This question already has answers here:
Filter multiple values on a string column in dplyr
(6 answers)
Closed 2 years ago.
I would like to filter values based on one column with multiple values.
For example, one data.frame has s&p 500 tickers, i have to pick 20 of them and associated closing prices. How to do it?
If I understand well you question, I believe you should do it with dplyr:
library(dplyr)
target <- c("Ticker1", "Ticker2", "Ticker3")
filter(df, Ticker %in% target)
The answer can be found in https://stackoverflow.com/a/25647535/9513536
Cheers !
Related
This question already has answers here:
How do I delete rows in a data frame?
(10 answers)
Closed 1 year ago.
So I've been trying to subset and remove the observations of a country from my data frame (ESS6). I have been able to remove certain variables with this function, -c(variable), but that is not useful since I only want to remove certain rows from the variable countries (cntry).
Thank you for your help :)
Try using dplyr and the "filter" function
This question already has answers here:
How to remove columns with same value in R
(4 answers)
Closed 2 years ago.
I have a really large dataset and I want to filter out some of the columns because it is the same data all throughout (ex: company name is all "Walmart"). I can go through and do these manually but I'm looking for a code to do it automatically.
I had in mind a function to subset based on if sum(unique(colnam)) == 1 but not sure how to get it to work. Thanks.
which(sapply(dat, function(col) length(unique(col)) == 1))
This question already has answers here:
How to sum a variable by group
(18 answers)
Closed 3 years ago.
I have three columns; loan_id, amount, date. I have 1,048,575 entries and I need to add together all the duplicates in loan_id column(there are different payments on the same loan_id) and in the second table the amount values should be added together matching with the loan_id.
Sample of how my data looks like this
Try
aggregate(df$amount,list(df$loan_id),sum)
So you want the total amount for each loan_id irrespective of date?
One way to do aggregate functions like this in R is by using the data.table package.
library(data.table)
# assuming you start with a data.frame
mydata = data.table(mydata)
mydata[,sum(amount), by=loan_id]
This question already has answers here:
dplyr - using mutate() like rowmeans()
(8 answers)
Closed 4 years ago.
I currently have a table in R with 4 columns and I want to average the last two columns (titled W10CP1 and W10CP2) into a 5th column of that table.
I tried to use rowMeans but I got an error.
Sorry for the basic question!
You can try use the tydeverse package here an example:
library(tidyverse)
data<-data%>%
mutate(mean= (data[,-1] +data[,-2]/2))
This question already has answers here:
Sort (order) data frame rows by multiple columns
(19 answers)
Closed 6 years ago.
I want to sort a variable in the dataset.
la3 <-order(la1$Id)
Iam getting the output as index. How to get the output as real values in the datatset
la3 <-la1[order(la1$Id),]
The length of the order will correspond to the length of the column and specify the ordered position.
Using an index call of the original data will therefore put the rows in that order.
Using dplyr
library(dplyr)
la1 %>%
arrange(Id)