#### Data Scripting

The purpose of this assignment is to get you comfortable with writing clean and correct programs quickly for basic tasks. The tasks are chosen as the kind you would encounter if you are processing data sets in a data science setting; hence the name. We strongly encourage the use of higher-order functions (in moderation) to both reduce your burden and improve the conciseness and comprehensibility of your code.

For this homework, you are expected to do the work entirely on your own (without help from the course staff, whom you may only consult for help with names of library functions or other essential information of that sort). This is to make sure you are functioning at the level we expect at this point of the course.

Note that some of the problems use special values like 0 or -999 to delimit content. In general, you should not do this in your own programs: use properly structured data rather than embedding the shape in the data. However, sometimes you will confront real-world data sources that do this, and you may not have the freedom to change them. These problems give you a feel for working in such settings.

##### 1Examplar

There is no Examplar for BMI Sorter.

##### 2Palindrome Detection Modulo Spaces and Capitalization

A palindrome is a string with the same letters in each of forward and reverse order (ignoring capitalization). Design a program called is-palindrome that consumes a string and produces a boolean indicating whether the string with all spaces and punctuation removed is a palindrome. Treat all non-alphanumeric characters (i.e., ones that are not digits or letters) as punctuation. For this problem, we assume the set of alphanumeric characters is letters (a-z and A-Z) and digits (0-9).

Examples:
 is-palindrome("a man, a plan, a canal: Panama") is true is-palindrome("abca") is false is-palindrome("yes, he did it") is false is-palindrome("1221") is true is-palindrome("01001") is false

##### 3Sum Over Table

Assume that we represent tables of numbers as lists of rows, where each row is itself a list of numbers. The rows may have different lengths. Design a program sum-largest that consumes a table of numbers and produces the sum of the largest item from each row. Assume that no row is empty.

Example:
 sum-largest( [list: [list: 1, 7, 5, 3], [list: 20], [list: 6, 9]]) is (7 + 20 + 9)

Design a program called adding-machine that consumes a list of numbers and produces a list of the sums of each non-empty sublist separated by zeros. Ignore input elements that occur after the first occurrence of two consecutive zeros.

Example:
 adding-machine([list: 1, 2, 0, 7, 0, 5, 4, 1, 0, 0, 6]) is [list: 3, 7, 10]

##### 5The BMI Sorter

A personal health record (PHR) contains four pieces of information on a patient: their name, height (in meters), weight (in kilograms), and last recorded heart rate (as beats-per-minute). A doctor’s office maintains a list of the personal health records of all its patients.

 data PHR: | phr(name :: String, height :: Number, weight :: Number, heart-rate :: Number) end
You can assume that none of the numeric fields will be zero.

Body mass index (BMI) is a measure that attempts to quantify an individual’s tissue mass. It is commonly collected during annual checkups or clinic visits. It is defined as:
 BMI = weight / (height * height)
A simplified BMI scale classifies a value below 18.5 as “underweight”, a value at least 18.5 but under 25 as “healthy”, a value at least 25 but under 30 as “overweight”, and a value at least 30 as “obese”.

Design a function called bmi-report
 fun bmi-report(phrs :: List) -> Report
that consumes a list of personal health records (defined above) and produces a report containing a list of names (not the entire records) of patients in each BMI classification category. The names can be in any order. Use the following datatype for the report:

 data Report: | bmi-summary(under :: List, healthy :: List, over :: List, obese :: List) end

Example:

Given the following input list of PHRs:

 [list: phr("eugene", 2, 60, 77), phr("matty", 1.55, 58.17, 56 ), phr("ray", 1.8, 55, 84), phr("mike", 1.5, 100, 64)]

The output of bmi-report should be:

 bmi-summary( [list: "eugene", "ray"], # under [list: "matty"],         # healthy [list: ],                # over [list: "mike"]           # obese )
##### 6Data Smoothing

In data analysis, smoothing a data set means approximating it to capture important patterns in the data while eliding noise or other fine-scale structures and phenomena. One simple smoothing technique is to replace each (internal) element of a sequence of values with the average of that element and its predecessor and successor. Assuming that extreme outlier values are an abberation caused, perhaps, through poor measurement, this averaging process replaces them with a more plausible value in the context of that sequence.

For example, consider this sequence of heart-rate values taken from a list of personal health records (defined above):

 95 102 98 88 105

The resulting smoothed sequence should be

 95 295/3 96 97 105

where:
• 102 was substituted by 295/3: (95 + 102 + 98) / 3

• 98 was substituted by 96: (102 + 98 + 88) / 3

• 88 was substituted by 97: (98 + 88 + 105) / 3

This information can be plotted in a graph such as below, with the smoothed graph superimposed over the original values.

Design a function data-smooth
 fun data-smooth(phrs :: List) -> List
that consumes a list of PHRs and produces a list of the smoothed heart-rate values (not the entire records).

Example:

As given in the descriptive example above, assuming the initial sequence is instead a list of PHRs with the given values as the heart-rates.

##### 7Most Frequent Words

Given a list of strings, design a function frequent-words
 fun frequent-words(words :: List) -> List
that produces a list containing the three strings that occur most frequently in the input list. The output list should contain the most frequent word first, followed by the second most frequent, then the third most frequent. If two words have the same frequency, put the shorter one (in character length) first. You may assume that:
• the input will have at least three different words

• all characters are lowercase letters (there will be no numbers, punctuations, or white spaces)

• multiple words with the same frequency will have different lengths

Example:

 frequent-words( [list: "silver", "james", "james", "silver", "howlett", "silver", "loganne", "james", "loganne"]) is  [list: "james", "silver", "loganne"]
##### 8Earthquake Monitoring

Geologists want to monitor a local mountain for potential earthquake activity. They have installed a sensor to track seismic (vibration of the earth) activity. The sensor sends measurements one at a time over the network to a computer at a research lab. The sensor inserts markers among the measurements to indicate the date of the measurement. The sequence of values coming from the sensor looks as follows:

 20151004 150 200 175 20151005 0.002 0.03 20151007 130 0.54 20151101 78

The 8-digit numbers are dates (in year-month-day format). For example, the first number 20151004 above is October 4th, 2015.

Numbers in the range (0, 500] are vibration frequencies (in Hz). This example shows readings of 200, 150, and 175 on October 4th, 2015 and readings of 0.002 and 0.03 on October 5th, 2015. There are no data for October 6th (sometimes there are problems with the network, so data go missing).

Assume that the data are in order by dates (so a later date never appears before an earlier one in the sequence) and that all data are from the same year. Also, assume that every date that appears has at least one measurement.

Design a function daily-max-for-month
 fun daily-max-for-month(sensor-data :: List, month :: Number) -> List
that consumes a list of sensor data and a month (represented by a number between 1 and 12) and produces a list of reports indicating the highest frequency reading for each day in that month. Only include entries for dates that are part of the data provided (so don’t report anything for October 6th in the example shown). Ignore data for months other than the given one. Each entry in your report should be an instance of the following datatype:

 data Report: | max-hz(date :: Number, max-reading :: Number) end

Example:

Given the following input list (repeated from above):

 [list: 20151004, 150, 200, 175, 20151005, 0.002, 0.03, 20151007, 130, 0.54, 20151101, 78]

and the month 10 (for October), the result of daily-max-for-month should be

 [list: max-hz(20151004, 200), max-hz(20151005, 0.03), max-hz(20151007, 130)]
##### 9Submission Guidelines

Please create seven files in: palindrome.arr, sum.arr, adding.arr, bmi.arr, datasmooth.arr, frequentwords.arr, and earthquake.arr. Please put the text provide * at the top of each file, like in previous stencils. After you finish writing your programs, submit using this link.

For this assignment, you are not asked to turn in separate test suites and will not be graded on your testing.