
```{R}
library(tidyverse)
library(HumanitiesDataAnalysis)
```

Two functions you may use again in R are called `intToUtf8` and
`utf8ToInt`. They convert *between* the numbers that represent Unicode
points, and the actual characters.

1.  **Vectors** in R are the underlying elements of datasets. In the
    movie ‘2001,’ the computer is called “HAL” with the hidden joke that
    each of those letters are one ahead of “IBM.”

Edit this code below to take the string “Ivnbojujft” and shift its
letters by one.

```{R}
IBM = utf8ToInt("IBM")
intToUtf8(IBM - 1)
```

Stop and think for a second: what is the term `- 1` doing above?

3.  The numbers for I, B, and M are 73, 66, and 77 respectively. But the
    Unicode space is much larger. Use the intToUTf8 function to find out
    what character is represented by the 128,512th character in Unicode.

```{R}
# 

```

Usually, you will load data that someone else has made. For example, the
code below uses a URL from the web to download the most common names in
Anchorage, Alaska.

Find a CSV or Excel file online and read it into R using `read_csv`.
Assign it to a variable, and then look at what happens when the variable
is printed back out. CSV reading will automatically *guess* at the types
of data you’ve imported–does it make the right choices? Why or why not?

```{R}
library(tidyverse)
read_csv("https://data.muni.org/api/views/a9a7-y93v/rows.csv?accessType=DOWNLOAD")
```
