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Scipy Library overview

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  SciPy Library Overview SciPy (Scientific Python) is an open-source Python library that provides a wide range of scientific and technical computing functionalities. It is built on top of NumPy and extends its capabilities with additional functions for mathematical algorithms and convenience for scientific computations. SciPy is particularly useful in fields such as: Mathematics Physics Engineering Machine Learning Data Science Key Features and Modules of SciPy SciPy contains several sub-packages, each providing specialized tools for scientific computing: 1. scipy.linalg – Linear Algebra This module builds upon NumPy’s linalg and includes additional linear algebra functions. Matrix operations : Matrix inversion, determinants, solving linear systems. Decompositions : LU, QR, Cholesky decompositions. Eigenvalue problems : Eigenvalues and eigenvectors of matrices. Python code >>import numpy as np >>from scipy.linalg ...
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insertionSort in c language

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  Insertion sort in c language   Note : it is completely based on sorting in ascending order   Implementing code #include<stdio.h>  int main()  {     int i,j,arr[100],temp, count; // declaration variables     printf("enter the of size elements: ");     scanf("%d",&count);     printf("enter the elements in array : ");     for(i=0;i<count;i++)  // inserting elements     {         scanf("%d",&arr[i]);// storing the elements i array     }     for(i=0;i<count;i++)     {         temp=arr[i];   //array values storing in temp variable         j=i-1;      //decreementing the values of 'i' and it will storing in j variable         while((temp<arr[j])&&(j>=0))           {   ...
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python seaborn library

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SEABRON LIBRARY Introduction:               Seaborn is a powerful Python data visualization library built on top of Matplotlib. It provides a high-level interface for creating attractive and informative statistical graphics. With Seaborn, users can quickly create a wide variety of plots, including heatmaps, violin plots, and categorical plots, with minimal code. One of Seaborn's strengths is its ability to work seamlessly with pandas DataFrames, making it ideal for exploring and visualizing complex datasets. It also integrates well with other libraries in the scientific Python ecosystem, such as NumPy and SciPy, offering flexibility for data analysis and presentation.   NOTE :  Seaborn is a Python data visualization library based on Matplotlib, used to make statistical graphics more attractive and informative. Installation of seaborn package : Steps to Install Seaborn: 1.     Open Command Promp...
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