Lab 8

Load the tidyverse and the stringr::words and stringr::fruit vectors. You won’t be able to use the data() function, you’ll have to assign stringr::words to a new object.

find matches

reminder: using str_view() will help you test and build your regular expressions.

1. Find words (from the words vector) that start with a vowel using str_subset(). You should have 175 words.

2. Find words (from the words vector) that end with at least 2 consecutive consonants using str_subset(). (Hint: thinking about matching “not”-vowels.). You should have 353 words.

3. Find words (from the words vector) that end with either “ing”, “ize” or “ise” using str_subset(). You should have 20 words.

replace

4. You decide berries cannot be singular and wish to replace every instance of “berry” with “berries” in the fruit vector.

5. replace all 5 letter words in the words vector with “five”

6. From the following emails, keep only the first part of the email. In other words, use regex to replace the “@something.net|com” with nothing ("").

emails <- c("ahmad@verizon.net", "kenja@sbcglobal.net", 
            "arandal@comcast.net", "seanq@me.com", 
            "vganesh@me.com", "jcholewa@msn.com", 
            "jeffcovey@aol.com", "seebs@me.com", 
            "camenisch@msn.com", "jmcnamara@yahoo.com", 
            "mcraigw@live.com", "conteb@live.com")

Your final result should be:

## ahmad kenja arandal seanq vganesh jcholewa jeffcovey seebs camenisch jmcnamara mcraigw conteb

combine

7. create the following tibble:

fruitibble <- tibble::tribble(
                       ~fruit,            ~origin,       ~scientific_name,
                 "Strawberry",           "frANCE",    "fragaria ananassa",
                  "Persimmon",            "China",       "Diospyros kaki",
                   "Honeydew",          "Algeria",         "Cucumis MELO",
                "Dragonfruit",  "Central America", "Selenicereus undatus",
                      "LEMON",            "india",         "citrus Limon",
                 "waterMelon",           "Africa",    "Citrullus lanatus",
                    "Avocado",           "Mexico",     "Persea americana",
                 "Blackberry",          "unknown",       "Rosaceae Rubus",
                     "Banana", "papua new guinea",       "Musa acuminata",
                  "Pineapple",           "Brazil",       "Ananas comosus"
                )

8. Use str_to_*() function to clean make clean capitalization on the fruitibble dataframe. Using tidyverse functions and glue, create a new column called about which includes something like “name (scientific name) is from origin”.

9. instead of creating a new column, use the glue_date() function to output only the about text into the chunk output. However, make sure your output is sorted by fruit name.