You can use the following syntax to calculate lagged values by group in R using the dplyr package: df %>% group_by (var1) %>% mutate (lag1_value = lag (var2, n=1, order_by=var1)) Note: The mutate () function adds a new variable to the data frame that contains the lagged values.
Full Answer
What is lag in R with a time series?
When a data scientist does a lag in r with a time series there is a simple function for the task. Doing a lag on a time series pushes the data back to an earlier time depending upon the size of the lag. This lag can be any integer value.
How to compute a lagged version of a time series?
Compute a lagged version of a time series, shifting the time base back by a given number of observations. lag is a generic function; this page documents its default method. lag (x, …) # S3 method for default lag (x, k = 1, …) A vector or matrix or univariate or multivariate time series The number of lags (in units of observations). …
Why do I get an error when using the lag function?
In other cases, you can get an error message or meaningless results. When using the lag function, it takes the value of the lag and shifts the data that a number of months. By using a negative number for the lag, you can produce a lead in the data. This function will not work with a vector, data frame, or another variable, other than a time series.
Why do we use a negative lag for lag?
By using a negative number for the lag, you can produce a lead in the data. This function will not work with a vector, data frame, or another variable, other than a time series. This makes it extremely easy to understand because all you are doing is shifting the data a certain number of months.
Using Lag To Calculate Time Between Events in R and SQL
Last week, amidst building some dashboards for the customer experience team at work, I came across an interesting problem, which led me to a cool function called lag () that I hadn’t come across before.
The Problem
Our customer experience data comes from a messaging platform called Intercom. After some preliminary cleaning steps (damn you, nested JSON files!), my data looked broadly like this:
Introduction of Example Data
The first step is to create some data that we can use in the examples later on:
Example: Create Lagged Variable by Group Using dplyr Package
In this example, I’ll illustrate how to use the functions of the dplyr package to add a new column with lagged values for each group to our data frame.
Video & Further Resources
I have recently released a video on my YouTube channel, which shows the R programming codes of this article. You can find the video below.
