Understanding Poker Deck Simulation in R: Calculating Hand Probability with Unique Suits

Understanding Poker Deck Simulation in R

Poker is a popular card game played with a standard deck of 52 cards. In this blog post, we will explore how to simulate a poker deck in R and calculate the probability of drawing a hand consisting of only one suit.

Introduction to Poker Deck Simulation

A poker deck simulation involves generating a random sample of cards from a standard deck, where each card is assigned a unique identifier (e.g., a letter). We can then use this simulated deck to analyze various poker-related statistics, such as the probability of drawing a specific hand or the likelihood of certain outcomes.

Setting Up the Simulation

To begin our simulation, we need to define the structure of the poker deck. In R, we can use the LETTERS function to generate a set of unique identifiers for each card in the deck.

# Define the letters representing each suit (hearts, diamonds, clubs, spades)
pokerdeck <- rep(LETTERS[1:4], 13) # Hearts (A-M): A, B, C, D, E, F, G, H, I, J, K, L, M

In this example, we create a vector pokerdeck containing the letters A-M to represent the hearts suit. We repeat each letter 13 times to account for the 13 cards in a standard deck.

Creating the Simulated Deck

Next, we use the sample() function to generate a random sample of cards from our poker deck.

# Create a simulated deck by sampling from the poker deck
deck <- sample(x = pokerdeck, size = 52)

In this step, we create a vector deck containing 52 unique cards drawn from our pokerdeck. The sample() function randomly selects 52 cards from the pokerdeck, ensuring that each card appears exactly once in the simulated deck.

Defining the `checkDeck1()` Function

The checkDeck1() function is responsible for determining whether a given hand consists of only one suit. To achieve this, we need to analyze the uniqueness of the cards in the hand.

# Define the checkDeck1() function
checkDeck1 <- function(deck) {
  # Identify unique cards in the first 13 positions of the deck
  uniquedeck <- unique(deck[1:13])
  
  # Check if there is only one unique suit (card)
  if (length(uniquedeck) == 1) {
    return(TRUE)
  } else {
    return(FALSE)
  }
}

In this function, we first extract the first 13 cards from our simulated deck using deck[1:13]. We then use the unique() function to identify the unique cards in this subset. If there is only one unique card, we return TRUE, indicating that the hand consists of only one suit. Otherwise, we return FALSE.

Calling the `checkDeck1()` Function

To demonstrate how to call the checkDeck1() function, we create an instance of our simulated deck and pass it to the function.

# Create a sample deck and check if it has only one suit
deck <- sample(x = pokerdeck, size = 52)
result <- checkDeck1(deck)

print(result) # Output: [1] TRUE or FALSE

In this example, we create a new deck instance by sampling from our pokerdeck. We then call the checkDeck1() function with this deck as an argument and print the resulting value.

Understanding the Error

The original error message indicates that the variable uniquedeck is missing, which means that the scope of the variable deck was local. To resolve this issue, we need to ensure that the checkDeck1() function has access to the simulated deck.

# Modify the checkDeck1() function to accept a single argument (deck)
checkDeck1 <- function(deck) {
  # Identify unique cards in the first 13 positions of the deck
  uniquedeck <- unique(deck[1:13])
  
  # Check if there is only one unique suit (card)
  if (length(uniquedeck) == 1) {
    return(TRUE)
  } else {
    return(FALSE)
  }
}

By modifying the function signature to accept a single argument deck, we ensure that the function has access to our simulated deck and can correctly determine whether it consists of only one suit.

Conclusion

In this blog post, we explored how to simulate a poker deck in R and calculate the probability of drawing a hand consisting of only one suit. We discussed various aspects of the simulation, including setting up the deck, creating the simulated deck, defining the checkDeck1() function, and calling it with our simulated deck.

By understanding these concepts and implementing them correctly, you can create your own poker deck simulations in R to analyze and visualize various poker-related statistics.

Additional Examples

Here are a few additional examples of how to use the checkDeck1() function:

# Create multiple decks and check their suits
deck1 <- sample(x = pokerdeck, size = 52)
deck2 <- sample(x = pokerdeck, size = 52)

result1 <- checkDeck1(deck1)
result2 <- checkDeck1(deck2)

print(result1) # Output: [1] TRUE or FALSE
print(result2) # Output: [1] TRUE or FALSE

# Create a deck with multiple suits and check its suit distribution
deck <- sample(x = pokerdeck, size = 52, replace = TRUE)
result <- checkDeck1(deck)

if (result) {
  print("The deck has only one suit.")
} else {
  print("The deck has more than one suit.")
}

These examples demonstrate how to use the checkDeck1() function with different decks and analyze their suit distributions.

References

R Core Team. (2022). R: A Language and Environment for Statistical Computing. Retrieved from https://www.R-project.org/
Hadley Wickham. (2019). Advanced R. Springer. ISBN 978-3-319-18830-7
Richard W. Seager. (2004). Practical Statistics Using R: A Guide to Data Analysis and Visualization. Springer.

Note that the references are fictional and intended for illustration purposes only.

Last modified on 2023-11-25