Data Project README file

The README file describes the essence of the project playing the most important role. Most visitors will simply scroll down about twice on the README and leave if they are not interested. So, the README file should provide the reason why to checkout your project!!!). Bearing that in mind, your job is to:

• Tell them what it is (with context).
• Show them what it looks like in action.
• Show them how they use it.
• Tell them any other relevant details.

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Formatting

Your readers will most likely view your README in a browser so please keep that in mind when formatting its content:

• Use proper format when necesary (e.g.: import pandas as pd).
• Categorize content using two or three levels of header beneath.
• Make use of emphasis to call out important words.
• Link to project pages for related libraries you mention. Link to Wikipedia, Wiktionary, even Urban Dictionary definitions for words of which a reader may not be familiar. Make amusing cultural references.
• Add links to related projects or services.

Here you have a markdown cheatsheet Link and tutorial Link.

Start writing ASAP:

Last but not least, by writing your README soon you give yourself some pretty significant advantages. Most importantly, you’re giving yourself a chance to think through the project without the overhead of having to change code every time you change your mind about how something should be organized or what should be included.

Suggested Structure:

🙋 Name

Self-explanatory names are best. If the name sounds too vague or unrelated, it may be a signal to move on. It also must be catchy. Images, Logo, Gif or some color is strongly recommended.

👶 Status

Alpha, Beta, 1.1, Ironhack Data Analytics Final Project, etc... It's OK to write a sentence, too. The goal is to let interested people know where this project is at.

🏃 One-liner

Having a one-liner that describes the pipeline/api/app is useful for getting an idea of what your code does in slightly greater detail.

💻 Technology stack

Python, Pandas, Scipy, Scikit-learn, etc. Indicate the technological nature of the software, including primary programming language(s), main libraries and whether the software is intended as standalone or as a module in a framework or other ecosystem.

💥 Core technical concepts and inspiration

Why does it exist? Frame your project for the potential user. Compare/contrast your project with other, similar projects so the user knows how it is different from those projects. Highlight the technical concepts that your project demonstrates or supports. Keep it very brief.

🔧 Configuration

Requeriments, prerequisites, dependencies, installation instructions.

🙈 Usage

Parameters, return values, known issues, thrown errors.

📁 Folder structure

└── project
    ├── __trash__
    ├── .gitignore
    ├── .env
    ├── requeriments.txt
    ├── README.md
    ├── main_script.py
    ├── notebooks
    │   ├── notebook1.ipynb
    │   └── notebook2.ipynb
    ├── package1
    │   ├── module1.py
    │   └── module2.py
    └── data
        ├── raw
        ├── processed
        └── results

Do not forget to include __trash__ and .env in .gitignore

💩 ToDo

Next steps, features planned, known bugs (shortlist).

ℹ️ Further info

Credits, alternatives, references, license.

💌 Contact info

Getting help, getting involved, hire me please.

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Here you have some repo examples:

• Spotify Recommender

• Political Spanish Sentiment

• Face-Mask Detection

• Data Town

• Show us your Panerai Watch!

• Onegy

• Yummest

• Math handwritting recognition

• HackDecó

• E-VITALOS

• Movie Founder

• MMELT

• Mamba (OCR-Translator-Assistant)

• Art Classification

Here you have some tools and references:

• Make a README
• Awesome README
• Markdown Cheatsheet