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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

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.

Source

Yahoo! Finance, retrieved 2012-03-08.

Examples


library(ggplot2)

ggplot(sp500, aes(x = ent_value, y = earn_before)) +
  geom_point() +
  labs(x = "Enterprise value", y = "Earnings")
#> Warning: Removed 3 rows containing missing values (geom_point).


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")
#> Warning: Removed 3 rows containing missing values (geom_point).


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"
  )