8:09 PM Fri Sep 16Canvas Studentinstructure incINSTALLEDcanvas.colorado.eduPage of 21. the number of lines (from the signature we know this is just n)2. the number of blank lines (i.e. lines that contain nothing or only whitespace)3. the number of lines that are comments (i.e. lines that starts with "#")4. the total number of characters in the text filePLO 89%5. the median line length (ie. the median number of characters per line)6. the max line length (i.e. the max number of characters in a line)OPENcompute_text_file_numeric_summary(textFile: character (n)) - numeric (6): takes a text fileas its input and outputs a numeric of length 6 with the following characteristics of the text file:ZOOM +compute_text_file_vord_counts (textFile: character (n)) -data.frane (kx2): takes a textfile as its input and outputs a dataframe with k rows and 2 columns where k is the number ofdistinct "words". Here "words" include English word, variable names, function names, or any stringthat starts with a letter and contains only alpha-numerics, periods, and underscores. The first columnwill consist of the different words and the second columns will be the frequency with which the wordappears in the text file. The names of the columns should be Word and Count and it should be sortedby frequency in descending order. 8:09 PM Fri Sep 16Canvas StudentInstructure incINSTALLEDcanvas.colorado.eduPage of 289%OPENZOOM +Analyzing an .R FileYour task is to produce functions that can be used to summarize the actual code within an R script. We willwork up to the following line of code:compute_text_file_summary(read_text_file(textFilePath))We have broken this "monolith" task down into a few "brick" tasks below. However, you may considerbreaking these down even further.For the read_text_file() function you will need to use the base: :readLines () function, readLines ()takes in a string that is the file path (either a relative or global) to a text file (or R script) and returns acharacter vector where each element corresponds to its respective line of text (or code).Below is a list of functions for you to construct. For each, we have prescribed a very specific function signature.When we grade the assignment, we will check to ensure your functions have this signature. Be sure toincorporate type checks for inputs of your function as well. For instance, if a function's signature denotes avariable to be numeric and a character is passed instead, your function should throw an error with a helpfulmessage. See the lecture notes from 2022-09-02 for more on type checking and the function signature syntaxused below..Per usual, to grade your script, we will source() it and check its performance against a variety of unitstests. The official unit tests won't be revealed until after the assignment is graded. However, we haveprovided a smaller set of unit tests in the script, grade_hul practice. R, to give you an idea of what wewill be looking for. To use this script, you will need to download the folder. HviTextFiles practice,containing the example test files. Then, at the top of the script, assign testFilesFolderPath to whereverthe HviTextFiles practice folder is located and huScriptPath to wherever your hw1.R script is located.Running the rest of the script and reviewing the print out will tell you how your script performed against thepractice unit tests.Your TaskCreate an R script entilted hw1.R that contains the following functions:read_text_file(textFilePath: character (1), withBlanks: logical (1) TRUE, withComments:TRUE) - character (n): as its inputs, it takes in an argument textFilePath that islogical(1)a single character and two optional parameters withBlanks and withComments that are both singlelogicals; textFilePath is the path to the text file (or R script); if withBlanks and withCommentsare set to FALSE, then read_text_file() will return the text file without blank lines (i.e. lines thatcontain nothing or only whitespace) and commented (i.e. lines that starts with "#") lines respectively:it outputs a character vector of length n where each element corresponds to its respective line oftext/code.• compute_text_file_summary(textFile: character (n)) - 11st (2): takes in a text file (acharacter vector where each element is a line of text/code) as an input and returns a namedlist of length 2 as the output; the output lcist will contain the outputs of the below definedcompute_text_file_numeric_summary() and compute_text_file_word_counts() functions withnames NumericSummary and WordCounts respectively.

Question

8:09 PM Fri Sep 16Canvas Studentinstructure incINSTALLEDcanvas.colorado.eduPage <2> of 21. the number of lines (from the signature we know this is just n)2. the number of blank lines (i.e. lines that contain nothing or only whitespace)3. the number of lines that are comments (i.e. lines that starts with "#")4. the total number of characters in the text filePLO 89%5. the median line length (ie. the median number of characters per line)6. the max line length (i.e. the max number of characters in a line)OPENcompute_text_file_numeric_summary(textFile: character (n)) -> numeric (6): takes a text fileas its input and outputs a numeric of length 6 with the following characteristics of the text file:ZOOM +compute_text_file_vord_counts (textFile: character (n)) ->data.frane (kx2): takes a textfile as its input and outputs a dataframe with k rows and 2 columns where k is the number ofdistinct "words". Here "words" include English word, variable names, function names, or any stringthat starts with a letter and contains only alpha-numerics, periods, and underscores. The first columnwill consist of the different words and the second columns will be the frequency with which the wordappears in the text file. The names of the columns should be Word and Count and it should be sortedby frequency in descending order. 8:09 PM Fri Sep 16Canvas StudentInstructure incINSTALLEDcanvas.colorado.eduPage <1> of 289%OPENZOOM +Analyzing an .R FileYour task is to produce functions that can be used to summarize the actual code within an R script. We willwork up to the following line of code:compute_text_file_summary(read_text_file(textFilePath))We have broken this "monolith" task down into a few "brick" tasks below. However, you may considerbreaking these down even further.For the read_text_file() function you will need to use the base: :readLines () function, readLines ()takes in a string that is the file path (either a relative or global) to a text file (or R script) and returns acharacter vector where each element corresponds to its respective line of text (or code).Below is a list of functions for you to construct. For each, we have prescribed a very specific function signature.When we grade the assignment, we will check to ensure your functions have this signature. Be sure toincorporate type checks for inputs of your function as well. For instance, if a function's signature denotes avariable to be numeric and a character is passed instead, your function should throw an error with a helpfulmessage. See the lecture notes from 2022-09-02 for more on type checking and the function signature syntaxused below..Per usual, to grade your script, we will source() it and check its performance against a variety of unitstests. The official unit tests won't be revealed until after the assignment is graded. However, we haveprovided a smaller set of unit tests in the script, grade_hul practice. R, to give you an idea of what wewill be looking for. To use this script, you will need to download the folder. HviTextFiles practice,containing the example test files. Then, at the top of the script, assign testFilesFolderPath to whereverthe HviTextFiles practice folder is located and huScriptPath to wherever your hw1.R script is located.Running the rest of the script and reviewing the print out will tell you how your script performed against thepractice unit tests.Your TaskCreate an R script entilted hw1.R that contains the following functions:read_text_file(textFilePath: character (1), withBlanks: logical (1) TRUE, withComments:TRUE) -> character (n): as its inputs, it takes in an argument textFilePath that islogical(1)a single character and two optional parameters withBlanks and withComments that are both singlelogicals; textFilePath is the path to the text file (or R script); if withBlanks and withCommentsare set to FALSE, then read_text_file() will return the text file without blank lines (i.e. lines thatcontain nothing or only whitespace) and commented (i.e. lines that starts with "#") lines respectively:it outputs a character vector of length n where each element corresponds to its respective line oftext/code.• compute_text_file_summary(textFile: character (n)) -> 11st (2): takes in a text file (acharacter vector where each element is a line of text/code) as an input and returns a namedlist of length 2 as the output; the output lcist will contain the outputs of the below definedcompute_text_file_numeric_summary() and compute_text_file_word_counts() functions withnames NumericSummary and WordCounts respectively.

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