This project is about collect data from iFood website and explore it.
It was developed with IME Jr. - Junior Enterprise from Maths and Statistics Institute from University of São Paulo - team members.
You can see the project description - in portuguese - here, in my website.
The Web Scraper (Python)
The Web Scraper was developed in Python, using Selenium and pandas.
Was scraped data from +100 restaurants next to me, in a radius of 10km.
The scraped data from iFood website is stored in a .csv file. You can download it if you want. Or scrape some data yourself, with the web scraper above, inputing your data in the program, using your PC location.
These are the first 5 rows of the data frame:
| Restaurante | Nota | Tipo de comida | Distancia | Tempo | Preco do Frete |
|---|---|---|---|---|---|
| Gokei - Carrão | 4.6 | Japonesa | 0.9 | 59-69 min | 0.0 |
| Pikurruchas Tatuapé | 4.7 | Doces & Bolos | 2.3 | 34-44 min | 6.99 |
| Mussa Esfiha - Anália Franco | 4.7 | Árabe | 2.1 | 23-33 min | 7.99 |
| Sassá Sushi - Tatuapé | 4.4 | Japonesa | 3.8 | 41-51 min | 10.49 |
| Meats - Anália Franco | 4.7 | Lanches | 2.6 | 22-32 min | 6.99 |
| ... | ... | ... | ... | ... | ... |
Cleaning Some Data (Python)
As this project was developed with the IME Jr. team, each member scraped its own data. This Jupyter Notebook (.ipynb) is about cleaning and joining 4 different dataframes from the team. The final file is here, (final-ifood-data.csv).
Final EDA (R)
The final Exploratory Data Analysis is hosted on my website - here's the link -, and you can take a look at it. The files are here, in this repo. It was developed in R Markdown, and in Portuguese, once it was developed with other people.
