sp500: Financial information for 50 S&P 500 companies

Description

Fifty companies were randomly sampled from the 500 companies in the S&P 500, and their financial information was collected on March 8, 2012.

Usage

sp500

Arguments

Format

A data frame with 50 observations on the following 12 variables.

market_cap: Total value of all company shares, in millions of dollars.
stock: The name of the stock (e.g. AAPL for Apple).
ent_value: Enterprise value, which is an alternative to market cap that also accounts for things like cash and debt, in millions of dollars.
trail_pe: The market cap divided by the earnings (profits) over the last year.
forward_pe: The market cap divided by the forecasted earnings (profits) over the next year.
ev_over_rev: Enterprise value divided by the company's revenue.
profit_margin: Percent of earnings that are profits.
revenue: Revenue, in millions of dollars.
growth: Quartly revenue growth (year over year), in millions of dollars.
earn_before: Earnings before interest, taxes, depreciation, and amortization, in millions of dollars.
cash: Total cash, in millions of dollars.
debt: Total debt, in millions of dollars.

Examples

Run this code

# NOT RUN {
library(ggplot2)

ggplot(sp500, aes(x = ent_value, y = earn_before)) +
  geom_point() +
  labs(x = "Enterprise value", y = "Earnings")

ggplot(sp500, aes(x = ev_over_rev, y = forward_pe)) +
  geom_point() +
  labs(x = "Enterprise value / revenue, logged",
       y = "Market cap / forecasted earnings, logged")

ggplot(sp500, aes(x = ent_value, y = earn_before)) +
  geom_point() +
  scale_x_log10() +
  scale_y_log10() +
  labs(x = "Enterprise value", y = "Earnings")

ggplot(sp500, aes(x = ev_over_rev, y = forward_pe)) +
  geom_point() +
  scale_x_log10() +
  scale_y_log10() +
  labs(x = "Enterprise value / revenue, logged",
       y = "Market cap / forecasted earnings, logged")

# }

Run the code above in your browser using DataCamp Workspace