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# Project Tour | ||
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* notes: | ||
* > Discuss about your project file structure | ||
* > what each folder is responsible | ||
* > then go through each file in folders and explain there purpose | ||
* > if possible create a doc system ( there are autogen docs available for most of the languages ) | ||
* > decide coding style , linting style and formatting style and other themes like variable naming etc. | ||
* > provide an example for existing function and tests system if possible | ||
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# MAKE SURE PROJECT MANAGERS UPDATE THIS MD | ||
## Folder Structure | ||
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* `dataset`: contains the dataset for the project. | ||
* `Accommodating_Insights.ipynb`: contains the main notebook for the project. | ||
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### `dataset` Folder | ||
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* `hotel.csv`: is the dataset for the project. | ||
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## Coding Style | ||
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For Jupyter Notebooks specifically: | ||
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* **Cell Organization:** Group related code together in cells and use markdown cells to explain the logic and flow of your notebook. | ||
* **Comments and Docstrings:** Write clear comments and docstrings for functions and classes to document their purpose and usage. | ||
<!-- * **Version Control:** Use tools like `nbdime` to simplify version control for notebooks. --> | ||
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## Tech Stack | ||
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* **Language:** Python | ||
* **Libraries:** Pandas, NumPy, Scikit-learn, Matplotlib, Scipy, Seaborn, etc. | ||
* **Tools:** Jupyter Notebook, Git, GitHub, etc. |
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# template | ||
A Template Repository for OpenSpringFest (OSF) | ||
# Accommodating Insights: A Data Exploration of the Transient Landscape | ||
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This project delves into a rich dataset containing information about short-term rentals in a geographic location. By analyzing this data, we aim to uncover insights and trends within the rental market. |
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