A simple web app and around 15 minutes of your time can make your GitHub Profile stand out. This article also contains a list of resources and tutorials to make your GitHub About Me/Read Me look fancy 😍

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You might have already seen articles explaining the ‘secret’ repo with a cool ReadMe feature in GitHub but put off actually creating one. I built an app to do most of the work for you 😃

Table of Contents

  1. Create the ‘secret’ repo with About Me
  2. GitHub About Me/ Profile README Generator
  3. Emojis and GIFS
  4. Visitor Badge
  5. Github Stats
  6. Latest Blog Posts
  7. WakaTime Stats
  8. Social Icons
  9. Inspiration for your ReadMe
  10. Resources
  11. Conclusion

Create the ‘secret’ repo 🔓

  • Go to https://github.com/new to create a new GitHub repository
  • Set your GitHub username as the repository name. My GitHub user name is rahulbanerjee26 therefore my repo name should also be rahulbanerjee26


Life is short, let Python automate your EDA

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EDA (Exploratory Data Analysis) is one of the first steps performed on a given dataset. It helps us to understand more about our data and gives us an idea of manipulations and cleaning we might have to do. EDA can take anywhere from a few lines to a few hundred lines. In this tutorial, we will look at libraries which help us perform EDA in a few lines

Dataset

We will use the Titanic Dataset provide by Kaggle. Using Panda’s describe() method, we get the below output


In this tutorial, we will be using the Boto3 module in Python to work with Amazon’s NoSQL Database, Dynamo DB. The tutorial will also talk about setting up a local instance of Dynam DB.

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NoSQL Databases

NoSQL databases are used to solve challenges faces by RDMS (Relational Database Management System), or simply put Relational Databases. Some cons of an RDMS are listed below

  • A schema has to be defined beforehand
  • The data to be stored has to be structured
  • It is difficult to change tables and relationships

On the other hand, NoSQL databases can handle unstructured data and do not need a schema to be defined.

In this tutorial, we will be working with Amazon Dynamo DB. It is a type of key-value and document database NoSQL database.

Table of Contents

  1. Pre-requisites
  2. Setting up Dynamo DB Locally
  3. Connecting to…


In this tutorial, we will be discussing user-defined functions in SQL Server. More specifically, we will be discussing Scalar functions and Table-Valued functions.

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When writing code, one must aim to follow the DRY Principle (Don’t Repeat Yourself). One way to avoid a repetition of code is to put chunks of code inside functions and invoke them as required.

The concept of functions in SQL is similar to other programming languages like Python. The major difference being the way they are implemented. There are two main types of user-defined functions in SQL based on the data they return:

  1. Scalar functions: These types of functions return a single value, i.e float, int, varchar, DateTime, etc.
  2. Table-Valued functions: These functions return tables.

Table of contents

  • Prerequisites.
  • Creating functions.
  • Using…


Streamlit is an open-source Python library that can build a UI for various purposes, it is not limited to data apps/machine learning. It is easy to learn, and a few lines of code can create a beautiful web app.

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Table of contents

  • Prerequisites
  • Installing required libraries
  • Logistic regression model
  • Streamlit UI
  • Conclusion

Why should you use Streamlit?

Streamlit is a Python library that helps us develop UIs for our models without HTML/CSS/JS. Most models die inside a Jupyter notebook and are not appealing. But, using Streamlit, you can create a clean UI for your model and showcase it to others. Building a UI lets users use your model in a more user-friendly format.

  • You don’t need to deal with HTML/CSS/JSS.
  • It supports markdown.
  • It has many prebuilt widgets available, further reducing the time you spend on building the UI.
  • Builds a responsive UI.
  • Easy to deploy Streamlit…


Data Visualization is the art of representing data in the form of graphs. It is a useful tool for professionals who work with data, i.e., financial analysts, business analysts, data analysts, data scientists, to name a few examples. In this tutorial, we will be working with Seaborn, a Python Library.

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Table of contents

  1. Introduction
  2. Prerequisites
  3. Installing Seaborn
  4. Import Seaborn and Load Dataset
  5. Different Types of Graphs
  6. Visualizing the Pokemon Dataset
  7. Conclusion

Introduction

Seaborn is an open-source Python library built on top of matplotlib. It is used for data visualization and exploratory data analysis. Seaborn works easily with dataframes and the Pandas library. The graphs created can also be customized easily. Below are a few benefits of Data Visualization.

Graphs can help us find data trends that are useful in any machine learning or forecasting project.

  • Graphs make it easier to explain your data to non-technical people.
  • Visually attractive graphs can make presentations and reports…


I don’t use VS Code

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Introduction

If you write articles on Medium or your personal blog, you probably have a collection of websites/software which help you produce great content. Below is a list of websites/software that I use for my articles

1. PyCharm

Although I love VS Code and would choose it over any other editor for development, copying code from VS Code to Medium is a pain.

  • When you paste your code, it doesn’t automatically create a code block (the gray block)
  • The code doesn’t respect tabs, spaces, or any indentation and format
  • For some weird reason, it adds a line gap after each line.

Below is…


This article also includes ways to display your confusion matrix

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Introduction

Accuracy, Recall, Precision, and F1 Scores are metrics that are used to evaluate the performance of a model. Although the terms might sound complex, their underlying concepts are pretty straightforward. They are based on simple formulae and can be easily calculated.

This article will go over the following wrt to each term

  • Explanation
  • Why it is relevant
  • Formula
  • Calculating it without sklearn
  • Using sklearn to calculate it

At the end of the tutorial, we will go over confusion matrices and how to present them. I have provided the link to the google colab at the end of the article.

Data 📈

Let’s…


We will be building a Streamlit Web App to showcase a word cloud of Trending Google Keywords and Twitter Hashtags in 2020

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The Link to the live app and screenshots of some of the word clouds are at the end of the article

Introduction

We will be getting our data from the following website

The above website stores archives of the trending keywords and hashtags for each day. Beautiful Soup will be used to scrape this website to get the required data. We will be building the following features

  • A 2020 word cloud
  • The ability for the user to select a date and generate a word cloud for that date
  • The ability for the user to change the image mask

Pre-Requisite

  • Basic Familiarity with…


We will be using Streamlit and pytube to build our youtube downloader web app. I will also give a brief overview of the pytube library.

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We will be implementing the following features

  • The ability for the user to give the URL as an input
  • If available, the ability to chose between video with audio/audio download

Setup Virtual Environment

Before we start, we will need to set up and activate a virtual environment

pip install virtualenv /* Install virtual environment */ virtualenv venv /* Create a virtual environment */ 
venv/Scripts/activate /* Activate the virtual environment */

Install Required Libraries

We will need to install the following Libraries

Streamlit

pytube

Rahul Banerjee

Just an average computer engineering student 💻 I mostly write ‘How to’ tutorials related to Python. https://www.linkedin.com/in/rahulbanerjee2699/

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