Python

EDA - Exploratory Data Analysis: Using Python Functions — step-by-step Python tutorial on Progressive Robot

EDA – Exploratory Data Analysis: Using Python Functions

In the previous articles, we have seen how to perform EDA using graphical methods. In this article, we will be focusing on Python functions used for [Exploratory Data Analysis](/community/tutorials/autoviz-module-in-python) in Python. As we all know, how important EDA is it provides a brief understanding of the data. So, without wasting much time, let's roll! Exploratory Data Analysis […]

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How To Use Templates in a Flask Application — step-by-step Python tutorial on Progressive Robot

How To Use Templates in a Flask Application

Jinja is the templating language that Flask uses to render HTML templates. Using templates allows you to separate the business logic of your application from the presentation logic. These templates provide many features that are not available in standard HTML, such as variables, if statements, for loops, filters, and template inheritance. This helps with maintenance of HTML pages, and prevents Cross-Site Scripting attacks.

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How To Harden the Security of Your Production Django Project — step-by-step Python tutorial on Progressive Robot

How To Harden the Security of Your Production Django Project

Developing a Django application can be a quick and clean experience, because its approach is flexible and scalable. Django also offers a variety of security-oriented settings that can help you seamlessly prepare your project for production. In this tutorial, you will leverage a security-oriented workflow for your Django development by implementing and configuring environment-based settings, dotENV, and Django’s built-in security settings.

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How To Perform Sentiment Analysis in Python 3 Using the Natural Language Toolkit (NLTK) — step-by-step Python tutorial on Progressive Robot

How To Perform Sentiment Analysis in Python 3 Using the Natural Language Toolkit (NLTK)

The process of analyzing natural language and making sense out of it falls under the field of Natural Language Processing (NLP). In this tutorial, you will prepare a dataset of sample tweets from the NLTK package for NLP with different data cleaning methods. You will also train a model on pre-classified tweets and use the model to classify them into negative and positives sentiments.

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