University Question Paper - CST 445 Python For Engineers KTU May 2023 ( sup)

 

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Python For Engineers CST 445 KTU Open Elective Notes Dr Binu V P 9847390760

About Me About the Course and Syllabus Model Question Paper Python For Engineers CST 445 University Question Paper- Python For Engineers CST 445 -Jan 2023 University Question Paper- Python For Engineers CST 445 -May 2023 ( supl) University Question Paper- Python For Engineers CST 445- Jan 2024  University Question Paper-Python For Engineers CST 445- June 2024(supl) Module 1:Basics of Python  1.Introduction to Python 2.Running Python Program- IDLE,Interactive Shell, Jupyter notebook 3.Identifiers, variables and keywords 4.Basic Python data types- numbers and strings, type conversion 5.Operators 6.Operator precedence and expression evaluation 7.Input and output- input() and print() 8.Built-in functions, modules and packages 9.The software development process 10.Simple programs to begin with, comments and statements 11.Basic Programs to try 12.Programs using built-in functions and modules 13.Sample Programs ( contact) Control statements  14.Selection statement -if else- sample programs 15
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Plotting- Simple plots,setting limits,subplot, semilog, loglog plots

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data—plotting—is one of the most important tools for evaluating and understanding scientific data and theoretical predictions. Plotting is not a part of core Python, however,but is provided through one of several possible library modules. The most highly developed and widely used plotting package for Python is matplotlib ( http://matplotlib.sourceforge.net/ ). It is a powerful and flexible program that has become the defacto standard for 2D plotting with Python. Because matplotlib is an external library—in fact it’s a collection of libraries—it must be imported into any routine that uses it. matplotlib makes extensive use of NumPy so the two should be imported together. Therefore, for any program that is to produce 2D plots, you should include the lines import numpy as np import matplotlib.pyplot as plt plot function.   It is used to plot x-y data sets and is written like this plot(x, y) where x and y are arrays (or lists) that have the same size. If the x array is omitted, that is,
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Scipy

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SciPy is an open-source library for mathematics, science, and engineering that builds on the capabilities of the NumPy library. It provides many efficient and user-friendly interfaces for tasks such as numerical integration, optimization, interpolation, signal and image processing, linear algebra, statistics, and more. SciPy is a Python library of mathematical routines. Many of the SciPy routines are Python “wrappers,” that is, Python routines that provide a Python interface, for numerical libraries and routines originally  written in Fortran, C, or C++. Thus, SciPy lets you take advantage of the decades of work that has gone into creating and optimizing numerical routines for science and engineering. Because the Fortran, C, or C++ code that Python accesses is compiled, these routines typically run very fast. Therefore, there is no real downside—no speed penalty—for using Python in these cases. SciPy is organized into sub-packages, each specializing in different aspects of scientif
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