**George J. Mount**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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This post follows a previous tutorial on pivoting on text in Excel. In this post I will reproduce the exercise in R. This way you begin to see the similarities and differences of the program and begin to diversify your data skill base.

**Related: 5 Things Excel Users Should Know About R — Free Mini-Course**

**Related: 5 Things Excel Users Should Know About R — Free Mini-Course**

Similar to the previous lesson, we will be using the 2017 .csv version of the Lahman baseball dataset. We will again be using the *People.csv *and *AwardsPlayers.csv *files.

**1. Set up our environment
**

In addition to reading in the two .csv files, we need to call two libraries for data manipulation: plyr and dplyr.

library(plyr) library(dplyr) players <- read.csv("C:/RFiles/people.csv") awards <- read.csv("C:/RFiles/awardsplayers.csv")

**2. Filter and merge tables**

Using the filter and select functions from dplyr, we create a table containing all awards information since 2010 by player ID, along with that player’s first and last name.

I include the nrow function to verify that indeed the resulting table in R has the same number of rows as the Excel table: 502.

awards <- filter(awards, yearID >= 2010) players <- select(players, playerID, nameFirst, nameLast) tbl <- merge(awards, players, all.x = TRUE) nrow(tbl)

**3. Derive “First Name Last Name” column**

Using the paste function with a space delimiter, we create a new column containing each player’s first and last name.

tbl$fullname <- paste(tbl$nameFirst, tbl$nameLast, sep = " ")

**4. Pivot and view results**

Now we use the ddply function from plyr to pivot on text. Similar to creating a measure in the Excel data model (Step 5 of the Excel post), we create a table summarized by awardID and yearID with the player name’s concatenated with a space delimiter (the paste function in R).

The View function then launches a spreadsheet-like viewer of the data frame.

x <- ddply(tbl, .(awardID, yearID), summarize, names = paste(fullname, collapse = ", ")) View(x)

Below I show the results in R and Excel — **they are the same. **Excel, however, does include a “subtotal” measure where R does not, but the base information is the same.

**Complete code below:**

#read in files and call libraries library(plyr) library(dplyr) players <- read.csv("C:/RFiles/people.csv") awards <- read.csv("C:/RFiles/awardsplayers.csv") #filter and merge data frames awards <- filter(awards, yearID >= 2010) players <- select(players, playerID, nameFirst, nameLast) tbl <- merge(awards, players, all.x = TRUE) nrow(tbl) #create full-name column tbl$fullname <- paste(tbl$nameFirst, tbl$nameLast, sep = " ") #pivot on full-name text x <- ddply(tbl, .(awardID, yearID), summarize, names = paste(fullname, collapse = ", ")) #launch spreadsheet-like viewer of data frame View(x)

**Related: 5 Things Excel Users Should Know About R — Free Mini-Course**

**Related: 5 Things Excel Users Should Know About R — Free Mini-Course**

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**George J. Mount**.

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