Excel reference functions are used to efficiently lookup values from a data source. The most popular lookup function is "VLOOKUP", which has been implemented in R.
These functions are designed to help users coming from an Excel background. Most functions replicate the behavior of Excel:
Names are similar to Excel function names
Functionality replicates Excel
Details
VLOOKUP()
Details
Performs exact matching only. Fuzzy matching is not implemented.
Can only return values from one column only. Use
dplyr::left_join()
to perform table joining.
Examples
library(dplyr)
lookup_table <- tibble(
stock = c("META", "AMZN", "NFLX", "GOOG"),
company = c("Facebook", "Amazon", "Netflix", "Google")
)
# --- Basic Usage ---
VLOOKUP("NFLX",
.data = lookup_table,
.lookup_column = stock,
.return_column = company)
#> [1] "Netflix"
# --- Usage with tidyverse ---
# Add company names to the stock data
FANG %>%
mutate(company = VLOOKUP(symbol, lookup_table, stock, company))
#> # A tibble: 4,032 × 9
#> symbol date open high low close volume adjusted company
#> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 META 2013-01-02 27.4 28.2 27.4 28 69846400 28 Facebook
#> 2 META 2013-01-03 27.9 28.5 27.6 27.8 63140600 27.8 Facebook
#> 3 META 2013-01-04 28.0 28.9 27.8 28.8 72715400 28.8 Facebook
#> 4 META 2013-01-07 28.7 29.8 28.6 29.4 83781800 29.4 Facebook
#> 5 META 2013-01-08 29.5 29.6 28.9 29.1 45871300 29.1 Facebook
#> 6 META 2013-01-09 29.7 30.6 29.5 30.6 104787700 30.6 Facebook
#> 7 META 2013-01-10 30.6 31.5 30.3 31.3 95316400 31.3 Facebook
#> 8 META 2013-01-11 31.3 32.0 31.1 31.7 89598000 31.7 Facebook
#> 9 META 2013-01-14 32.1 32.2 30.6 31.0 98892800 31.0 Facebook
#> 10 META 2013-01-15 30.6 31.7 29.9 30.1 173242600 30.1 Facebook
#> # ℹ 4,022 more rows