Perform vlookup and fill down in R: Excel-like guide

If you're familiar with Excel, you're probably familiar with the VLOOKUP function. It's a powerful tool that allows you to search for a specific value in a range of cells and return a corresponding value from another column in that range. But what if you're working in R and need to perform a similar task? Fortunately, there's a way to replicate the functionality of VLOOKUP in R using the dplyr package.

To start, you'll need to load your data into R using the read.csv function. Once you have your data loaded, you can use the left_join function from dplyr to merge two data frames based on a common column. The left_join function works by matching the values in the common column of the two data frames and returning a new data frame with the matching rows combined.

For example, let's say you have two data frames: one with a list of products and their prices, and another with a list of customer orders. You want to add a column to the customer orders data frame that shows the price of each product. To do this, you can use the left_join function to match the product names in the two data frames and combine the corresponding rows.

library(dplyr)

# Load the data
products <- read.csv("products.csv")
orders <- read.csv("orders.csv")

# Merge the two data frames
merged_data <- left_join(orders, products, by = "Product")

# Fill in missing values using fill()
merged_data <- fill(merged_data, Price)

In addition to left_join, you can also use other dplyr functions like filter, mutate, and select to manipulate your data as needed. And if you need to fill in missing values (similar to the "fill down" functionality in Excel), you can use the fill function from the tidyr package.

With these tools at your disposal, you can perform VLOOKUP-like operations in R with ease. So the next time you need to search for a value in a data frame and return a corresponding value from another column, give dplyr a try.