Python for data science

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Arulmigu Meenakshi Amman college of Engineering
Vadamavandal-604410.
Prepared by,
V.Umapathy,
Prof./Mech.
Imortant Questions and Answers
AD25201-Python for Data Science
Syllabus
1. Basics of Python: What is Python, Python Interpreter, Python language basics: Language
Semantics, Data Types, Variables, Basic Functions, Operators, Flow Control Statements,
Data Structures and Sequences: List, Tuple, Set, Dictionaries.
Practical:
1. Programs using conditional and looping constructs
2. Programs using different data frames like list, tuple, set and dictionary.
2. Functions and Files: Defining a Function, Passing Arguments, Return Values, Passing a
List, Creating and Using a Class, Strings: Working with Strings, String Methods, Files:
Reading from a File, Writing to a File, Exceptions, Python Libraries: Importing libraries.
Practical:
1. Programs using functions and classes.
2. Programs using strings and files.
3. Foundations of Data Science: Introduction to Data Science- Applications of Data Science -
Data Science Process: Overview, Defining Research Goals, Retrieving Data - Data
Preparation: Data Wrangling- Handling Missing Data- Data Transformation, Outlier/Noise
and Anomalies, Exploratory Data Analysis, Build the Model, Present Findings, Data Mining,
Data Warehousing.
Practical:
1. Data Creation and Mathematical operations.
2. Graphs and Plotting.
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4. Descriptive Analytics: Facets of Data, Types of Variables, Statistical Description of Data,
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Describing Data with Tables and Graphs, Describing Data with Averages, Describing
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Variability, Normal Distributions and Standard (z) Scores, Correlation, Scatter plots,
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correlation coefficient for quantitative data –computational formula for correlation
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coefficient, Regression, Regression line, least squares regression line.
Practical:
1. Statistical description of data without libraries
2. Generation of correlation coefficient.
3. Linear regression model.
5. Numpy and Pandas Libraries: Creating Arrays, attributes, Numpy Arrays objects, Basic
operations (Array Join- split- search- sort), Indexing, Slicing and Iterating, Copying Arrays,
Arrays shape Manipulation, Identity Array, eye function. Exploring Data using Series-
Exploring Data using Data Frames, Index objects- reindex, Drop Entry, Selecting Entries-
Data Alignment, Rank and Sort, Summary Statistics, Index Hierarchy.
Practical:
1. Creation of 1D, 2D, and 3D NumPy arrays
2. Array Slicing and Indexing operations
3. Reindexing, and aligning data across multiple Data Frames.
6. Data Visualization: Introduction to Matplotlib, Plots, making subplots, Controlling axes,
Ticks, Labels and legends, Annotations and drawing on subplots, Saving plots to files,
Seaborn library, Making sense of data through advanced visualization, Controlling the
properties of Chart, Scatter plot, Line plot, Bar plot, Histogram, Box plot, Pair plot, Styling
your plot, 3D plot of surface.
Practical:
1. Line plot, bar plot, histogram, and box plot.
2. Seaborn plots, plot styling and customization.
S.No. Description
Unit-I
Basics of Python
Prepared by,
V.Umapathy,Prof./Mech.
Basic Concepts
S.
Topic Important Basic Concepts
No.
High-level, interpreted, general-purpose programming language. Simple
1 Python
syntax, readable code, and supports object-oriented programming.
Python Executes Python code. Interactive mode executes statements directly; script
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Interpreter mode runs .py files.
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Language Defines the meaning and behavior of Python statements. Python uses
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Semantics indentation to identify code blocks and is case-sensitive.
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int – integers; float – decimal numbers; complex – complex numbers; str –
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4 Data Types
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strings; bool – True/False; NoneType – no value.
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5 Variables Names used to store values. Example: x = 10, name = "Ravi". Python uses
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dynamic typing; explicit type declaration is not required.
Built-in functions include print() (display), input() (read input), type() (check
6 Basic Functions
type), len() (length), int() and float() (type conversion).
Arithmetic: + - * / // % **; Comparison: == != > < >= <=; Logical: and, or,
7 Operators
not; Assignment: =, +=; Membership: in, not in; Identity: is, is not.
Flow Control if, elif, else – decision-making; for, while – looping; break – terminate loop;
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Statements continue – skip iteration; pass – placeholder statement.
Ordered, mutable collection; allows duplicate values. Example: a = [10, 20,
9 List
30]. Access using a[0]; modify using append() or remove().
Ordered, immutable collection; allows duplicates. Example: t = (10, 20, 30).
10 Tuple
Elements cannot be modified after creation.
Unordered collection of unique elements. Example: s = {10, 20, 30}. Supports
11 Set
union (\|), intersection (&) and difference (-).
Stores data as key–value pairs. Example: d = {"name": "Ravi", "age": 20}.
12 Dictionary
Access using d["name"]; update values using keys.
Important points for examinations

 Mutable: List, Set, Dictionary.
 Immutable: Integer, Float, String, Tuple, Boolean.
 Indexing: Lists and tuples support indexing; ordinary sets do not.
 Indentation: Python uses indentation instead of braces to define blocks.
 Comments: Use # for a single-line comment.
 Output example: print("Hello Python")

Remember: Lists use [], tuples use (), sets use {}, and dictionaries use {key: value}. Empty sets are
created using set(), while {} creates an empty dictionary.
Multiple Choice QA
Prepared by,
V.Umapathy,Prof./Mech.
1. Which of the following is a key feature of Python?

A) Python is a machine-level language

B) Python is a high-level, interpreted programming language
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C) Python does not support functions
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D) Python supports only numerical data

Correct Answer: B) Python is a high-level, interpreted programming language

Reason: Python has simple, readable syntax and supports interpreted execution, making it easy to
develop and test programs.

2. What is the data type of the variable x in the following Python statement?

x = 10.5print(type(x))

A) int

B) str

C) float

D) bool

Correct Answer: C) float

Reason: The value 10.5 is a decimal number, so Python identifies its data type as float.

3. What is the output of the following Python code?

x = 10y = 3print(x // y)

A) 3.33

B) 3

C) 1

D) 30

Correct Answer: B) 3
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Reason: The // operator performs floor division. It returns the quotient rounded down to the nearest
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integer in this example: \(10 // 3 = 3\).
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