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I want to create a new column in a data.frame where its value is equal to the value in another data.frame where a particular condition is satisfied between two columns in each data frame.
The R pseudo-code being something like this:
DF1$Activity <- DF2$Activity where DF2$NAME == DF1$NAME
In each data.frame values for $NAME are unique in the column.
467
Replace column values based on checking logical conditions in R DataFrame is pretty straightforward. All you need to do is select the column vector you wanted to update and use the condition within [] .
To add a new column to a dataframe in R you can use the $-operator. For example, to add the column “NewColumn”, you can do like this: dataf$NewColumn <- Values . Now, this will effectively add your new variable to your dataset.
We reference a data frame column with the double square bracket "[[]]" operator. For example, to retrieve the ninth column vector of the built-in data set mtcars, we write mtcars[[9]].
To create a data frame with a column having repeated values, we simply need to use rep function and we can repeat the values in a sequence of the values passed or repeating each value a particular number of times.
without an example its quite hard to tell. But from your description it sounds like a base::merge or dplyr::inner_join operation. Those are quite fast in comparison to if statements.
Cheers
59
Use the ifelse function. Here, I put NA when the condition is not met. However, you may choose any value or values from any vector.
Recycling rules1 apply.
DF1$Activity <- ifelse(DF2$NAME == DF1$NAME, DF2$Activity, NA)
I'm not sure this one actually needs an example. What happens when you create a column with a set of NA values and then assign the required rows with the same logical vector on both sides:
DF1$Activity <- NA
DF1$Activity[DF2$NAME == DF1$NAME] <- DF2$Activity[DF2$NAME == DF1$NAME]
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