solution-exercise2.Rmd

---
title: "Exercise 2"
author: "Mark Dunning"
date: '`r format(Sys.time(), "Last modified: %d %b %Y")`'
output: pdf_document
---


```{r}
age    <- c(50, 21, 35, 45, 28, 31, 42, 33, 57, 62)
weight <- c(70.8, 67.9, 75.3, 61.9, 72.4, 69.9, 
            63.5, 71.5, 73.2, 64.8)

firstName  <- c("Adam", "Eve", "John", "Mary",
                "Peter", "Paul", "Joanna", "Matthew",
                "David", "Sally")
secondName <- c("Jones", "Parker", "Evans", "Davis",
                "Baker","Daniels", "Edwards", "Smith", 
                "Roberts", "Wilson")

consent <- c(TRUE, TRUE, FALSE, TRUE, FALSE, 
             FALSE, FALSE, TRUE, FALSE, TRUE)

sex <- c("Male", "Female", "Male", "Female", "Male",
         "Male", "Female", "Male", "Male", "Female")

patients <- data.frame(First_Name = firstName, 
                       Second_Name = secondName, 
                       Full_Name = paste(firstName,
                                         secondName), 
                       Sex = factor(sex),
                       Age = age,
                       Weight = weight,
                       Consent = consent,
                       stringsAsFactors = FALSE)
patients

```

- Write R code to print the following subsets of the patients data frame
- The first and second rows, and the first and second colums

```{r}
patients[1:2,1:2]
```

- All rows, but in the order 10 to 1.

```{r}
patients[10:1,]
```

- All rows except the first row, all columns

```{r}
patients[-1,]
```

- Use logical indexing to select the following patients from the data frame:
    1. Patients under 40
    2. Patients who give consent to share their data
    3. Men who weigh as much or more than the average European male (70.8 kg)
    
```{r}
patients[patients$Age < 40,]
```


```{r}
patients[patients$Consent,]
```

```{r}
patients[patients$Sex == "Male" & patients$Weight >= 70.8,]
```