Perfect! Of course, most of the time you'll create new columns using information from other columns in a data frame. For example, the avg_price column currently represents average housing prices in Euros.
Let's create an additional column called avg_price_usd that will represent average housing prices in dollars. We'll use existing columns to calculate this price: avg_price (which is the average price in Euros), and conversion_rate (which equals 1.20). Here's the expression:
quarter_prices$avg_price_usd <- quarter_prices$avg_price * quarter_prices$conversion_rate
This expression will create a vector with average price converted to USD and it will assign this vector to a new column avg_price_usd in the quarter_prices data frame.
| period | avg_price | conversion_rate | avg_price_usd |
|---|---|---|---|
| Q1 2017 | 170195 | 1.20 | 204234 |
| Q2 2017 | 173937 | 1.20 | 208724 |
| Q3 2017 | 177938 | 1.20 | 213526 |
Chris would like to know the price per square meter for each property that is on sale in Cibaly. The price per square meter for a property can be calculated with the following formula:
price / living_area
Use the price and living_area columns from the houses data frame to calculate the price per square meter for each property. Store the results in a column named price_per_sq_meter.
