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Computation Thinking

1. Computational thinking concepts like variables, iteration, filtering, and flowcharts were introduced. Variables represent unknown terms, iteration is repetition to generate outcomes, and filtering selects specific data. 2. Basic data types include Boolean, integer, character, and string, with defined ranges and operations. Subtypes further constrain ranges and operations. Data can be transformed, like converting dates to integers. 3. Lists are sequences of same or different data types, while records store data with named fields. Examples included subject marks lists and student data records.

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0% found this document useful (0 votes)
42 views4 pages

Computation Thinking

1. Computational thinking concepts like variables, iteration, filtering, and flowcharts were introduced. Variables represent unknown terms, iteration is repetition to generate outcomes, and filtering selects specific data. 2. Basic data types include Boolean, integer, character, and string, with defined ranges and operations. Subtypes further constrain ranges and operations. Data can be transformed, like converting dates to integers. 3. Lists are sequences of same or different data types, while records store data with named fields. Examples included subject marks lists and student data records.

Uploaded by

uday vivek
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© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Computational Thinking

A brief summary of Week 1

Variable: “A variable is a symbol which is used to represent a varying expression or quantity.”


OR
“A variable is a symbol used for representing an unspecified/unknown term.”

Example: 1. Counting number of cards present in the “Scores” dataset.


For that we created a variable called Count and initialized it to 0.
Then we add one to Count as we move a card from pile 1 to pile 2.
Count = 0 + 1 = 1

Iteration: “Repetition of a process”


OR
“Iteration is the repetition of a process in order to generate a sequence of outcomes”

Example: In the previous example we saw that every time we move cards from pile 1 to pile 2, we
add one to variable Count. This is nothing but an iteration.

Filtering: “Some specific decision”


OR
“In an iteration if we are only interested in specific item/data which are special to us and
not all items.”

Example: If we want to only count students from Chennai. In this case also we will move all cards
from pile 1 to pile 2 but we will add one to variable Count only when we find students from
Chennai.

Multiple filtering: For example if we want to find number of female students from Chennai.
Filters: (i) Checking gender: Male/Female
(ii) Checking City/Town
So, here total two filters are required to get the number of female students from Chennai.
Flowchart: “Pictorial representation of an algorithm”
OR
“A flowchart is a step-by-step diagrammatic representation using some defined shaped boxes to
solve a task.”

Rectangular box: Process or activity: Set of operations that change the value of data/variables

Arrow: Flowline: Shows the order of execution of the program steps

Diamond: Decision: Determines which path/direction the program will take (True/False)

Oval shaped box: Terminal: Indicates the start or end of the program.

Datatypes: (Lecture 1.7): “Defines the values that the variable can take, and the set of operations
that are permitted.”

Basic datatypes:

Boolean datatype: Range: Has only two values: True and False
Operation: AND, OR (Result type: Boolean) Result will be Boolean type
either True or False
Example:
If (X.Gender == ‘M’ AND X.City/Town == “Chennai”)

If (X.Gender == ‘M’ OR X.City/Town == “Chennai”)

Integer datatype: Range: ...., -3, -2, -1, 0, 1, 2, 3,.....


Operation: +, -, x, / (Result type: Integer)
<, >, == (Result type: Boolean)

Character datatype: Range: All alphanumeric: A, B,....Z, a, b,.....,z, 0, 1,.....,9


Special characters: ., $, #, @, .....
Operation: == (Result type: Boolean)
Example: ‘C’, ‘1’, ‘#’, ‘M’, ‘F’
*
String: Range: Any sequence of characters
Operation: == (Result type: Boolean)
Example: “IIT Madras”, “21F00055”, “can@1#23”

Subtype of basic datatypes: “Restrict the basic datatypes in terms of their ranges and constrained
on their operations”

Examples: Seq. No.: Ranges: 0, 1, 2, ..., Max (some reasonable number)


Operation: None of the integer operations make sense
: Boolean operations such as “==” can be performed
Marks: Ranges: 0, 1, ...., 100
Operation: Integer operation such as +, -

Transformation of sub-datatypes:
Date: 15 Jan : It is a string datatype.
Questions: What will be the date after 3 days?

We assume, 1 Jan : 0
2 Jan : 1
3 Jan : 2
--------
15 Jan : 14
-------
18 Jan: 17
-------
31 Dec : 364 (for non-leap year)

15 Jan Tranform 14
Integer operation

14 + 3

Print
18 Jan 17

Marks: Physics marks = 80.5


Mathematics marks = 90.5

We want to add the above two subject marks.

80.5 80.5x100 = 8050


90.5 90.5x100 = 9050

Then we performed integer operation, 8050 + 9050 = 17100


After that we need to bring back in original form by using “print” (defined in lecture)

print(17100) = 171.00
Lists and Records:

List: “A sequence of data elements of same or may be of different datatypes”


Example: (i) Subject marks obtained by Clarence: [63, 88, 73]

(ii) Details of Clarence: [9, “Clarence”, ‘M’, “6 Dec”, “Bengaluru”, 63, 88, 73, 224]

Record: “Stores data with multiple fields: each of which has a name and a value”
Example: A card of the Scores dataset.
{“Seq. No.”: 9, “Name”: “Clarence”, “DoB”: “6 Dec”, “Town/City”: “Bengaluru”,
“Mathematics”: 63, “Physics”: 88, “Chemistry”: 73, “Total”: 224}

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