Publishing Online Books using Jupyter Book and GitHub Pages
Publishing Online Books using Jupyter Book and GitHub Pages

In this beginner-friendly tutorial, we will learn how to publish online books using Jupyter Book and GitHub Pages. In this tutorial, everything will be discussed in detail. Although you don’t need any pre-requisites as such to follow this tutorial, it is better if you have previous knowledge of markdown syntax and Git commands.

At the end of this tutorial, you will be ready to publish your online book hosted by GitHub. One of the significant benefits of using Jupyter Book and GitHub Pages is that you can easily update the book’s contents at any time. You can also make use…


Exploratory Data Analysis using Python Pandas: A Tutorial
Exploratory Data Analysis using Python Pandas: A Tutorial

In this tutorial, we will learn about exploratory data analysis using Python Pandas. In exploratory data analysis, we analyze the input dataset to summarize its main characteristics. Sometimes, we examine the main features of the input dataset visually using different standard plots.

This is a beginner-friendly tutorial. Here, we assume that the readers are familiar with the basic Python programming language. If you are new to Python programming and have never used Pandas before, you can read the following beginner-friendly tutorial on Python Pandas.

In this tutorial, we will use a well-known dataset, known as Pima Indian Diabetes data. This…


Creating Professional Presentation using Markdown
Creating Professional Presentation using Markdown

In this tutorial, we will learn how to create professional presentations from a Markdown document. Creating good-looking professional slides using Markdown is very easy and less time-consuming. You don’t need to spend time on the design and layout of the slides.

We will use the following software:

  • Visual Studio Code (VS Code)
  • Marp for VS Code

Install VS Code

VS Code is free software and it is used as a source-code editor for many programming languages such as C, Python, Julia, and many more. It is developed by Microsoft, and available in different operating systems such as Windows, Linux, and macOS. If you…


In this tutorial, we will learn about the NetworkX package of Python. NetworkX stands for network analysis in Python. It is mainly used for creating, manipulating, and study complex graphs. This is the Part-I of the tutorial on NetworkX. The remaining tutorial will be posted in different parts.

Prerequisites: Basic knowledge about graph theory and Python programming.

“NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.” — https://networkx.org/

Installation

If the NetworkX package is not installed in your system, you have to install it at first. …


Lambda and map() functions in Python
Lambda and map() functions in Python

This is a tutorial on lambda and map() functions in Python. Here, we will consider Python3. We start with the lambda function, and then we discuss the map() function in Python. This tutorial will help to understand the concepts of lambda and map() functions in Python.

Lambda function

At first, we will learn about the basics of the lambda function in Python. A lambda function is a simple one-line function. It doesn’t use def or return keywords. These are implicit here.

Syntax:

lambda args : exp

where args represents arguments and exp is the expression. The expression is executed and the result…


List and dictionary comprehensions in Python
List and dictionary comprehensions in Python

In this tutorial, we will learn about the list and dictionary comprehensions in Python. We will begin with list comprehension and then we discuss dictionary comprehension.

List Comprehension

List comprehension is an elegant way of creating a new list from an existing list. Let us understand Python’s list comprehension using examples.

Example 1:

At first, we create dummy data. It is a list L of the first ten natural numbers. Using list comprehension, we create another list E which contains the even numbers from L.

L = [1,2,3,4,5,6,7,8,9,10] # dummy dataE = [num for num in L if num%2 == 0]

Descriptive Statistics using Pandas: An Introductory Tutorial
Descriptive Statistics using Pandas: An Introductory Tutorial

In this tutorial, we will learn how to compute descriptive statistics using Python’s Pandas library. We use a well-known dataset in this tutorial. This dataset consists of several medical predictor (independent) variables and one target (dependent) variable, Outcome. Independent variables include the number of pregnancies the patient has had, their BMI, insulin level, age, and so on.

The columns of this dataset are as follows:

  1. Pregnancies — Number of times pregnant
  2. GlucosePlasma — glucose concentration 2 hours in an oral glucose tolerance test
  3. Blood Pressure — Diastolic blood pressure (mm Hg)
  4. SkinThickness — Triceps skin-fold thickness (mm)
  5. Insulin — Two…


Python Pandas DataFrame Tutorial for Beginners
Python Pandas DataFrame Tutorial for Beginners

This is a tutorial on Python Pandas DataFrame for absolute beginners. Pandas is a fast, powerful, flexible, and easy-to-use open-source data analysis and manipulation tool, built on top of the Python programming language. In this tutorial, we will use the Customers.csv file which can be downloaded from here.

Here, we will learn about the following: read_csv() method, shape attribute of DataFrame, head() and tail() methods, info() method, columns and index attributes of DataFrame, dtypes, subsetting of rows and columns, drop, loc, iloc, aggregate function, and groupby.

At first, we import Pandas using the import statement.

# Import Pandas with an…


Solving linear programming problems (LPPs) using PuLP and Python
Solving linear programming problems (LPPs) using PuLP and Python

In this tutorial, we will learn how to solve linear programming problems (LPPs) using PuLP and Python. At first, we learn how to install PuLP. If PuLP is already not installed in your system, then you can use the following commands to install it.

For Ubuntu, run the following command in the terminal:

pip install pulp


In this tutorial, we will learn how to write a model for linear programming problems (LPPs) using Python API and solve the model using IBM Decision Optimization CPLEX (DOcplex) Modeling for Python on your computer with IBM ILOG CPLEX Optimization Studio. Here, we will assume that Python3 and IBM ILOG CPLEX Optimization Studio v12.8 or later are installed on your machine.

Example problem

Consider a chocolate manufacturing company that produces only two types of chocolate — A and B. Both the chocolates require Milk and Choco only. To manufacture each unit of A and B, the following quantities are required:

  • Each unit…

Dr. Soumen Atta, Ph.D.

Assistant Professor at Indian Institute of Information Technology (IIIT) Vadodara, India, and Postdoctoral researcher at Masaryk University, Czech Republic.

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