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In this article we will learn about replacement of punctuation with letter k in the string. You may have seen this problem while performing text processing or data cleaning task in the python where you need to replace punctuations with specific characters or any symbol. Here we will see various methods for replacing the punctuations with given text "k" Let’s get to know this using below example − string = "Welcome, to, * the website ! aliens" Here we have a string which contains punctuations like [, * !] and we want to replace that with text "k". ... Read More
In this article we will see method to replace negative values with zero. If we talk about data analysis then handling negative values is very crucial step to ensure meaningful calculation. So, here you will learn about various methods using which we can replace negative values with 0. Method 1. Using Traversal and List Comprehension. Example import numpy as np arr = np.array([-12, 32, -34, 42, -53, 88]) arr = [0 if x < 0 else x for x in arr] arr = np.array(arr) print("array with replaced values is: ", arr) Output array with replaced values ... Read More
In this article we will see method to replace NaN (Not a Number) value with the average of columns. If we talk about data analysis then handling NaN value is very crucial step. So, here you will learn about various methods using which we can replace NaN (Not a Number) value with the average of columns. Method 1: Using Numpy.nanmean(). Example import numpy as np arr = np.array([[1, 2, np.nan], [4, np.nan, 6], [np.nan, 8, 9]]) col_means = np.nanmean(arr, axis=0) arr_filled = np.where(np.isnan(arr), col_means, arr) print("Column mean: ", col_means) print("Final array: ... Read More
In this article we will see method to replace the multiple characters at once in any string. While working with programs where we face such situation when we will have to replace any particular character simultaneously at all of its occurences. Suppose a situation in which you have an article in which it contains one word named as “word” which is having multiple occurrences and you want to convert that “word” into “work” so you can do this manually but it is very bad practice of doing this work one by one. So, we will look at multiple methods using ... Read More
Entropy is a property of a thermodynamic system that remains constant during a reversible adiabatic process. Moreover, we can also say that it is the degree of randomness or disorder in the system. If a system exchanges dQ heat from its surroundings at temperature T, then the chance in the entropy can be written as − $$\mathrm{ds \: = \: \frac{dQ}{T} \dotso \dotso \: (1)}$$ According to Clausius' inequality the cyclic integral of $\mathrm{\frac{dQ}{T}}$ along a reversible path is either less or equal to zero. Mathematically, it can be written as − $$\mathrm{\oint\frac{dQ}{T} \: \leq \: 0\dotso \dotso \: (2)}$$ ... Read More
In this article we will learn how to replace any given list element with its ordinal number. We will see various methods to get this work done. Before that let’s know about ordinal numbers. Ordinal number − In mathematics we say ordinal number as number which represents the position or original order of list items present in a sequence. Take an example of a list: [ 6, 8, 5, 3 ] so ordinal value of these number would be − The first element (6) has ordinal value 1. The second element (8) has ordinal value 2. The third element ... Read More
In this article we will learn about the Jacobian matrix and how to calculate this matrix using different methods in PyTorch. We use Jacobian matrix in various machine learning applications. Jacobian Matrix We use Jacobian matrix to calculate relation between the input and output variable. Jacobian matrix has all the partial derivatives of vector valued function. We can use this matrix in various applications machine learning applications. Here are some of its usages − For analyzing the gradients and derivatives of functions in multivariable calculus. Solving differential equations of systems. Calculating inverse of vector-values functions. Analyzing stability of dynamic ... Read More
In this article we will learn about pandas, DataFrame and how we can iterate over rows and columns in the pandas DataFrame using various methods. Iteration is a basic operation we do when we have tabular data containing rows and columns. To install the pandas in the system execute the command in cmd. pip install pandas Method 1. Using Iterrows() Method. Example import pandas as pd df = pd.DataFrame({'Name': ['Kalyan', 'Gungun', 'Sona', 'Ram'], 'Age': [21, 20, 23, 23], 'Roll': [12, 13, 14, 15], 'Game': ['Cricket', 'Lodu', 'Chess', ... Read More
In this article we will learn about different methods to find the Summation of Random Numbers using Python language. In some scenarios we need to generate some random number and find its summation so we will see basic to improved versions of functions using which we can get this task done. Let’s see some methods to find the summation of random numbers. Method 1. Using Simple Loop Example import random n = 10 rand_nums = [] for _ in range(n): rand_nums.append(random.randint(1, 100)) total = sum(rand_nums) print("Random Numbers:", rand_nums) print("Summation of random numbers:", total) Output Random Numbers: ... Read More
The purpose of integration (definite) is to calculate the area under a curve of a function between two limits, a and b. The plot shown below will clear this concept further. Quadrature, which is also commonly called as numerical integration, is a method for evaluating the area under the curve of a given function. The process is very simple i.e. first we dividing the bounded area into several regions or strips. Thereafter, the areas is evaluated with the help of mathematical formula of simple rectangle. Then the area of all strips is added to obtain the gross area under ... Read More