data handling assignment

• Math Article

Data Handling

In Statistics, “Data Handling” is an important concept that ensures the integrity of the research data, as it addresses some important concerns such as security, confidentiality, and the preservation of the research data. In every field, we have information in the form of a numerical figure. Every figure of this kind is known as an observation. Generally, the collection of all the observation is called data. To handle the data, Statisticians use different data management methods. In this article, let us discuss what data handling is, and the various methods to handle the data.

Table of Contents:

• Data Handling Definition
• Types of Data
• How to Represent Data
• Data Representation Using Bar Graph

What is Data Handling?

Data handling means collecting the set of data and presenting in a different form. Data is a collection of numerical figures that represents a particular kind of information. The collection of observations which are gathered initially is called the raw data. Data can be in any form. It may be words, numbers, measurements, descriptions or observations. Data handling is the process of securing the research data is gathered, archived or disposed of in a protected and safe way during and after the completion of the analysis process.

For More Information On Data Handling, Watch The Below Video:

Types of data

Data handling methods can be performed based on the types of data. The data is classified into two types, such as:

• Qualitative Data
• Quantitative Data

Qualitative data gives descriptive information of something whereas quantitative data gives numerical information about something. Here, the quantitative data is further divided into two. They are discrete data and continuous data. The discrete data can take only certain values such as whole numbers. The continuous data can take a value within the provided range.

Data Handling Steps

The steps involved in the data handling process are as follows:

Step 1: Problem Identification

In the data handing process, the purpose or problem statement has to be identified and well defined.

Step 2: Data Collection

The data relevant to the problem statement is collected.

Step 3: Data Presentation

The collected data should be presented in a meaningful manner and it should be easily understood. It can be done by arranging the collected data in the tally marks, table forms, and so on.

Step 4: Graphical Representation

Since the visual or graphical representation of the data makes the analysis and understanding easier, the presented data can be plotted in graphs, charts such as bar graphs, pie charts and so on.

Step 5: Data Analysis

The data should undergo data analysis so that the necessary information can be concluded from the data, which helps in taking further actions.

Step 6: Conclusion

From the analysis of the data, we can derive the solution to our problem statement.

How to Represent Data?

The data can be usually represented in any one of the following ways. They are:

• Line Graphs
• Pictographs
• Stem and Leaf Plot
• Frequency Distribution
• Cumulative Tables and Graphs

Now, we will have a look at one of the methods to represent the data using “Bar Graph”.

Representation of Data Using Bar Graph

Data can be represented in various forms through numbers, pictures, tables, graphics, etc. The most common type of graphical representation of data is through bar graphs . A bar graph or bar chart portrays a visual interpretation of data with the help of vertical or horizontal rectangular bars of equal width which are uniformly spaced with respect to each other, where the lengths of the bars are proportional to the data to be represented. Let us consider the following example to understand bar graph more closely:

In a school of 406 students, the percentage of attendance of students is represented by the following table. We’ll represent it through a bar graph.

Each bar in the above example is of uniform width and the data which varies is represented on one of the axes. Another axis represents the measure of the variable data through the height of the bars. The heights or the lengths of the bars denote the value of the variable. These graphs are also used to compare certain quantities.

In this example, the attendance of the students is represented by the X-axis and the number of students on the Y-axis. The bars are of uniform width and the length of the bar is equal to the number of students. By observing the bar graph it can be concluded that the number of students with 60% attendance is 105, the number of students with 70% attendance is 199, the number of students with 80% attendance is 29 and the number of students with 90% attendance is 73. Thus, close observation of the bar chart makes the data representation simple and easy and therefore bar graph makes data organized, its analysis and interpretation simple.

Frequently Asked Questions on Data Handling

What is data handling.

Data handling is the process of collecting, organizing and presenting the data in such a way that is helpful to analyse and make the conclusion.

What are the two different types of data?

The two different types of data are qualitative data and quantitative data.

Mention the different types of graphical representation?

The different types of graphical representation are: Bar graph Line graph Pie chart Pictograph Scatter plot Stem and leaf plot

What are the steps involved in data handling?

The steps involved in the data handling process are: Problem identification Data collection Data presentation Graphical representation Data analysis Conclusion

What is a pictograph?

Pictograph is one of the graphical representations of data, where the information is represented in the form of symbols, icons, pictures and so on. It is one of the simplest forms of data representation in data handling.

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• What are Rational Numbers?
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Data handling.

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Chapter 6: Squares and Square Roots

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Chapter 7: Cubes and Cube Roots

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Chapter 8: Comparing Quantities

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Chapter 9: Algebraic Expressions and Identities

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Chapter 10: Visualising Solid Shapes

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Chapter 11: Mensuration

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Nowadays, managing and representing data systematically has become very important especially when the data provided is large and complex, This is when Data Handling comes into the picture. The definition of Data handling is in the title itself, that is, Handling the data in such a way that it becomes easier for people to understand and comprehend the given information. Hence, The process of collecting, Recording , and representing data in some form of graph or chart to make it easy for people to understand is called Data handling.

Statistics is another term for data handling, and it is useful not only in the field of Math and Science but also in the fields where the representation of data is required. Let’s learn about some forms of Data handling, and how they work.

Pictographs

A pictograph is the pictorial representation of any data given to us in written form. It can be said that pictograph used to be the earliest form of conversation, since way back in time, people have communicated mostly through pictures with each other since the languages were not present.

Indeed, Pictograph plays a role in our day-to-day life too. For instance, when a friend tells us a story, we start imagining the story in our head and that makes it both easy to understand and easy to remember for a long time for us.

Drawing a Pictograph

Let’s learn to draw the pictograph with the help of an example,

Example: In a reading competition, there were three students participating- Rahul, Saumya, Ankush. They were supposed to read as many books as they can in an hour. Rahul read 3 books, Saumya read 2 books and Ankush read 4 books. Draw the pictograph for the information.

There are some basic steps to draw a Pictograph: Decide the particular picture/pictures that is required to represent data, make sure that the picture is a little related in order to memorize information easily. Here, to successfully read a book, a smiley is denoted. Now, draw the pictures according to information presented, for example, there will be 3 smilies for Rahul as he completed 3 books in an hour.

Sample Questions on Pictograph

Question 1: In a Theater, there are 3 Plays with different amounts of actors participating in each play. In play 1, there are 9 actors, in play 2, there are 3 lesser actors, and the number of actors in play 3 is one lesser than play 1. Draw the Pictograph for the information given and analyze in which play, the stage will be most crowded.

From the information given in the question, we can say that play 1 has 9 actors, play 2 has 6 actors and play 3 has 10 actors  Representing actors in the pictorial form as, Therefore, we can conclude that Play 3 has the stage most crowded as it has 10 actors acting on stage.

Question 2: In a Weather Report conducted for 5 weeks continuously, it was noted that not all days are sunny days in the season of spring. The observation said that week 1 had 4 sunny days, week 2 had 5 sunny days, week 3 had only 2 sunny days, week 4 had sunny days in the entire week, and week 5 had only 3 sunny days.

Draw a Pictograph for the information given above.

Representing sunny days in pictorial form for better understanding,

The graphical representation of any quantity, number or data in the form of bars is called a bar graph. With the help of Bar Graph, not only the data look neat and understanding but also it is easier to compare the data given.

Types of Bar Graph

Vertical bar graph, horizontal bar graph.

These are the most common bar graph we come across, the bars of grouped data in vertical bar graphs lie vertically. Sometimes when the data categorized have long names, then Horizontal bar graphs are preferred since, in vertical bar graphs, there is not much space on the x-axis.

Question: There are 800 students in a school and the table for their birthdays in all 12 months is given below, Draw the Vertical Bar graph and answer,

• Maximum number of students have their birthdays in which month?
• Which two months have equal number of birthday?
• The minimum number of birthdays occur in which month?

The vertical bar graph for the table given in the question will be, From the Bar graph we can figure out the answer of the questions August is that month in which maximum birthdays are happening, since the bar above august is the longest(there are 110 students whose birthday come in August) From the graph, we can tell that January and April have equal lengths of bars, That means they have the same number of birthdays (both have 50 birthdays) The minimum number of birthdays occur in December since it has the smallest bar.(20 students have their birthdays in December.

The graphs that have their rectangular bars lying horizontally, which means that the frequency of the data lie on the x-axis while the categories of the data lie on the y-axis are known as Horizontal bar graphs.

Horizontal bar graphs are preferred when the name of the categories of data are long and the minimum space on the x-axis is not sufficient.

Question: In an examination, Reeta performed in 5 subjects, her performance is given in the table below. Draw a Horizontal Bar graph showing the marks she obtained in all the subjects, Also, calculate the overall Percentage obtained by her.

The Horizontal bar graph for the table mentioned in the question, The overall Percentage obtained by Reeta =  ×100 = 79 percent.

Double- Bar Graph

Double-bar graphs are used when two groups of data are required to be represented on a single graph. In a double-bar graph, to represent two groups of data, they are represented beside each other at different heights depending upon their values.

Advantages of double-bar graph:

• A double-bar graph is helpful when multiple data are required to be represented.
• It helps in summarizing large and big data in an easy and visual form.
• It shows and covers all different frequency distribution.

Question 1: The table for the number of boys and girls for classes 6, 7, 8, 9, and 10 is shown below. Represent the data on a Double-bar graph.

The double-bar graph for the table given the question,

Question 2: In a survey done for a week from Monday to Sunday, for two cities Agra and Delhi, The temperatures of both the cities are measured and the temperatures obtained are as following,

Draw the Bar Graph for the given table in the question.

The Given table has two categories of data, one is the temperature for Agra and the other is the temperature for Delhi, Therefore, the graph can be drawn in one as a double- Bar graph, the graph shall look like,

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Data Handling

Class 11 - computer science with python sumita arora, multiple choice questions.

Which of the following are valid Python data types ?

• dictionary ✓

Which of the following are datatypes considered as Numbers in Python.

• floating point ✓

Consider the following sequence of statements: a = 35 m = a Following the execution of these statements, Python has created how many objects and how many references ?

• Two integer objects, two references
• One integer object, two references ✓
• One integer object, one reference
• Two integer objects, one reference

Which Python built-in function returns the unique number assigned to an object?

• identity( )

The operator used to check if both the operands reference the same object memory, is the .......... operator.

For two objects x and y, the expression x is y will yield True, if and only if

• id(x) == id(y) ✓
• len(x) == len(y)
• all of these

Which of the following is not an immutable type in Python ?

Python operator always yields the result of .......... datatype.

What is the value of the expression 100 / 25 ?

• none of these

Question 10

What is the value of the expression 100 // 25 ?

Question 11

In Python, a variable must be declared before it is assigned a value.

• Only in Functions
• Only in modules

Question 12

In Python, a variable is assigned a value of one type, and then later assigned a value of a different type. This will yield .......... .

Question 13

In Python, a variable may be assigned a value of one type, and then later assigned a value of a different type. This concept is known as .......... .

• static typing
• dynamic typing ✓
• immutability

Question 14

Is it safe to directly use the == operator to determine whether objects of type float are equal ?

• Yes, if the values are < 100
• Yes, if the values are > 100

Question 15

What will the following code produce ?

• compilation error

Question 16

In the Python statement x = a + 5 - b : a and b are .......... .

Question 17

In the Python statement x =a + 5 - b : a + 5 - b is .......... .

• Expression ✓

Question 18

What will be the value of y after following code fragment is executed ?

Question 19

Which of the following literals has True truth-value ?

Question 20

What will the following code result as ?

Question 21

Which of the following operators has the lowest precedence ?

Question 22

What is the value of the expression 10 + 3 ** 3 * 2?

Question 23

To increase the value of x five times using an augmented assignment operator, the correct expression will be

Question 24

What will be the result of the expression 10 or 0 ?

Question 25

What will be the result of the expression 5 or 10 ?

Question 26

What will be the result of the expression 5 and 10?

Question 27

What will be the result of the expression 15 and 10?

Question 28

Question 29.

What will be the result of the expression 'a' or " (" is an empty string) ?

Question 30

What will be the result of the expression 'a' and " (" is an empty string) ?

Question 31

What will be the result of the expression 'x' and 'a' ?

Question 32

What will be the result of the expression 'a' and 'x' ?

Question 33

What will be the result of the expression 'a' and 'None' ?

Question 34

What will be the result of the expression 'None' and 'a' ?

Question 35

What will be the result of the expression 'false' and False ?

Question 36

What will be the result of the expression 'false' or False ?

Fill in the Blanks

Boolean data type is internally treated as integer data type.

Two forms of floating-point numbers are: fractional form and exponent notation.

Python's floating point numbers have precision of 15 digits.

Three mutable types of Python are lists , dictionaries and sets .

The floor division of two integers yields a result of integer type.

The division of two integers yields a result of floating-point type.

The set sequence type cannot store duplicate values.

The tuple datatype is like lists but is not mutable.

The id of an object gives the memory location of the object.

To check if two objects reference the same memory address, is operator is used.

To use function fabs( ), math module should be imported.

To generate a random floating number in the range 0 to 100, random() or random.random() function is used.

To generate a random integer in a range, randint() or random.randint() function is used.

To generate a random number in a sequence of values where two values have a difference a step value, randrange() or random.randrange() function is used.

To use mean() function, statistics module is to be imported.

True/False Questions

List is an immutable data type. False

Set is a mutable data type. True

A set can contain duplicate values in it. False

A Boolean value is internally treated as an integer value. True

'' (an empty string) has truth value as False. True

' ' (a space) has truth value as False. False

Value false is a legal literal value in Python. False

Value False is a legal literal value in Python. True

Value 'False' is a legal literal value in Python. True

Value 'false' is a legal literal value in Python. True

None and 'None' are the same. False

None has the truth value as False. True

'None' has the truth value as False. False

The result of bool(0) is False. True

The result of bool('None') is False. False

Dividing two integers results in an integer. False

Floor division of two integers results in an integer. True

Two floating point numbers should not be compared for equality using == True

In implicit conversion, all operands' data types are converted to the datatype of the largest operand. True

Explicit type conversion involves the use of a function to convert datatype of a value. True

Type A: Short Answer Questions/Conceptual Questions

What are data types in Python? How are they important?

Data types are used to identify the type of data a memory location can hold and the associated operations of handling it. The data that we deal with in our programs can be of many types like character, integer, real number, string, boolean, etc. hence programming languages including Python provide ways and facilities to handle all these different types of data through data types. The data types define the capabilities to handle a specific type of data such as memory space it allocates to hold a certain type of data and the range of values supported for a given data type, etc.

How many integer types are supported by Python? Name them.

Two integer types are supported by Python. They are:

• Integers (signed)

How are these numbers different from one another (with respect to Python)? 33, 33.0, 33j, 33 + j

The number 33 is an integer whereas 33.0 is a floating-point number. 33j represent the imaginary part of a complex number. 33 + j is a complex number.

The complex numbers have two parts : real and imaginary. In which data type are real and imaginary parts represented ?

In Python, the real and imaginary parts of a complex number are represented as floating-point numbers.

How many string types does Python support? How are they different from one another?

Python supports two types of strings — Single-line strings and Multi-line strings. Single line strings are enclosed in single or double quotes and terminate in one line. Multi-line strings store multiple lines of text and are enclosed in triple quotes.

What will following code print?

This code will print:

len(str1) is 6 due to the EOL character. len(str2) is 5 as backslash (\) character is not counted in the length of string. As len(str1) is greater than len(str2) so the output is True.

What are Immutable and Mutable types in Python? List immutable and mutable types of Python.

Mutable types are those whose values can be changed in place whereas Immutable types are those that can never change their value in place.

Mutable types in Python are:

• Dictionaries

Immutable types in Python are:

• Floating-Point numbers

What are three internal key-attributes of a value-variable in Python ? Explain with example.

The three internal key-attributes of a value-variable in Python are:

For example, consider this:

The type of a is int which can be found with the built-in function type() like this: type(a).

Value can be found using the built-in function print() like this: print(a)

It will give the output as 4 which is value contained in variable a.

Id is the memory location of the object which can be determined using built-in function id() like this: id(a)

Is it true that if two objects return True for is operator, they will also return True for == operator?

Yes, if is operator returns true, it implicitly means that the equality operator will also return True. is operator returning true implies that both the variables point to the same object and hence == operator must return True.

Are these values equal? Why/why not?

• 20 and 20.0
• 20 and int(20)
• str(20) and str(20.0)
• 'a' and "a"
• The type of 20 is int whereas the type of 20.0 is float so they are two different objects. Both have the same value of 20. So, as values are same equality (==) operator return True but as objects are different is operator returns False.
• The value and type of both 20 and int(20) are the same and both point to the same object so both equality (==) and is operator returns True.
• For str(20) and str(20.0), both equality (==) and is operator returns False as their values are different and they point to two different objects.
• For 'a' and "a", both equality (==) and is operator returns True as their values are same and they point to the same object.

What is an atom in Python? What is an expression?

In Python, an atom is something that has a value. Identifiers, literals, strings, lists, tuples, sets, dictionaries, etc. are all atoms. An expression in Python, is any valid combination of operators and atoms. It is composed of one or more operations.

What is the difference between implicit type conversion and explicit type conversion?

Two objects (say a and b) when compared using == ,return True. But Python gives False when compared using is operator. Why? (i.e., a == b is True but why is a is b False?)

As equality (==) operator returns True, it means that a and b have the same value but as is operator returns False, it means that variables a and b point to different objects in memory. For example, consider the below Python statements:

Here, both a and b have the same value 'abc' but they point to different objects.

Given str1 = "Hello", what will be the values of:

(a) str1[0]

(b) str1[1]

(c) str1[-5]

(d) str1[-4]

(e) str1[5]

(e) IndexError: string index out of range

Explanation

H 0 − 5 e 1 − 4 l 2 − 3 l 3 − 2 o 4 − 1 \begin{matrix} \underset{-5}{\overset{0}{\bold{H}}} & \underset{-4}{\overset{1}{\bold{e}}} & \underset{-3}{\overset{2}{\bold{l}}} & \underset{-2}{\overset{3}{\bold{l}}} & \underset{-1}{\overset{4}{\bold{o}}} \end{matrix} − 5 H 0 ​ ​ − 4 e 1 ​ ​ − 3 l 2 ​ ​ − 2 l 3 ​ ​ − 1 o 4 ​ ​

If you give the following for str1 = "Hello", why does Python report error?

str1[2] = 'p'

Python reports error because strings are immutable and hence item assignment is not supported.

What will the result given by the following?

(a) type (6 + 3)

(b) type (6 -3)

(c) type (6 *3)

(d) type (6 / 3)

(e) type (6 // 3)

(f) type (6 % 3)

(a) type (6 + 3) ⇒ int + int ⇒ int So the result is int.

(b) type (6 -3) ⇒ int - int ⇒ int So the result is int.

(c) type (6 * 3) ⇒ int * int ⇒ int So the result is int.

(d) type (6 / 3) ⇒ int / int ⇒ float So the result is float.

(e) type (6 // 3) ⇒ int // int ⇒ int So the result is int.

(f) type (6 % 3) ⇒ int % int ⇒ int So the result is int.

What are augmented assignment operators? How are they useful?

Augmented assignment operators combine the impact of an arithmetic operator with an assignment operator. For example, to add the value of b to the value of a and assign the result back to a then instead of writing:

we can write

Augmented assignment operators are useful as they provide a shorthand way by combining the arithmetic and assignment operators.

Differentiate between (555/222)**2 and (555.0/222)**2.

In the first expression, 555 is of int type whereas in the second expression 555.0 is of float type.

Given three Boolean variables a, b, c as : a = False, b = True, c = False. Evaluate the following Boolean expressions:

(a) b and c

(c) not a and b

(d) (a and b) or not c

(e) not b and not (a or c)

(f) not ((not b or not a) and c) or a

(a) b and c      ⇒ False and True      ⇒ False

(b) b or c      ⇒ True or False      ⇒ True

(c) not a and b      ⇒ not False and True      ⇒ True and True      ⇒ True

(d) (a and b) or not c      ⇒ (False and True) or not False      ⇒ False or not False      ⇒ False or True      ⇒ True

(e) not b and not (a or c)      ⇒ not True and not (False or False)      ⇒ not True and not False      ⇒ False and True      ⇒ False

(f) not ((not b or not a) and c) or a      ⇒ not ((not True or not False) and False) or False      ⇒ not ((False or True) and False) or False      ⇒ not (True and False) or False      ⇒ not False or False      ⇒ True or False      ⇒ True

What would following code fragments result in? Given x = 3.

(a) 1 < x

(d) x == 3.0

(e) "Hello" == "Hello"

(f) "Hello" > "hello"

(g) 4/2 == 2.0

(h) 4/2 == 2

(i) x < 7 and 4 > 5.

Write following expressions in Python:

(a) 1 3 b 2 h \dfrac{1}{3} b^2 h 3 1 ​ b 2 h

(b) π r 2 h \pi r^2 h π r 2 h

(c) 1 3 π r 2 h \dfrac{1}{3} \pi r^2 h 3 1 ​ π r 2 h

(d) ( x 2 − x 1 ) 2 + ( y 2 − y 1 ) 2 \sqrt{(x2 - x1)^2 + (y2 - y1)^2} ( x 2 − x 1 ) 2 + ( y 2 − y 1 ) 2 ​

(e) ( x − h ) 2 + ( y − k ) 2 = r 2 (x - h)^2 + (y - k)^2 = r^2 ( x − h ) 2 + ( y − k ) 2 = r 2

(f) x = − b + b 2 − 4 a c 2 a x = \dfrac{-b + \sqrt{b^2 - 4ac}}{2a} x = 2 a − b + b 2 − 4 a c ​ ​

(g) a n × a m = a n + m a^n \times a^m = a^{n+m} a n × a m = a n + m

(h) ( a n ) m = a n m (a^n)^m = a^{nm} ( a n ) m = a nm

(i) a n a m = a n − m \dfrac{a^n}{a^m} = a^{n - m} a m a n ​ = a n − m

(j) a − n = 1 a n a^{-n} = \dfrac{1}{a^n} a − n = a n 1 ​

int('a') produces error. Why ?

int() converts its argument into an integer. As 'a' is a letter, it cannot be converted into a valid integer hence int('a') produces an error.

int('a') produces error but following expression having int('a') in it, does not return error. Why?

len('a') + 2 or int('a')

The or operator tests the second operand only if the first operand is false otherwise it ignores it. In the expression, the first operand of or operator is len('a') + 2. It evaluates to 3 and as it is a non-zero value hence it is True for or operator. As first operand of or operator is True so it doesn't evaluate its second argument int('a') and no error is returned.

Write expression to convert the values 17, len('ab') to (i) integer (ii) str (iii) boolean values

(i) int(17), int(len('ab'))

(ii) str(17), str(len('ab'))

(iii) bool(17), bool(len('ab'))

Evaluate and Justify:

(i) 22 / 17 = 37 / 47 + 88 /83

(ii) len('375')**2

(i) It produces an error as LHS value in this case is an expression that evaluates to a literal whereas LHS value should be a variable.

(ii) len('375')**2  ⇒ 3 ** 2    [∵ len('375') = 3]  ⇒ 9           [∵ 3 * 3 = 9]

(i) 22.0/7.0 - 22/7

(ii) 22.0/7.0 - int(22.0/7.0)

(iii) 22/7 - int (22.0)/7

(i) 22.0/7.0 - 22/7  ⇒ 0

As values of 22.0/7.0 and 22/7 are equal, subtracting them will give the result as 0.0.

(ii) 22.0/7.0 - int(22.0/7.0)  ⇒ 3.142857142857143 - 3  ⇒ 0.142857142857143

(iii) 22/7 - int (22.0)/7  ⇒ 0.0

int (22.0) gives 22 so the expression becomes 22/7 - 22/7 which results in 0.0

(i) false and None

(ii) 0 and None

(iii) True and None

(iv) None and None

(i) This produces an error as false is an invalid literal in Python. It should be False. Had the expression being False and None, the return value will be False.

(ii) This logical expression evaluates to 0. As first operand of and operator is false so it will return the first operand itself.

(iii) This logical expression evaluates to None. As first operand of and operator is True so it will return the second operand.

(iv) This logical expression evaluates to None. As first operand of and operator is false so it will return the first operand itself.

(a) 0 or None and "or"

(b) 1 or None and 'a' or 'b'

(c) False and 23

(d) 23 and False

(e) not (1 == 1 and 0 != 1)

(f) "abc" == "Abc" and not (2 == 3 or 3 == 4)

(g) False and 1 == 1 or not True or 1 == 1 and False or 0 == 0

(a) 0 or None and "or"  ⇒ 0 or None   [∵ and has higher precedence than or]  ⇒ None

(b) 1 or None and 'a' or 'b'  ⇒ 1 or None or 'b'  ⇒ 1 or 'b'  ⇒ 1

(c) False and 23  ⇒ False

(d) 23 and False  ⇒ False

(e) not (1 == 1 and 0 != 1)  ⇒ not (True and True)  ⇒ not True  ⇒ False

(f) "abc" == "Abc" and not (2 == 3 or 3 == 4)  ⇒ "abc" == "Abc" and not (False or False)  ⇒ "abc" == "Abc" and not False  ⇒ False and not False  ⇒ False and True  ⇒ False

(g) False and 1 == 1 or not True or 1 == 1 and False or 0 == 0  ⇒ False and True or not True or True and False or True  ⇒ False and True or False or True and False or True  ⇒ False or False or False or True  ⇒ False or False or True  ⇒ False or True  ⇒ True

Evaluate the following for each expression that is successfully evaluated, determine its value and type for unsuccessful expression, state the reason.

(a) len("hello") == 25/5 or 20/10

(b) 3 < 5 or 50/(5 - (3 + 2))

(c) 50/(5 - (3 + 2)) or 3 < 5

(d) 2 * (2 * (len("01")))

(a) len("hello") == 25/5 or 20/10  ⇒ 5 == 25/5 or 20/10  ⇒ 5 == 5 or 2  ⇒ True or 2  ⇒ True

The type of result is Boolean.

(b) 3 < 5 or 50/(5 - (3 + 2))  ⇒ True or 50/(5 - (3 + 2))   [∵ first operand is True, second operand is not evaluated so no division by 0 error happens]  ⇒ True

(c) 50/(5 - (3 + 2)) or 3 < 5  ⇒ 50/(5 - 5) or 3 < 5  ⇒ 50/0 or 3 < 5  ⇒ Division by Zero Error

As the denominator of or operator's first operand is 0, Division by Zero error occurs.

(d) 2 * (2 * (len("01")))  ⇒ 2 * (2 * 2)  ⇒ 2 * 4  ⇒ 8

The type of result is Integer.

Write an expression that uses exactly 3 arithmetic operators with integer literals and produces result as 99.

Add parentheses to the following expression to make the order of evaluation more clear.

y % 4 == 0 and y % 100 != 0 or y % 400 == 0

((y % 4) == 0) and ((y % 100) != 0) or ((y % 400) == 0)

A program runs to completion but gives an incorrect result. What type of error would have caused it?

Logical errors can make a program run till completion but give incorrect result.

In Python, strings are immutable while lists are mutable. What is the difference?

In Python, strings are immutable means that individual letter assignment for strings is not allowed. For example:

The above Python code will cause an error as we are trying to assign some value to an individual letter of a string.

Lists are mutable in Python means that we can assign values to individual elements of a list. For example:

The above Python code will work correctly without any errors as Lists are mutable in Python.

How does the // operator differ from the / operator? Give an example of where // would be needed.

The Division operator (/) divides its first operand by second operand and always returns the result as a float value whereas Floor Division operator (//) divides its first operand by second operand and truncates the fractional part of the result and returns it as an int value. Floor Division operator is useful in situations where we only need the integer part of the division operation result. For example, to determine how many minutes are there in some given number of seconds:

MidAir Airlines will only allow carry-on bags that are no more than 22 inches long, 14 inches wide, and 9 inches deep. Assuming that variables named length, width, and depth have already been assigned values, write an expression combining the three that evaluates to True if bag fits within those limits, and False otherwise.

length <= 22 and width <= 14 and depth <= 9

What are main error types? Which types are most dangerous and why?

The types of errors are:

• Compile Time Errors (Syntax errors and Semantic Errors)
• Runtime Errors
• Logical Errors

Logical Errors are the most dangerous as they are hardest to prevent, find and fix.

Question 37

Correct any false statements:

(a) Compile-time errors are usually easier to detect and to correct than run-time errors.

(b) Logically errors can usually be detected by the compiler.

(a) The statement is correct.

(b) The statement is incorrect. The correct statement should be:

Logical errors cannot be detected by the compiler.

Question 38

Differentiate between a syntax error and a semantics error.

Question 39

Differentiate between a syntax error and a logical error in a python program. When is each type of error likely to be found?

Syntax errors are found at compile type whereas Logical errors are found when the program starts executing.

Question 40

What is the difference between an error and exception?

An Error is a bug in the code that causes irregular output or stops the program from executing whereas an Exception is an irregular unexpected situation occurring during execution on which programmer has no control.

Type B: Application Based Questions

What is the result produced by (i) bool (0) (ii) bool (str(0))? Justify the outcome.

(i) bool (0)

The result is False as truth value of 0 is false tval

(ii) bool (str(0))

The result is True as str(0) converts 0 to string "0". As it becomes a non-empty string so its truth value is true tval

What will be the output, if input for both the statements is 5 + 4/2.

6 == input ("Value 1:") 6 == int(input ("value 2:"))

Output of first statement is False as '5 + 4/2' is entered as a string so it cannot be equal to the number 6.

The second statement gives an error as int() function cannot convert the string '5 + 4/2' to a valid integer.

Following Python code has an expression with all integer values. Why is the result in floating point form?

The output of the above Python code is 8.0. Division operator is present in the expression. The result of Division operator is of float type. Due to implicit conversion, other operand in this expression are also converted to float type and hence the final result is in floating point form.

Question 4a

This Python code prints:

Question 4b

As values of a and b are equal so equality operator returns True. a is of int type and b is of float type so a and b are different objects so a is b returns False.

Question 5a

What will be output produced by following code? State reason for this output.

Value of d becomes 2 and as values of c and d are equal so print(c == d) prints True.

Question 5b

    a = 5 - 4 - 3 ⇒ a = 1 - 3 ⇒ a = -2

The exponentiation operator (**) has associativity from right to left so:

    b = 3**2**3 ⇒ b = 3**8 ⇒ b = 6561

Question 5c

    e = a+b+c-d ⇒ e = 1+1+1-0.3 ⇒ e = 3-0.3 ⇒ e = 2.7

As 0.3 is float so implicit conversion converts 3 also to float and result of the expression is of float type.

    f = a + b + c == d ⇒ f = 1 + 1 + 1 == 0.3 ⇒ f = 3 == 0.3 ⇒ f = False

Question 6a

What will be the output of following Python code?

    a -= b ⇒ a = a - b ⇒ a = 12 - 7.4 ⇒ a = 4.6

    a *= 2 + c ⇒ a = 4.6 * (2 + c) ⇒ a = 4.6 * (2 + 1) ⇒ a = 4.6 * 3 ⇒ a = 13.799999999999999

    b += a * c ⇒ b = b + (a * c) ⇒ b = 7.4 + (13.799999999999999 * 1) ⇒ b = 7.4 + 13.799999999999999 ⇒ b = 21.2

Question 6b

    z = x/y*y ⇒ z = 4/8*8 ⇒ z = 0.5*8 ⇒ z = 4.0

Make change in the expression for z of previous question so that the output produced is zero. You cannot change the operators and order of variables. (Hint. Use a function around a sub-expression)

Consider the following expression:

x = "and" * (3 + 2) > "or" + "4"

What is the data type of value that is computed by this expression?

The data type of value that is computed by this expression is bool.

    x = "and" * (3 + 2) > "or" + "4" ⇒ x = "and" * 5 > "or" + "4" ⇒ x = "andandandandand" > "or4" ⇒ x = False

Consider the following code segment:

When the program is run, the user first enters 10 and then 5, it gives an error. Find the error, its reason and correct it

The error is:

TypeError: can only concatenate str (not "int") to str

It occurs because a is of type string but b is of type int. We are trying to add together a string operand and an int operand using addition operator. This is not allowed in Python hence this error occurs.

To correct it, we need to cast a to int like this:

a = int(input())

If the user runs the program and enters 11 for a and 9 for b then what will the above code display?

input() function accepts user input as string type. The data type of a and b is string not int so addition operator concatenates them to print 119 instead of 20.

Find out the error and the reason for the error in the following code. Also, give the corrected code.

a and b are defined as strings not float or int. Division operator doesn't support strings as its operand so we get the error — unsupported operand type(s) for /: "str" and "str".

The corrected code is:

Consider the following program. It is supposed to compute the hypotenuse of a right triangle after the user enters the lengths of the other two sides.

When this program is run, the following output is generated (note that input entered by the user is shown in bold):

Enter the length of the first side: 3 Enter the length of the second side: 4 Traceback (most recent call last): h = sqrt(a * a + b * b) NameError: name 'sqrt' is not defined

Why is this error occurring? How would you resolve it ?

The error is coming because math module is not imported in the code. To resolve it, we should import the math module using the import statement import math.

After adding import math to the code given above, what other change(s) are required in the code to make it fully work ?

After adding import math statement, we need to change the line h = sqrt(a * a + b * b) to h = math.sqrt(a * a + b * b) . The corrected working code is below:

Which of the following expressions will result in an error message being displayed when a program containing it is run?

(b) "3" + "Hello"

(d) int("5")/float("3")

(e) float("6"/"2")

(a) No Error

(b) No Error

(c) No Error

(d) No Error

(e) This will cause an error of unsupported operand types as using division operator on string types is not allowed in Python.

Question 15a

Following expression does not report an error even if it has a sub-expression with 'divide by zero' problem:

What changes can you make to above expression so that Python reports this error?

Interchanging the operands of or operator as shown below will make Python report this error:

Question 15b

What is the output produced by following code?

The above code will give an error as the line print (len(a), len(b)) is calling len function with bool arguments which is not allowed in Python.

Given a string s = "12345". Can you write an expression that gives sum of all the digits shown inside the string s i.e., the program should be able to produce the result as 15 (1+2+3+4+5). [Hint. Use indexes and convert to integer]

Predict the output if e is given input as 'True':

• As 0 < 5 is True so b value of b becomes True and its type is bool.
• print (a == b) gives True as a and b both are True.
• print (a is b) gives True as a and b both being True point to the same object in memory.
• Similarly print (c == d) and print (c is d) give True as c and d both are string and point to the same object in memory.
• The user input for e is True so e is of type string having value "True".
• As value of strings c and e is "True" so print (c == e) gives True.
• Even though the values of strings c and e are same, they point to different objects in memory so print (c is e) gives False.

Question 18a

Find the errors(s)

The line name[2] = 'R' is trying to assign the letter 'R' to the second index of string name but strings are immutable in Python and hence such item assignment for strings is not supported in Python.

Question 18b

false and true are invalid literals in Python. The correct boolean literals are False and True.

Question 18c

In the line print (type (int("Hello"))) , string "Hello" is given as an argument to int() but it cannot be converted into a valid integer so it causes an error.

Question 18d

In the line print (type (float("three point fourteen"))) , string "three point fourteen" is given as an argument to float() but it cannot be converted into a valid floating-point number so it causes an error.

Question 18e

The line print ("Hello" + 2) causes an error as addition operator (+) cannot concatenate a string and an int.

Question 18f

Both the lines of this Python code will give an error as strings cannot be used with division operator (/).

Question 19a

What will be the output produced?

• x or (y and z) ⇒ True or (False and False) ⇒ True
• (x or y) and z ⇒ (True or False) and False ⇒ True and False ⇒ False

Question 19b

This code produces an error in the line z = x + y as operands of addition operator (+) are string and int, respectively which is not supported by Python.

Question 19c

• s1 = s + '2' concatenates 'Sipo' and '2' storing 'Sipo2' in s1.
• s2 = s * 2 repeats 'Sipo' twice storing 'SipoSipo' in s2.

Question 19d

    -(x + z) < y or x ** z < 10 ⇒ -(4 + 2) < -6 or 4 ** 2 < 10 ⇒ -6 < -6 or 4 ** 2 < 10 ⇒ -6 < -6 or 16 < 10 ⇒ False or False ⇒ False

Program is giving a weird result of "0.50.50.50.50.50.50..........". Correct it so that it produces the correct result which is the probability value (input as 0.5) times 150.

[Hint. Consider its datatype.]

The corrected program is below:

Consider the code given below:

Which of the following are the possible outcomes of the above code ? Also, what can be the maximum and minimum number generated by line 2 ?

(a) 655, 705, 220 (b) 380, 382, 505 (c) 100, 500, 999 (d) 345, 650, 110

The possible outcomes of the above code can be:

Option (a) — 655, 705, 220 Option (d) — 345, 650, 110

Maximum number can be 995 and minimum number can be 100.

Which of the following are the possible outcomes of the above code? Also, what can be the maximum and minimum number generated by line 2?

(a) 12 45 22 (b) 100 80 84 (c) 101 12 43 (d) 100 12 10

Option (a) — 12 45 22

Maximum number can be 90 and minimum number can be 0.

Which of the following are the possible outcomes of the above code? Also, what can be the maximum and minimum number generated by line 2 ?

(a) 0.5 1.6 9.8 (b) 10.0 1.0 0.0 (c) 0.0 5.6 8.7 (d) 0.0 7.9 10.0

Option (a) — 0.5 1.6 9.8 Option (c) — 0.0 5.6 8.7

Maximum number can be 9.999999..... and minimum number can be 0.

Which of the following is the correct output of the above code?

(a) 7 8 7.5 (b) 8 7 7 (c) 8 7 7.5 (c) 8.5 7 7.5

The correct output of the above code is:

Option (c) — 8 7 7.5

Type C: Programming Practice/Knowledge based Questions

Write a program to obtain principal amount, rate of interest and time from user and compute simple interest.

Write a program to obtain temperatures of 7 days (Monday, Tuesday ... Sunday) and then display average temperature of the week.

Write a program to obtain x, y, z from user and calculate expression : 4x 4 + 3y 3 + 9z + 6π

Write a program that reads a number of seconds and prints it in form : mins and seconds, e.g., 200 seconds are printed as 3 mins and 20 seconds. [Hint. use // and % to get minutes and seconds]

Write a program to take year as input and check if it is a leap year or not.

Write a program to take two numbers and print if the first number is fully divisible by second number or not.

Write a program to take a 2-digit number and then print the reversed number. That is, if the input given is 25, the program should print 52.

Try writing program (similar to previous one) for three digit number i.e., if you input 123, the program should print 321.

Write a program to take two inputs for day, month and then calculate which day of the year, the given date is. For simplicity, take 30 days for all months. For example, if you give input as: Day3, Month2 then it should print "Day of the year : 33".

Write a program that asks a user for a number of years, and then prints out the number of days, hours, minutes, and seconds in that number of years.

How many years? 10 10.0 years is: 3650.0 days 87600.0 hours 5256000.0 minutes 315360000.0 seconds

Write a program that inputs an age and print age after 10 years as shown below:

What is your age? 17 In ten years, you will be 27 years old!

Write a program whose three sample runs are shown below:

Sample Run 1: Random number between 0 and 5 (A) : 2 Random number between 0 and 5 (B) :5. A to the power B = 32

Sample Run 2: Random number between 0 and 5 (A) : 4 Random number between 0 and 5 (B) :3. A to the power B = 64

Sample Run 3: Random number between 0 and 5 (A) : 1 Random number between 0 and 5 (B) :1. A to the power B = 1

Write a program that generates six random numbers in a sequence created with (start, stop, step). Then print the mean, median and mode of the generated numbers.

Write a program to generate 3 random integers between 100 and 999 which is divisible by 5.

Write a program to generate 6 digit random secure OTP between 100000 to 999999.

Write a program to generate 6 random numbers and then print their mean, median and mode.

Write a program to find a side of a right angled triangle whose two sides and an angle is given.

Write a program to calculate the radius of a sphere whose area (4πr 2 ) is given.

Write a program that inputs a string and then prints it equal to number of times its length, e.g.,

Enter string : "eka" Result ekaekaeka

Find the volume of the cylinder (πr 2 h) as shown:

Radius = 8 cm Height = 15 cm

Write a program to calculate the area of an equilateral triangle. (area = (√3 / 4) * side * side).

Write a program to input the radius of a sphere and calculate its volume (V = 4/3πr 3 )

Write a program to calculate amount payable after simple interest.

Write a program to calculate amount payable after compound interest.

Write a program to compute (a + b) 3 using the formula a 3 + b 3 + 3a 2 b + 3ab 2

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Grade 6 Data Handling Worksheets

Grade 6 maths data handling multiple choice questions (mcqs).

A. Multiple Choice Questions (MCQs)

1. A ……………….. is a collection of numbers gathered to give some information. (a) bar graph (b) data (c) frequency (d) tally mark

3. In a bar graph bars are made ……………. . (a) horizontally (b) vertically (c) sometimes horizontally sometimes vertically (d) oblique

• CBSE Worksheets for Class 6 Maths Data Handling Assignment 1
• CBSE Worksheets for Class 6 Maths Data Handling Assignment 2
• CBSE Worksheets for Class 6 Maths Data Handling Assignment 3
• CBSE Worksheets for Class 6 Maths Data Handling Assignment 4
• CBSE Worksheets for Class 6 Maths Data Handling Assignment 5
• CBSE Worksheets for Class 6 Maths Data Handling Assignment 6
• CBSE Worksheets for Class 6 Maths Data Handling Assignment 7

4. Representation of data in the fonn of picture is called ………………. . (a) bar graph (b) pictograph (c) histogram (d) none of these

5. In a bar graph space between rectangles is always ……………. . (a) unequal (b) increasing (c) decreasing (d) equal

7. In a bar graph the width of the rectangle is ……………. . (a) unequal (b) increasing (c) decreasing (d) equal

9. Which day had full attendance? (a) Thursday (b) Friday (c) Wednesday (d) Saturday

10. What was the total number of absentees in that week? (a) 600 (b) 130 (c) 150 (d) 100

11. What was the total number of absentees on Tuesday? (a) 20 (b) 25 (c) 50 (d) 10

12. On which day 5 students were absent? (a) Thursday (b) Friday (c) Wednesday (d) Saturday

13. On which day 30 students were absent? (a) Thursday (b) Friday (c) Wednesday (d) Saturday

15. Flow many people liked red colour? (a) 120 (b) 80 (c) 50 (d) 110

16. Find the number of people preferring white colour. (a) 20 (b) 80 (c) 50 (d) 10

17. Which colour preferred most? (a) red (b) blue (c) yellow (d) black

18. Which colour preferred least? (a) green (b) white (c) yellow (d) black

19. Which two colours liked by same number of people? (a) green and red (b) white and yellow (c) green and black (d) black and red

20. Find the number of people preferring yellow colour. (a) 20 (b) 80 (c) 50 (d) 60

B. The following pictograph shows the number of Maruti van manufactured during a week. Read the table and answer the questions given below (Q1 – Q7):

C. Following table shows the number of bicycles manufactured in a factory during the year 1998 to 2002. Read the table and answer the questions given below (Q8 – Q13):

8. In which year were the maximum number of bicycles manufactured? ……………. 9. In which year were the minimum number of bicycles manufactured? …………….. 10. How many bicycles were manufactured from 1998 to 2002? …………….. 11. What is the difference between number of bicycles manufactured in 2002 and 1999? ……………… 12. How many bicycles were manufactured from 1998 to 2000? ……………… 13. On which year did the number of bicycles differ the most from the preceding year? …………..

D. The bar graph shows the number of cars sold in a showroom during five different years (Q14 – Q17):

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Maths and Science Lessons

South Africa Maths and Science Lessons Online

Grade 7 – Data handling 1: Collecting, organising & summarising data

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• Support knowledge, grasp and understanding, by completing a digital, interactive assignment
• Earn a badge for having successfully completed the tutorial and assignment.

Format of tutorial:

• View introductory videos
• Study content slides on the topic (1 – 2 hours in total)
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Course Content

Video introduction to data handling, collecting data, video organising data, organising data, video summarising data, summarising data, genius – data handling fun game, summary of all pdf slides for printing.

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6.894 : Interactive Data Visualization

Assignment 2: exploratory data analysis.

In this assignment, you will identify a dataset of interest and perform an exploratory analysis to better understand the shape & structure of the data, investigate initial questions, and develop preliminary insights & hypotheses. Your final submission will take the form of a report consisting of captioned visualizations that convey key insights gained during your analysis.

Step 1: Data Selection

First, you will pick a topic area of interest to you and find a dataset that can provide insights into that topic. To streamline the assignment, we've pre-selected a number of datasets for you to choose from.

However, if you would like to investigate a different topic and dataset, you are free to do so. If working with a self-selected dataset, please check with the course staff to ensure it is appropriate for the course. Be advised that data collection and preparation (also known as data wrangling ) can be a very tedious and time-consuming process. Be sure you have sufficient time to conduct exploratory analysis, after preparing the data.

After selecting a topic and dataset – but prior to analysis – you should write down an initial set of at least three questions you'd like to investigate.

Part 2: Exploratory Visual Analysis

Next, you will perform an exploratory analysis of your dataset using a visualization tool such as Tableau. You should consider two different phases of exploration.

In the first phase, you should seek to gain an overview of the shape & stucture of your dataset. What variables does the dataset contain? How are they distributed? Are there any notable data quality issues? Are there any surprising relationships among the variables? Be sure to also perform "sanity checks" for patterns you expect to see!

In the second phase, you should investigate your initial questions, as well as any new questions that arise during your exploration. For each question, start by creating a visualization that might provide a useful answer. Then refine the visualization (by adding additional variables, changing sorting or axis scales, filtering or subsetting data, etc. ) to develop better perspectives, explore unexpected observations, or sanity check your assumptions. You should repeat this process for each of your questions, but feel free to revise your questions or branch off to explore new questions if the data warrants.

• Final Deliverable

Your final submission should take the form of a Google Docs report – similar to a slide show or comic book – that consists of 10 or more captioned visualizations detailing your most important insights. Your "insights" can include important surprises or issues (such as data quality problems affecting your analysis) as well as responses to your analysis questions. To help you gauge the scope of this assignment, see this example report analyzing data about motion pictures . We've annotated and graded this example to help you calibrate for the breadth and depth of exploration we're looking for.

Each visualization image should be a screenshot exported from a visualization tool, accompanied with a title and descriptive caption (1-4 sentences long) describing the insight(s) learned from that view. Provide sufficient detail for each caption such that anyone could read through your report and understand what you've learned. You are free, but not required, to annotate your images to draw attention to specific features of the data. You may perform highlighting within the visualization tool itself, or draw annotations on the exported image. To easily export images from Tableau, use the Worksheet > Export > Image... menu item.

The end of your report should include a brief summary of main lessons learned.

Recommended Data Sources

To get up and running quickly with this assignment, we recommend exploring one of the following provided datasets:

World Bank Indicators, 1960–2017 . The World Bank has tracked global human developed by indicators such as climate change, economy, education, environment, gender equality, health, and science and technology since 1960. The linked repository contains indicators that have been formatted to facilitate use with Tableau and other data visualization tools. However, you're also welcome to browse and use the original data by indicator or by country . Click on an indicator category or country to download the CSV file.

Chicago Crimes, 2001–present (click Export to download a CSV file). This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system.

Daily Weather in the U.S., 2017 . This dataset contains daily U.S. weather measurements in 2017, provided by the NOAA Daily Global Historical Climatology Network . This data has been transformed: some weather stations with only sparse measurements have been filtered out. See the accompanying weather.txt for descriptions of each column .

Social mobility in the U.S. . Raj Chetty's group at Harvard studies the factors that contribute to (or hinder) upward mobility in the United States (i.e., will our children earn more than we will). Their work has been extensively featured in The New York Times. This page lists data from all of their papers, broken down by geographic level or by topic. We recommend downloading data in the CSV/Excel format, and encourage you to consider joining multiple datasets from the same paper (under the same heading on the page) for a sufficiently rich exploratory process.

The Yelp Open Dataset provides information about businesses, user reviews, and more from Yelp's database. The data is split into separate files ( business , checkin , photos , review , tip , and user ), and is available in either JSON or SQL format. You might use this to investigate the distributions of scores on Yelp, look at how many reviews users typically leave, or look for regional trends about restaurants. Note that this is a large, structured dataset and you don't need to look at all of the data to answer interesting questions. In order to download the data you will need to enter your email and agree to Yelp's Dataset License .

Additional Data Sources

If you want to investigate datasets other than those recommended above, here are some possible sources to consider. You are also free to use data from a source different from those included here. If you have any questions on whether your dataset is appropriate, please ask the course staff ASAP!

• data.boston.gov - City of Boston Open Data
• MassData - State of Masachussets Open Data
• data.gov - U.S. Government Open Datasets
• U.S. Census Bureau - Census Datasets
• IPUMS.org - Integrated Census & Survey Data from around the World
• Federal Elections Commission - Campaign Finance & Expenditures
• Federal Aviation Administration - FAA Data & Research
• fivethirtyeight.com - Data and Code behind the Stories and Interactives
• Buzzfeed News
• Socrata Open Data
• 17 places to find datasets for data science projects

Visualization Tools

You are free to use one or more visualization tools in this assignment. However, in the interest of time and for a friendlier learning curve, we strongly encourage you to use Tableau . Tableau provides a graphical interface focused on the task of visual data exploration. You will (with rare exceptions) be able to complete an initial data exploration more quickly and comprehensively than with a programming-based tool.

• Tableau - Desktop visual analysis software . Available for both Windows and MacOS; register for a free student license.
• Data Transforms in Vega-Lite . A tutorial on the various built-in data transformation operators available in Vega-Lite.
• Data Voyager , a research prototype from the UW Interactive Data Lab, combines a Tableau-style interface with visualization recommendations. Use at your own risk!
• R , using the ggplot2 library or with R's built-in plotting functions.
• Jupyter Notebooks (Python) , using libraries such as Altair or Matplotlib .

Data Wrangling Tools

The data you choose may require reformatting, transformation or cleaning prior to visualization. Here are tools you can use for data preparation. We recommend first trying to import and process your data in the same tool you intend to use for visualization. If that fails, pick the most appropriate option among the tools below. Contact the course staff if you are unsure what might be the best option for your data!

Graphical Tools

• Tableau Prep - Tableau provides basic facilities for data import, transformation & blending. Tableau prep is a more sophisticated data preparation tool
• Trifacta Wrangler - Interactive tool for data transformation & visual profiling.
• OpenRefine - A free, open source tool for working with messy data.

Programming Tools

• JavaScript data utilities and/or the Datalib JS library .
• Pandas - Data table and manipulation utilites for Python.
• dplyr - A library for data manipulation in R.
• Or, the programming language and tools of your choice...

The assignment score is out of a maximum of 10 points. Submissions that squarely meet the requirements will receive a score of 8. We will determine scores by judging the breadth and depth of your analysis, whether visualizations meet the expressivenes and effectiveness principles, and how well-written and synthesized your insights are.

We will use the following rubric to grade your assignment. Note, rubric cells may not map exactly to specific point scores.

Submission Details

This is an individual assignment. You may not work in groups.

Your completed exploratory analysis report is due by noon on Wednesday 2/19 . Submit a link to your Google Doc report using this submission form . Please double check your link to ensure it is viewable by others (e.g., try it in an incognito window).

Resubmissions. Resubmissions will be regraded by teaching staff, and you may earn back up to 50% of the points lost in the original submission. To resubmit this assignment, please use this form and follow the same submission process described above. Include a short 1 paragraph description summarizing the changes from the initial submission. Resubmissions without this summary will not be regraded. Resubmissions will be due by 11:59pm on Saturday, 3/14. Slack days may not be applied to extend the resubmission deadline. The teaching staff will only begin to regrade assignments once the Final Project phase begins, so please be patient.

• Due: 12pm, Wed 2/19
• Recommended Datasets
• Example Report
• Visualization & Data Wrangling Tools
• Submission form

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Download Free PDF easy notes for Data handling using Pandas-I Series Class 12

In this article, Data Handling using Pandas-I you will learn about the Python Pandas data structure series.

Topics Covered

Introduction to Python Libraries

Python libraries are in-built Python modules that allow performing system-related operations, IO operations, data analysis, and some other standard operations. Pandas library is used for data analysis.

Introduction to Data handling using Pandas-I

Important points for pandas:

• Pandas word derived from PAN el DA ta S ystem.
• It becomes popular for data analysis.
• It provides highly optimized performance with back-end source code purely written in C or Python.
• It makes a simple and easy process for data analysis. 

Pandas offer two basic data structures:

To work with pandas import the pandas library and create one object using one of these statements:

Looking for questions on the series? Follow this link:

Assignment Questions on Pandas Series

Data handling using Pandas-I Series

Series is an important data structure of pandas. It represents a one-dimensional array, containing an array of data. It can be any type of NumPy data. Basically series has two main components:

• An Array (Values)
• An index associated with an array (labels)

Task 1 Creating Series

The Series() function from the pandas module is used to create a series. 

An empty panda series has float64 data type.

Creating non-empty series

In non-empty series data and index will be supplied while creating series. Here data can be one of these data types:

• A python sequence
• A dictionary
• A scalar value
• Equi-space Elements
• Repeated list

Creating series with a python sequence (Data handling using Pandas-I)

range() function is used to generate a series with python pandas.

In the above screenshot, a series is created with float numbers. Observe this code:

Series can be also created using a list of characters. Observe this series of vowels.

A series can be also created using a list of words/names. Let’s have a look at this code:

Creating Series with ndarray (Data handling using Pandas-I)

Creating a series from ndarray named nda. An array of odd numbers between 1 to 10 is created through the arange() function.

The arange() function also useful for creating a series with decimal step values such as 0.5, 0.8 etc. Observe this code:

Creating a series with a dictionary

Crating series from Dictionary object and storing first three days of the week in series. when a series is created using a dictionary, the dictionary keys become an index of a series by default.

Creating a series with a scalar value

Series created with scalar value 5. When a series is created using a scalar value, the index must be specified.

Task 2 Specifying NaN values in the series

Specified NaN at the index 1. If the data value for the series is unknown, python assigns the value as NaN (Not a Number). There are two methods to assign NaN: np.NaN and None in the sequence.

Task 3 creating series and specifying index

In the above example, two lists were created for train numbers and train names. Train no list assigned as data and train name assigned as indexes.

Task 4 Creating series using arithmetic operation

In this example, a series is created with a * 3 as data.

Task 5 Creating series with equispaced elements

To create a series with equispaced elements linspace() function of numpy module is used. Let’s have a look:

Task 6 Creating series using the repeated list

A list can be replicated or repeated to create a series. This can be done using two methods:

• Using tile() function of numpy module
• using replication operator for list

Just have a look at the following code:

Data handling using Pandas-I Common Series attributes

Common series attribute Example

Attributes Example:

Watch this video to understand the practical aspects:

Accessing elements from series

In the above screenshot, I have accessed elements by using their index value such as ser[2] and ser[3].

Observe the following which accesses 3rd and last element using a positional index.

The series can be also accessed using its label or index. Observe this code:

Follow this link to read the questions and answer:

Informatics practices Series QnA

Modifying series elements

In the above screenshot code, I have changed the element value with a scalar value. In Python, series objects are valued mutable i.e. values can be changed but the size is immutable i.e. can’t be changed.

Slicing in Series (Data handling using Pandas-I)

Slicing is also one of the methods to select/access or modify data from a series. Observe this code:

head() and tail() function in series (Data handling using Pandas-I)

The head() function displays n number of elements from the top in the series. In the above example, I have accessed top 3 elements. If no value is passed in the parameter then by default it will display 5 elements from the top. Similarly, the tail function will work and display n number of elements from the bottom.

Observe this code and the output will return the first 5 elements from series:

The following code will return the last 5 elements from a series:

The following codes display n rows from top and bottom, I have taken 3 as n.

Vector and arithmetic operations on series

Here I have used different vector operations and operators to perform various tasks on series.

Observe this code:

Watch this video for practical understanding:

drop() method – (Data handling using Pandas-I)

drop(): R emove any entry from the series.

Observe this code and output to understand:

Follow this link for practical programs with solutions:

Python Pandas Series Practicals with solutions

Watch this video for series program:

Follow this link to read questions about the Python pandas series for class 12.

Important Questions for Python pandas series class XII

Download PDF

Download pdf for Python Pandas – Series from the below given button:

Thank you for reading the article. Feel free to ask any doubt in the comment section and share this article with your friends and classmates.

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Mathematics - Class ...

Topic outline

Data Handling

Pictorial Representation of Data

When we represent numerical data through pictures or graph, it is termed as pictorial representation of data . Such visual representation makes our understanding more clear.

In pictograph we use icon, pictures, symbol etc. repetitively, to show the relationship between two variable quantities. Pictograph can also be referred as pictogram, pictorial chart, pictorial graph, or picture graph. The quantity that each symbol or picture symbolizes is specified clearly in the representation, this helps to represent large quantities of data.

Example: The below graph shows how many oranges were sold in 3 weeks

Now, answer the following questions:

Q1. How many oranges were sold during the third Week?

Ans. 20 x 3 = 60 oranges (as each orange stand for 20 oranges)

Q2. In which Week the oranges sold were maximum?

Ans. In Week 2

Pie Chart / Pie Graph

Representing numerical data by dividing a circle into slices or sectors is called pie chart or pie graph or circle graph . Each sector in pie chart represents a fraction of whole. It is simple to understand as it summarizes a large data in visual form.

Example: In a circle below are the details of library books in the school library.

Q1.  How many books are there in the library in all?

Ans. 1000 books

Q2. Name the subject on which least number of books is there in the library.

Ans. French, 100

Q3. Find the number of books on Math subject in the library.

Q4. Work out the difference between the number of French books and English books.

Ans. English Books – 300

       French Books – 100

       Difference = 300 – 100

                      = 200

Bar Graph/Column Chart

Bar graph is the simplest form of representing data by displaying rectangular bars of different heights proportional to the value they represent. Bar graph can also be referred as bar chart, column graph, and column chart .

The bars can be plotted vertically or horizontally. Bar graph makes comparison easier. The title of the bar graph tells what the graph is about and bars of different height tell the facts or information. Each bar represents a quantity for a particular group.

Example: The graph shows different grades scored by students in grade 4.

Q1. How many students scored Grade B?

Ans. 25 students

Q2. Which Grade was least scored?

Ans. Grade D

Q3. How many student scored Grade A?

Ans. 10 students

Q4. How many students are there in grade 4?

Ans. 10 + 25 + 10 + 5 = 50 students

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Arinjay Academy » Maths » Data handling Worksheets for Grade 3

• Data handling Worksheets for Grade 3

Download Data handling Worksheets for Grade 3

Q.1) The following pictograph shows the number of bananas Aman and Mohit ate during the week- Each symbol = 2 bananas

i) Find the number of bananas they ate on Tuesday ?

iii) Find the number of bananas they ate on Wednesday ?

iv) Find the total number of bananas they ate on Sunday, Wednesday and Thursday?

v) On which day maximum number of bananas were eaten ?

[B] Thursday

[C] Wednesday

Q.2) The following pictograph shows how much pocket money Sanjay earned every day from Tuesday to Saturday –

Each symbol = ₹ 5

i) How much money did Sanjay earn on Tuesday ?

ii) How much money did Sanjay earn on Friday ?

iii) On which day did he earn the maximum money ?

[A] Saturday

[C] Thursday

iv) ​What is the total amount earned by him on Thursday, Friday and Saturday ?

v) On which day did he earn the minimum money ?

[B] Wednesday

[C] Saturday

Q.3) The following pictograph shows how many students of a class like which of the games –

Each symbol = 6 Students

i) ​How many students like Football ?

ii) How many students like Cricket ?

iii) Which game is liked the most by the students ?

[B] Badminton

[C] Cricket

iv) Which game is liked the least by the students ?

[B] Football

v) What is the total number of students who like Badminton or Hockey ?

Q.4) The following pictograph shows how many students of a class like which of the flavours of Ice cream –

Each symbol  = 12 Students

i) ​How many students like Chocolate flavours ?

ii) How many students like Chocolate marshmallow flavour ?

iii) ​Which flavour of ice cream is liked the most by the students ?

[A] Chocolate

[B] Strawberry

[C] Vanilla

iv) ​Which flavour of ice cream is liked the least by the students ?

[A] Butter pecan

[B] Vanilla

[C] Chocolate Marshmallow

v) Which flavour of ice cream is liked equally by the students ?

[A] Chocolate Marshmallow & Strawberry

[B] Chocolate Marshmallow & Butter pecan

[C] Strawberry & Vanilla

Q.5) The following pictograph shows the transport used by the students to reach the school –

i) How many students come by Motorcycle?

ii) How many students come by Car ?

iii) How many students come by Bus or Scooter ?

iv) How many students come by Auto ?

v) Which transport is used by the least number of students ?

[B] Scooter

Data handling Worksheets for Grade 3 Explanations

Q.1) Explanation – Data handling Worksheets for Grade 3

(i) Given that each symbol = 2 bananas

So, the number of bananas they ate on Tuesday = Number of Stars on Tuesday  x 2 =  ( 2 x 2 ) =    4

(ii) Given that each symbol = 2 bananas So, the number of bananas they ate on Monday = Number of Stars on Monday  x 2 =  ( 2 x 3 ) =   6

(iii) Given that each symbol = 2 bananas So, the number of bananas they ate on Wednesday =  Number of Stars on Wednesday  x 2 = ( 2 x 4 ) =   8

(iv) Given that each symbol = 2 bananas So, the number of bananas they ate on Sunday = ( 2 x 1 ) = 2 The number of bananas they ate on Wednesday = ( 2 x 4 ) = 8 The number of bananas they ate on Thursday = ( 2 x 5 ) =   10 The total number of bananas they ate on Sunday, Wednesday and Thursday = 2 + 8 + 10 = 20

(v) Since there are maximum number of symbols on Thursday, maximum number of bananas were eaten on Thursday.

Q.2) Explanation – Data handling Worksheets for Grade 3

(i) Given that each symbol = ₹ 5 So, money earned by Sanjay on Tuesday = Number of symbols on Tuesday X 5  =    ( 5 x 3 ) = ₹ 15

(ii) Given that each symbol = ₹ 5 So, money earned by Sanjay on Friday = Number of symbols on  x 5 =  ( 5 x 4 ) =   ₹ 20

(iii) Since there are maximum numbers of symbols on Thursday, the maximum money is earned on Thursday.

(iv) Given that each symbol = ₹ 5 So, money earned by Sanjay on Thursday = ( 5 x 5 ) = ₹ 25 Money earned by Sanjay on Friday  = ( 5 x 4 ) =  ₹ 20 Money earned by Sanjay on Saturday = ( 5 x 1 ) = ₹ 5 Total amount of money earned by him on Thursday, Friday and Saturday is = ₹ 25 + ₹ 20 + ₹ 5 = ₹50

(v) Since there are minimum numbers of symbols on Saturday, the minimum money is earned on Saturday.

Q.3) Explanation – Data handling Worksheets for Grade 3

(i) Given that each symbol = 6 Students So,  the number of students who like Football = Number of symbols in Football X 6 = ( 6 x 3 ) =  18

(ii) Given that each symbol = 6 Students So,  the number of students who like Cricket = Number of symbols in Cricket x 6 =  ( 6 x 5 ) = 30

(iii) Since, there are maximum numbers of symbols for Cricket, Cricket is liked the most by the students.

(iv) Since, there are minimum numbers of symbols for Tennis, Tennis is liked the least by the students.

(v) Given that each symbol = 6 Students Number of students who like Badminton = ( 6 x 4 ) =  24 The number of students who like Hockey = ( 6 x 2 ) = 12 Total number of students who like Badminton or Hockey = 24 + 12 =  36

Q.4) Explanation – Data handling Worksheets for Grade 3

(i) Given that each symbol = 12 Students So, the number of students who like Chocolate flavour =  Number of symbols in Chocolate x 5 = ( 12 x 5 ) = 60

(ii) Given that each symbol = 12 Students So, the number of students who like Chocolate marshmallow flavour = Number of symbols in marshmallow x 4   =  ( 12 x 4 ) = 48

(iii) Since, there are maximum number symbols for Chocolate flavour, Chocolate flavour is liked the most by the students.

(iv) Since, there are minimum number of symbols for Vanilla flavour, Vanilla is liked the least by the students.

(v) Since, there are equal numbers of symbols for Strawberry and Chocolate marshmallow, Strawberry and Chocolate marshmallow flavours are liked equally by the students.

Q.5) Explanation – Data handling Worksheets for Grade 3

(i) Given that each symbol = 15 Students So,  the number of students who use Motorcycle to reach school = Number of symbols in X 4 = ( 12 x 4 ) =  48

(ii) Given that each symbol = 15 Students So,  the number of students who use Car to reach school = ( 12 x 3 ) =  36

(iii) Given that each symbol = 15 Students So,  the number of students who use Bus to reach school = ( 12 x 2 ) =  24 The number of students who use Scooter to reach school = ( 12 x 1 ) =  12| The number of students who use Bus or Scooter to reach school = 24 + 13  = 37

(iv) Given that each symbol = 15 Students So,  the number of students who use Auto to reach school = ( 12 x 3 ) =  36

(v) Since, there are minimum numbers of symbols for Scooter, Scooter is used by the least number of students.

Maths Worksheets for Class 3

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• Money Worksheets Grade 3
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Worksheets for Class 3

Cbse notes for class 3, leave a comment cancel reply.

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We have provided below free printable Class 6 Mathematics Data Handling Assignments for Download in PDF. The Assignments have been designed based on the latest NCERT Book for Class 6 Mathematics Data Handling . These Assignments for Grade 6 Mathematics Data Handling cover all important topics which can come in your standard 6 tests and examinations. Free printable Assignments for CBSE Class 6 Mathematics Data Handling , school and class assignments, and practice test papers have been designed by our highly experienced class 6 faculty. You can free download CBSE NCERT printable Assignments for Mathematics Data Handling Class 6 with solutions and answers. All Assignments and test sheets have been prepared by expert teachers as per the latest Syllabus in Mathematics Data Handling Class 6. Students can click on the links below and download all Pdf Assignments for Mathematics Data Handling class 6 for free. All latest Kendriya Vidyalaya Class 6 Mathematics Data Handling Assignments with Answers and test papers are given below.

Mathematics Data Handling Class 6 Assignments Pdf Download

We have provided below the biggest collection of free CBSE NCERT KVS Assignments for Class 6 Mathematics Data Handling . Students and teachers can download and save all free Mathematics Data Handling assignments in Pdf for grade 6th. Our expert faculty have covered Class 6 important questions and answers for Mathematics Data Handling as per the latest syllabus for the current academic year. All test papers and question banks for Class 6 Mathematics Data Handling and CBSE Assignments for Mathematics Data Handling Class 6 will be really helpful for standard 6th students to prepare for the class tests and school examinations. Class 6th students can easily free download in Pdf all printable practice worksheets given below.

Topicwise Assignments for Class 6 Mathematics Data Handling Download in Pdf

Advantages of Class 6 Mathematics Data Handling Assignments

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