Module # 3 Data.frame

 

Exploring Fictional 2016 Presidential Election Poll Results

In this blog post, we delve into a fictional dataset based on the 2016 presidential election. It's essential to note that this data is entirely fabricated and does not reflect the actual events of the election. The purpose is to explore the dynamics of political polls and the insights we can gain from them.

The Candidates:

Let's begin by introducing the candidates included in our fictional poll:

- Jeb

- Donald

- Ted

- Marco

- Carly

- Hillary

- Bernie

Poll Results:

We have two sources for our poll data: ABC and CBS. The poll results for each candidate from these sources are as follows:

```R

# Creating the data

Name <- c("Jeb", "Donald", "Ted", "Marco", "Carly", "Hillary", "Bernie")

ABC_poll_results <- c(4, 62, 51, 21, 2, 14, 15)

CBS_poll_results <- c(12, 75, 43, 19, 1, 21, 19)

```

Visualizing the Data:

Let's create visualizations to better understand the poll results. Bar charts can effectively represent the support for each candidate according to ABC and CBS polls.

```R

# Creating bar charts

barplot(ABC_poll_results, names.arg = Name, beside = TRUE, col = "skyblue", main = "ABC Poll Results")

barplot(CBS_poll_results, names.arg = Name, beside = TRUE, col = "lightcoral", main = "CBS Poll Results")

```

Conclusion:

In this fictional exploration of the 2016 presidential election poll data, we've visualized and analyzed the support for various candidates according to ABC and CBS polls. Remember, these results are entirely hypothetical, but the process of data analysis and interpretation remains valuable. By understanding the dynamics of political polls, we gain insights into the complexities of public opinion and the factors influencing electoral outcomes.