{"id":829,"date":"2018-05-19T19:27:38","date_gmt":"2018-05-19T17:27:38","guid":{"rendered":"https:\/\/blogs.fu-berlin.de\/reseda\/?page_id=829"},"modified":"2018-09-25T10:33:52","modified_gmt":"2018-09-25T08:33:52","slug":"e05","status":"publish","type":"page","link":"https:\/\/blogs.fu-berlin.de\/reseda\/e05\/","title":{"rendered":"R – Exercise V"},"content":{"rendered":"

1) Use ifelse()<\/span> and your data frame df<\/span> from exercise IV: If the person is less than or equal to 175 cm, it should have the attribute “small”, otherwise “tall”. Save the result in your df<\/span> as the new column size.category<\/span>.<\/p>\n

\r\nx <- ifelse(df$size <= 175, "small", "tall")\r\n\r\nx\r\n## [1] "small" "small" "tall" "tall" "small"\r\n\r\ndf$size.categorie <- x\r\n\r\ndf\r\n##    name age size    city weight size.categorie\r\n## 1  Anna  66  170 Hamburg  115.0          small\r\n## 2  Otto  53  174  Berlin  110.2          small\r\n## 3 Natan  22  182  Berlin   95.0          tall\r\n## 4   Ede  36  180 Cologne   87.0          tall\r\n## 5  Anna  32  174 Hamburg   63.0          small\r\n<\/pre>\n
2) Write a loop that outputs all integers from 5 to 15!<\/p>\n
\r\nvektor <- 5:15\r\nvektor\r\n##  [1]  5  6  7  8  9 10 11 12 13 14 15\r\n\r\nfor (i in vektor) {\r\n  print(i)\r\n}\r\n## [1] 5\r\n## [1] 6\r\n## [1] 7\r\n## [1] 8\r\n## [1] 9\r\n## [1] 10\r\n## [1] 11\r\n## [1] 12\r\n## [1] 13\r\n## [1] 14\r\n## [1] 15\r\n<\/pre>\n
3) Advanced: Create a for loop that outputs the arithmetic mean for each variable (column) of your data frame df<\/span> – provided that the variable is numeric!<\/p>\n
\r\nfor (i in 1:ncol(df)) {\r\n  \r\n  if (class(df[[i]]) == \"numeric\") {\r\n    print(names(df)[i])\r\n    result <- mean(df[[i]], na.rm=TRUE)\r\n    print(result)\r\n  }\r\n  \r\n}\r\n## [1] "age"\r\n## [1] 41.8\r\n## [1] "size"\r\n## [1] 176\r\n## [1] "weight"\r\n## [1] 94.04\r\n\r\n# Even if it looks complicated, take your time and go through it line by line. Everything should be known by now! \r\n<\/pre>\n
\n
\n