https://github.com/audevuilli/guardian_recipes
This repository provides the code to code to analyse data from The Guardian newspaper using data science techniques. Read more about the analysis on Medium: https://tinyurl.com/2ekse7ct
https://github.com/audevuilli/guardian_recipes
data-science machine-learning nlp
Last synced: about 1 year ago
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This repository provides the code to code to analyse data from The Guardian newspaper using data science techniques. Read more about the analysis on Medium: https://tinyurl.com/2ekse7ct
- Host: GitHub
- URL: https://github.com/audevuilli/guardian_recipes
- Owner: audevuilli
- Created: 2019-06-01T15:18:22.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2021-11-20T11:16:58.000Z (over 4 years ago)
- Last Synced: 2025-06-18T10:53:38.723Z (about 1 year ago)
- Topics: data-science, machine-learning, nlp
- Language: Jupyter Notebook
- Homepage:
- Size: 129 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# The Guardian Recipes Analysis
## Overview
This GitHub repository contains the iPython files for the analysis of more than 7,000 recipe articles (between 2009 and 2019) webscraped from The Guardian website. You can view the most recent published recipes over [here](https://www.theguardian.com/tone/recipes)
The analysis of this incredible large food recipes dataset is summarised in two blogposts published on [Towards Data Science on Medium](https://towardsdatascience.com/).
- [**Part 1: Exploratoray Data Analysis**](https://towardsdatascience.com/analyzing-the-guardian-food-recipes-from-2009-to-2019-11b83e12efdf) give an overview of the most popular chefs and categories of recipes for each of the year.
- [**Part 2: Topic Modeling**](https://towardsdatascience.com/the-guardian-recipes-part-2-lda-topic-modeling-51e5b13faefa) Explore the use of Natural Language Processing, the use of machine learning algorithms to analyse and retrieve information form textual data.
Hope you will enjoy reading the articles as well as dive into the code to learn more about EDA and NLP techniques.