Exercises

1. What function would you use to read a file where fields were separated with “|”?

I would use read_delim() and include the argument delim = '|''.

2. Apart from file, skip, and comment, what other arguments do read_csv() and read_tsv() have in common?

col_names, col_types, col_select, id, locale, na, quoted_na, quote, comment, trim_ws, n_max, guess_max, progress, name_repair, num_threads, show_col_types, skip_empty_rows, lazy.

3. What are the most important arguments to read_fwf()?

file, fwf_cols, fwf_positions, fwf_widths, fwf_empty

4. Sometimes strings in a CSV file contain commas. To prevent them from causing problems, they need to be surrounded by a quoting character, like ” or ’. By default, read_csv() assumes that the quoting character will be “. To read the following text into a data frame, what argument to read_csv() do you need to specify?

quote = "''" to specify that we are using '' as quotes in a string.

5. Identify what is wrong with each of the following inline CSV files. What happens when you run the code?

read_csv("a,b\n1,2,3\n4,5,6") # Need to include a third column c

## Warning: One or more parsing issues, call `problems()` on your data frame for details,
## e.g.:
##   dat <- vroom(...)
##   problems(dat)

## Rows: 2 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (1): a
## num (1): b
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## # A tibble: 2 × 2
##       a     b
##   <dbl> <dbl>
## 1     1    23
## 2     4    56

read_csv("a,b,c\n1,2\n1,2,3,4") # Seems like they are missing a value in first row c, and there's an extra value in second row c. 

## Warning: One or more parsing issues, call `problems()` on your data frame for details,
## e.g.:
##   dat <- vroom(...)
##   problems(dat)

## Rows: 2 Columns: 3
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (2): a, b
## num (1): c
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## # A tibble: 2 × 3
##       a     b     c
##   <dbl> <dbl> <dbl>
## 1     1     2    NA
## 2     1     2    34

read_csv("a,b\n\"1") # 1 is in quotes, should there be two values? One for each column? 

## Rows: 0 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): a, b
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## # A tibble: 0 × 2
## # ℹ 2 variables: a <chr>, b <chr>

read_csv("a,b\n1,2\na,b") # second row has the same names as the column names, should they be numbers? 

## Rows: 2 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): a, b
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## # A tibble: 2 × 2
##   a     b    
##   <chr> <chr>
## 1 1     2    
## 2 a     b

read_csv("a;b\n1;3") # using ';' to delimit data. Either change it to read_csv2 or use commas ','

## Rows: 1 Columns: 1
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): a;b
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## # A tibble: 1 × 1
##   `a;b`
##   <chr>
## 1 1;3

6. Practice referring to non-syntactic names in the following data frame by:

   1. Extracting the variable called 1.
   2. Plotting a scatterplot of 1 vs. 2.
   3. Creating a new column called 3, which is 2 divided by 1.
   4. Renaming the columns to one, two, and three.

annoying <- tibble(
  `1` = 1:10,
  `2` = `1` * 2 + rnorm(length(`1`))
)

Here is my answer

clean <- annoying %>% 
  janitor::clean_names() %>% 
  rename(one = x1, two = x2) %>% # Rename columns
  mutate(three = one/two) # Create a third column 

clean_one <- clean %>% select(one) #Extract column one

# Scatterplot of columns one and two
ggplot(clean, 
       aes(x=one, y=two))+
  geom_point()+
  theme_classic()