R folks:
I have a dataframe with many sets of columns. Each set is a bank of survey items. I would like to count the number of columns in each set having a certain value. I wrote a function to do this but it results in a list of repeated values that is appended to my dataframe.
df<- structure(list(RespondentID = c(6764279930, 6779986023, 6760279439,
6759243066),
q1 = c(3L, 3L, 4L, 1L),
q2 = c(2L, 2L, 4L, 4L),
q3 = c(4L, 2L, 4L, 5L),
q0010_0004 = c(1L, 2L, 3L, 1L)),
.Names = c("RespondentID", "q1", "q2", "q3", "q4"),
row.names = c(NA, 4L), class = "data.frame")
group1<-c("q1","q2","q3","q4")
# Objective: Count number of ratings==4 for each row
# Make function that receives list of columns &
# then returns ONE column in dataframe with total # columns
# having certain value (in this case, 4)
countcol<-function(colgroup) {
s<-subset(df, select=c(colgroup)) #select only the columns designated by list
s$sum<-Reduce("+", apply(X=s,1,FUN=function(x) (sum(x==4, na.rm = TRUE)))) # count instances of value==4
s2<-subset(s,select=c(sum)) # return ONE column with result for each row
return(s2$sum) }
countcol(group1)
My function, countcol runs without errors but as stated above results in what appears to be a transposed list of results for each row. I would like to have ONE number for each row that indicates the count of values.
I attempted various apply functions here but could not prevail. Anyone have a tip?
Thanks!
rowSums can give you results OP is looking for. This return count of ratings==4 for each group.
rowSums(df[2:5]==4)
#1 2 3 4
#1 0 3 1
OR just part of function from OP can give answer.
apply(df[2:5], 1, function(x)(sum(x==4)))
#1 2 3 4
#1 0 3 1
Related
Hi I have been trying for a while to match two large columns of names, several have different spellings etc... so far I have written some code to practice on a smaller dataset
examples%>% mutate(new_ID = case_when(mapply (adist, example_1 , example_2) <= 3 ~ example_1, TRUE ~ example_2))
This manages to create a new column with names the name from example 1 if it is less than an edit distance of 3 away. However, it does not give the name from example 2 if it does not meet this criteria which I need it to do.
This code also only works on the adjacent row of each column, whereas, I need it to work on a dataset which has two columns (one is larger- so cant be put in the same order).
Also needs to not try to match the NAs from the smaller column of names (there to fill it out to equal length to the other one).
Anyone know how to do something like this?
dput(head(examples))
structure(list(. = structure(c(4L, 3L, 2L, 1L, 5L), .Label = c("grarryfieldsred","harroldfrankknight", "sandramaymeres", "sheilaovensnew", "terrifrank"), class = "factor"), example_2 = structure(c(4L, 2L, 3L, 1L,
5L), .Label = c(" grarryfieldsred", "candramymars", "haroldfranrinight",
"sheilowansknew", "terryfrenk"), class = "factor")), row.names = c(NA,
5L), class = "data.frame")
The problem is that your columns have become factors rather than character vectors. When you try to combine two columns together with different factor levels, unexpected results can happen.
First convert your columns to character:
library(dplyr)
examples %>%
mutate(across(contains("example"),as.character)) %>%
mutate(new_ID = case_when(mapply (adist, example_1 , example_2) <= 3 ~ example_1,
TRUE ~ example_2))
# example_1 example_2 new_ID
#1 sheilaovensnew sheilowansknew sheilowansknew
#2 sandramaymeres candramymars candramymars
#3 harroldfrankknight haroldfranrinight harroldfrankknight
#4 grarryfieldsred grarryfieldsred grarryfieldsred
#5 terrifrank terryfrenk terrifrank
In your dput output, somehow the name of example_1 was changed. I ran this first:
names(examples)[1] <- "example_1"
I am reposting this question with a bit of more clarity. Unfortunately, didn't get any solutions from my previous posting. Please help me with this.
Below is what I want to do:
I have a dataset with the name of proteome. It has 14 columns and thousands of rows.
Row 1, column 5: GHFCLKPGCNFHAESTRGYR
Row 2, column 5: FCLKPGCNFHAESTRGYR
Row 3, column 5: GHFCLKPGCNFHAESTR
Row 4: column 5: GCNFHAESTR
Please click on this link to see the screenshot of a part of the original data frame; i67.tinypic.com/2wd0ap3.png[/IMG]
So, In row 2, first two letters of row 1 are missing; in row 3, last three letters of row 1 are missing; in row 4, first seven and last three letters of row 1 are missing.
Rows 2, 3, and 4 reflect the artifacts of the scientific method I have been using to generate the data, and therefore I want to remove these entries.
I want R to return only one of the four rows, ideally row 1, and remove the rest. The way R can do it is by first finding all rows with a matching string of letters and then eliminating such rows while keeping only one. For example, in the above data set, GCNFHAESTR match in all four rows, so I want R to return me only one row, ideally the top one. But I don't know how to do this.
Hope this makes better sense this time. I look forward to hearing from the experts.
Thanks!
In response to Julian_Hn suggestion, here is the dput of my dataset:
dput(Proteome)
structure(list(Protein.name = structure(c(1L, 1L, 1L, 1L, 2L,
3L), .Label = c("HCTF", "IFT", "ROSF"), class = "factor"), X..Proteins = c(5L,
5L, 5L, 5L, 3L, 7L), X..PSMs = c(3L, 1L, 6L, 2L, 2L, 4L), Previous.5.amino.acids = structure(c(4L,
5L, 4L, 2L, 3L, 1L), .Label = c("CWYAT", "FCLKP", "MGCPT", "NCTMY",
"TMYFC"), class = "factor"), Sequence = structure(c(5L, 1L, 4L,
2L, 3L, 6L), .Label = c("FCLKPGCNFHAESTRGYR", "GCNFHAESTR", "GFGFNWPHAVR",
"GHFCLKPGCNFHAESTR", "GHFCLKPGCNFHAESTRGYR", "GNFSVKLMNR"), class = "factor")), .Names = c("Protein.name",
"X..Proteins", "X..PSMs", "Previous.5.amino.acids", "Sequence"
), class = "data.frame", row.names = c(NA, -6L))
I have a large dataframe and I have a vector to pull out terms of interest. for a previous project I was using:
a=data[data$rn %in% y, "Gene"]
To pull out information into a new vector. Now I have a another job Id like to do.
I have a large dataframe of 15 columns and >100000 rows. I want to search column 3 and 9 for the content in the vector and print this as a new dataframe.
To make this extra annoying the hit could be in v3 and not in v9 and visa versa.
Working example
I have striped the dataframe to 3 cols and few rows.
data <- structure(list(Gene = structure(c(1L, 5L, 3L, 2L, 4L), .Label = c("ibp","leuA", "pLeuDn_02", "repA", "repA1"), class = "factor"), LocusTag = structure(c(1L,2L, 5L, 3L, 4L), .Label = c("pBPS1_01", "pBPS1_02", "pleuBTgp4","pleuBTgp5", "pLeuDn_02"), class = "factor"), hit = structure(c(2L,4L, 3L, 1L, 5L), .Label = c("2-isopropylmalate synthase", "Ibp protein","ORF1", "repA1 protein", "replication-associated protein"), class = "factor")), .Names = c("Gene","LocusTag", "hit"), row.names = c(NA, 5L), class = "data.frame")
y <- c("ibp", "orf1")
First of all R is case sensitive so your example will not collect the third line but I guess you want that extracted. so you would have to change your y to
y <- c("ibp", "ORF1")
Ok from your example I try to see what you want to achieve I am not sure if this is really what you want but R knows the operator | as "or" so you could try something like:
new.data<-data[data$Gene %in% y|data$hit %in% y,]
if you only want to extract certain columns of your data set you can specify them behind the "," e.g.:
new.data<-data[data$Gene %in% y|data$hit %in% y, c("LocusTag","Gene")]
My objective is to get a count on how many duplicate are there in a column.So i have a column of 3516 obs. of 1 variable, there are all dates with about 144 duplicate each from 1/4/16 to 7/3/16. Example:(i put 1 duplicate each for example sake)1/4/161/4/1631/3/1631/3/1630/3/1630/3/1629/3/1629/3/1628/3/1628/3/16so i used the function date = count(date)where date is my df date.But once i execute it my date sequence is not in order anymore. Hope someone can solve my problem.
If we need to count the total number of duplicates
sum(table(df1$date)-1)
#[1] 5
Suppose, we need the count of each date, one option would be to group by 'date' and get the number of rows. This can be done with data.table.
library(data.table)
setDT(df1)[, .N, date]
If you want the count of number of duplicates in your column , you can use duplicated
sum(duplicated(df$V1))
#[1] 5
Assuming V1 as your column name.
EDIT
As per the update if you want the count of each data, you can use the table function which will give you exactly that
table(df$V1)
#1/4/16 28/3/16 29/3/16 30/3/16 31/3/16
# 2 2 2 2 2
library(dplyr)
library(janitor)
df%>% get_dupes(Variable) %>% tally()
You can add group_by in the pipe too if you want.
One way is to create a data frame with unique values of your initial data which will preserve the order and then use left_join from dplyr package to join the two data frames. Note that the name of your column should be the same.
Initial_data <- structure(list(V1 = structure(c(1L, 1L, 5L, 5L, 4L, 4L, 3L, 3L,
2L, 2L, 2L), .Label = c("1/4/16", "28/3/16", "29/3/16", "30/3/16",
"31/3/16"), class = "factor")), .Names = "V1", class = "data.frame", row.names = c(NA,
-11L))
df1 <- unique(Initial_data)
count1 <- count(df1)
left_join(df1, count1, by = 'V1')
# V1 freq
#1 1/4/16 2
#2 31/3/16 2
#3 30/3/16 2
#4 29/3/16 2
#5 28/3/16 3
if you want to count number of duplicated records use:
sum(duplicated(df))
and when you want to calculate the percentage of duplicates use:
mean(duplicated(df))
I have a large amount of graph data in the following form. Suppose a person has multiple interests.
person,interest
1,1
1,2
1,3
2,1
2,5
2,2
3,2
3,5
...
I want to construct all pairs of interests for each user. I would like to convert this into an edgelist like the following. I want the data in this format so that I can convert it into an adjacency matrix for graphing etc.
person,x_interest,y_interest
1,1,2
1,1,3
1,2,3
2,1,5
2,1,2
2,5,2
3,2,5
There is one solution here: Pairs of Observations within Groups but it works only for small datasets as the call to table wants to generate more than 2^31 elements. Is there another way that I can do this without having to rely on table?
We can use data.table. We convert the 'data.frame' to 'data.table' (setDT(df1), grouped by 'person', we get the unique pairwise combinations of 'interest' to create two columns ('x_interest' and 'y_interest').
library(data.table)
setDT(df1)[,{tmp <- combn(unique(interest),2)
list(x_interest=tmp[c(TRUE, FALSE)], y_interest= tmp[c(FALSE, TRUE)])} , by = person]
NOTE: To speed up, combnPrim from library(gRbase) could be used in place of combn.
data
df1 <- structure(list(person = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L),
interest = c(1L,
2L, 3L, 1L, 5L, 2L, 2L, 5L)), .Names = c("person", "interest"
), class = "data.frame", row.names = c(NA, -8L))