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Rwasi Transport And Contracting Interview Questions and Answers
Q1. What is Python and what are its key features?
Python is a high-level programming language known for its simplicity and readability.
Python is an interpreted language, meaning it does not need to be compiled before execution.
It supports multiple programming paradigms, including object-oriented, imperative, and functional programming.
Python has a large standard library with built-in modules for various tasks, making it versatile and efficient.
It is widely used in data analytics, machine learning, web development, and scient...read more
Q2. What are the different data types in Python?
Different data types in Python include integers, floats, strings, lists, tuples, dictionaries, and booleans.
Integers: whole numbers without decimals (e.g. 5, -10)
Floats: numbers with decimals (e.g. 3.14, -0.5)
Strings: sequences of characters enclosed in quotes (e.g. 'hello', '123')
Lists: ordered collections of items (e.g. [1, 'apple', True])
Tuples: ordered, immutable collections of items (e.g. (1, 'banana', False))
Dictionaries: unordered key-value pairs (e.g. {'key': 'value',...read more
Q3. What is PEP 8 and why is it important?
PEP 8 is a style guide for Python code that outlines best practices for writing clean and readable code.
PEP 8 stands for Python Enhancement Proposal 8.
It covers topics such as indentation, line length, imports, naming conventions, and more.
Following PEP 8 helps improve code consistency, readability, and maintainability.
For example, PEP 8 recommends using 4 spaces for indentation and limiting line length to 79 characters.
Q4. What is machine leaening
Machine learning is a subset of artificial intelligence that involves training algorithms to make predictions or decisions based on data.
Machine learning involves using algorithms to learn patterns in data
It can be supervised, unsupervised, or semi-supervised
Examples include image recognition, natural language processing, and recommendation systems
Q5. How to handle missing values
Missing values can be handled by imputation or deletion.
Imputation involves filling in missing values with estimated values based on other data points.
Deletion involves removing rows or columns with missing values.
The choice of method depends on the amount and pattern of missing data.
Imputation methods include mean imputation, regression imputation, and k-nearest neighbor imputation.
Deletion methods include listwise deletion, pairwise deletion, and mean substitution.
Multiple ...read more
Q6. explain the oops concept?
Object-oriented programming paradigm that focuses on objects and classes for code organization and reusability.
Encapsulation: Bundling data and methods that operate on the data into a single unit (class).
Inheritance: Ability of a class to inherit properties and behavior from another class.
Polymorphism: Ability to present the same interface for different data types.
Abstraction: Hiding the complex implementation details and showing only the necessary features of an object.
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