Well done! You can use multiple columns in conditions. Consider this example: You want to create a column named clean_ownership in the houses data frame that indicates whether a particular property's paperwork is in order.
Here are the conditions we'll use for creating this column:
usage_permit, ownership_licence, ownership_licence are all marked with "Y".clean_ownership should be populated with "No".First, we'll create the new clean_ownership column and populate it with an initial value of "No" for all rows:
houses$clean_ownership <- "No"
Afterwards, we'll overwrite "No" with "Yes" for rows that satisfy the clean ownership conditions:
houses[ houses$usage_permit == "Y" & houses$building_permit == "Y" & houses$ownership_licence == "Y",]$clean_ownership <- "Yes"
A client is searching a house that has a decorated yard. We'll define a "decorated yard" as one that has a pool, garden, or both. Create a new column named garden_decorated in the houses data frame. The column is set to "Yes" if at least one of the columns has_pool or has_garden is populated with "Y".
First you should populate the garden_decorated column with "No". Then populate the column with "Yes" according to the given condition:
houses[houses$has_pool == "Y" | houses$has_garden == "Y",]$garden_decorated <-"Yes"
