111 11111211111 This is the desired output. But, the record/file/data has missing values (30% of all elements are missing). How can we impute missing values so as to get this desired output keeping the circular trend in mind. 回答1: This is how I would solve a

问题 Define df<-read.table(textConnection('egg 1 20 a egg 2 30 a jap 3 50 b jap 1 60 b')) s.t. > df V1 V2 V3 V4 1 egg 1 20 a 2 egg 2 30 a 3 jap 3 50 b 4 jap 1 60 b My data has no factors so I convert factors to characters: > df$V1 <- as.character(df$V1) > df$V4 <- as.character(df$V4) I would like to "collapse" the data frame by V1 keeping: The max of V2 The mean of V3 The mode of V4 (this value does not actually change within V1 groups, so first, last, etc might do also.) Please note this is a

问题 I have this dataframe: df<-data.frame(a=c("a1","a2","a3","a4","b1","b2","b3","b4","a1","a2","a3","a4","b1","b2","b3","b4"), b=c("x1","x2","x3","total","x1","x2","x3","total", "x1","x2","x3","total","x1","x2","x3","total"), reg=c("A","A","A","A","A","A","A","A","B", "B","B","B","B","B","B","B"), c=c(1:16)) which looks like: a b reg c 1 a1 x1 A 1 2 a2 x2 A 2 3 a3 x3 A 3 4 a4 total A 4 5 b1 x1 A 5 6 b2 x2 A 6 7 b3 x3 A 7 8 b4 total A 8 9 a1 x1 B 9 10 a2 x2 B 10 11 a3 x3 B 11 12 a4 total B 12 13

问题 Let this be my data set: df <- data.frame(x1 = runif(1000), x2 = runif(1000), x3 = runif(1000), split = sample( c('SPLITMEHERE', 'OBS'), 1000, replace=TRUE, prob=c(0.04, 0.96) )) So, I have some variables (in my case, 15), and criteria by which I want to split the data.frame into multiple data.frames. My criteria is the following: each other time the 'SPLITMEHERE' appears I want to take all the values, or all 'OBS' below it and get a data.frame from just these observations. So, if there's 20

问题 This question already has answers here : Add column which contains binned values of an integer column (3 answers) Closed 2 years ago . Hope my title makes sense. I have a dataframe with a column of numeric values, and I would like to use this column to create a new column whereby the numeric values are 'mapped' to different buckets based on their values. Below is some test data, as well as a rough-around-the-edges nested ifelse() approach that I am currently using to solve this problem. I am

问题 I have a file that looks like this: type created_at repository_name 1 IssuesEvent 2012-03-11 06:48:31 bootstrap 2 IssuesEvent 2012-03-11 06:48:31 bootstrap 3 IssuesEvent 2012-03-11 06:48:31 bootstrap 4 IssuesEvent 2012-03-11 06:52:50 bootstrap 5 IssuesEvent 2012-03-11 06:52:50 bootstrap 6 IssuesEvent 2012-03-11 06:52:50 bootstrap 7 IssueCommentEvent 2012-03-11 07:03:57 bootstrap 8 IssueCommentEvent 2012-03-11 07:03:57 bootstrap 9 IssueCommentEvent 2012-03-11 07:03:57 bootstrap 10 IssuesEvent

问题 Hi I have two data frames: df1 = data.frame(PersonId1=c(1,2,3,4,5,6,7,8,9,10,1),PersonId2=c(11,12,13,14,15,16,17,18,19,20,11), Played_together = c(1,0,0,1,1,0,0,0,1,0,1), Event=c(1,1,1,1,2,2,2,2,2,2,2), Utility=c(20,-2,-5,10,30,2,1,.5,50,-1,60)) df2 = data.frame(PersonId1=c(11,15,9,1),PersonId2=c(1,5,19,11), Played_together = c(1,1,1,1), Event=c(1,2,2,2)) Where df1 looks like this: PersonId1 PersonId2 Played_together Event Utility 1 1 11 1 1 20.0 2 2 12 0 1 -2.0 3 3 13 0 1 -5.0 4 4 14 1 1 10

问题 I have a variable, and for some reason R has added an extra "X" in the beginning of each. Is this a common occurrence that I could have avoided? Anyhow, below is my data (currently the variable is stored in a list): X1 X5 X33 X37 ... > str(rc1_output) chr [1:63, 1:3] "X1" "X5" "X33" "X37" "X52" "X645" "X646" ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:63] "X1" "X5" "X33" "X37" ... ..$ : chr [1:3] "" "Entropy" "Subseq." > dput(head(rc1_output)) structure(c("X1", "X5", "X33", "X37", "X52",