T$1.$ For the following strings that each define a regular expression, explain why each will not match a $\backslash$: $\backslash ,\backslash \backslash ,\backslash \backslash \backslash$

T$2.$ What patterns will the regular expression $\backslash ..\backslash ..\backslash ..$ match? Give an example of a character string that would match.

T$3.$ Write a statement to convert all the backslashes in a string into forward slashes.

T$4.$ Create a regular expression that will match telephone numbers in the format $($###$)$ ###$-$#### $.$

T$5.$ Describe the equivalents of $?,+,$ and $*$ in $\{$m$,$ n$\}$ form.

T$6.$ Using the words vector from stringr, write regular expressions to find all the words that:

a$.$ Contain only consonants $($no vowels$)$

b$.$ Have three or more vowels in a row

c$.$ End with $-$ed$,$ but not $-$eed

d$.$ Contain a repeated pair of letters $($e$.$g$.,$church$$ contains $$ch$$ twice$)$

T$7.$ Using the sentences vector from stringr, extract:

a$.$ All the words ending in ing.

b$.$ All the pronouns.

R Script$-$

R$1.$ Here $($top of next page$)$ is a view of the top portion of alc$\_$abuse.txt$.$

a$.$ Import the data beginning in line $19$ of this file as a data frame.

b$.$ How many variables are recorded in the data in this file?

c$.$ How many observations of data are there?

d$.$ What percent of the participants in this data frame are married?

R$2.$ Using the starwars dataset:

a$.$ Write a statement using a str$\_*$ function that will count the number of characters with more than one hair color listed.

b$.$ Split hair$\_$color into two columns, one for each hair color listed $($the second column will be mostly missing$).$

Python Script$-$

P$1.$ Import all the table objects from scores.html as a list of data frames.

a$.$ How many tables are there?

b$.$ Pull out the first data frame from the imported list and call it scores.

c$.$ Look at the Series scores.columns. Notice that every column name begins with $$Sort by $.$ Replace $$Sort by $$ with $$ in every element of scores.columns to remove that part in each column name.

d$.$ Use a combination of a string method and the $.$sum$()$ method on the scores.Player series to find the number of players with a last name that starts with the letter $$R$.$

e$.$ Create a column containing each player$$s first name.