I have two files with huge data set, below is the sample data mentioned,
Trying to map Unique BIN number from 2nd file to 1st one(output as below)
I am able to create this in excel by using the countif function with multiple conditions but unable to do it in R. pls help to create code for the same.
Can you explain how to build this logic using R
Related
I want to use the activity_stats function (and others) on a data set that has several dozen subjects. Based on the documentation, it looks like I have to make a separate data frame for each subject, and then run the functions on each individual data frame. Is that the case?
https://github.com/martakarass/arctools#using-arctools-package-to-compute-physical-activity-summaries
Apologies if this has already been answered somewhere else.
So I have a dataset in R that contains a certain amount of variables. When I preview it some of the variables I need for my analysis are there but outside the count of the variables as if they were in subsections of the dataframe itself.
Now I managed to access some of it using sapply (these were sublists in the dataframe) but there are several others I cannot.
I am still unable to access a column that is containing the country information for my data set.
It looks as if it is contained in another variable.
Any suggestions how to bring this variable on the same plane as the others in the data set and eliminate subfolders?
Hi so I have two nearly identical data sets, however one has some values the other doesn't and I'm trying to compare them in R. I'm trying to create a list of the observations in the two data sets that aren't shared between the two, but I'm struggling with how to do this. I'm relatively new to R.
You should try the arsenal package.
try
install.packages("arsenal")
library(arsenal)
captureVariable <- summary(arsenal::comparedf(list1,list2))
captureVariable[["diffs.byvar.table"]]
There are some other helpful outputs that will be captured by captureVariable if that particular table doesn't suit your needs.
Example output of tab_model
I have created a table from tab_model that includes multiple models and wish to extract all 'p-values' and 'Estimates/Odds Ratio' to create a data frame that includes these. Output of tab_model is an html file. I am unable to find a function to pull this info in accordance, any ideas on how I could do this?
For example, I want to retrieve all p-values and Estimates for variable 'age' in all of my models...Only 3 in example image but I have hundreds
You should get these values from the regression models themselves, instead of outputting them to a HTML-table, and then extract them.
Without further knowledge of your process and data it is difficult to provide a more concrete answer.
I have a question about the setup and execution of a function to some multivariate data.
My data file is set up in excel with each variable as individual sheets, and each trajectory as a row of data (100 trajectories in total). The values within each row across 365 columns show the measurements associated with the respective variable across time (daily measurements over 1 year).
I’ve done some analysis of 1 trajectory by setting up my data manually in a separate excel file, where I’ve got 16 columns containing separate variables, and 365 rows containing the associated data from each daily measurement. I’ve imported this into R as ‘Traj1’ and set up the function as follows;
> T1 <- Traj1[,1:16]
> multi.fun <- function(T1) {c(summary(T1),sd(T1), skewness(T1), kurtosis(T1), shapiro.test(T1))}
However, I need to do this with 100 trajectories, and this is extremely inefficient (both in R and Excel time).
I’m not sure how best to set this up in R with my initial excel file set up, and how this function should be set up so that I can batch execute and export the output into a new excel file.
Sorry I am new to programming in general and haven’t had much experience in dealing with large data sets. Any help is really appreciated.