I am new to R programming and attempting to remove certain rows per a group of rows after a filtering criteria has been met.
I've looked at other answers but cannot find a solution for the code below to work. Basically, I'm creating a function that inner_join the two data frame and filter based on a column inputted in the function.
I've tried searching through the forums and unable to find help. I'm quite new to R, and am having limited success in loading in some strings to be used as a formula.
I have data as follows and I want to create new variable that takes into account the preceding information in the prior period. For example,
This is my dataframe:I want to extract col1=df[] as a dataframe. Then col1 of the second position of this list I want to merge to the df[], then I will have a dataframe with 2 columns. After this I want to merge the column 1 of the third position of...
There are great questions and answers on how to move a column to the first or last place.Using dplyr The best answers are respectively analog to :
Suppose this is my datasetI need calculate frequency for two groupsand for variable var1, calculate count of 1 value and 2 value. For each group. So the desired output
I am trying to calculate p.values with a students t-test within a very huge data frame in the long data format. Since my original data frame has about lines within the data frame, the calculation of the p.values takes very long (took about 100 Minutes).
I have a data frame with patient encounters, and want to extract only the oldest encounter for each patient (which can be done using the sequential encounter ID). The code I came up with works, but I'm sure there are more efficient ways to perform this task using dplyr. What...
I'm aware of similar questions here and here, but I haven't been able to figure out the right solution for my specific situation. Some of what I'm finding are solutions which use mutate_, etc but I understand these are now obsolete. I'm new to dynamic usages of dplyr.