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Identified and investigated fluctuations and patterns of tube temperatures on the London Underground network over an eight-year period, focusing on examining the various factors that influence tube temperatures and how they affect the overall temperature trends.

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Exploring temperatures on the London Underground 🚇

This project is a data visualization of transportation average temperature data from Transport for London (TfL). The data includes data of the tube temperatures from 2013 to 2020 on the London Underground. This data was provided by TfL and is available through this link. This data has been used in accordance with the UK Open Government License.

You can view this project on Streamlit

Prerequisites

You will need to have Python 3 and the following libraries installed:

  • Pandas - Data manipulation library
  • Matplotlib - Data visualization library
  • Seaborn - Data visualization library
  • Plotly - Interactive data visualization library

You can install these libraries using pip:

pip install -r requirements

Running the code

The code for the data analysis & visualization is in the 'TFL Temperature.ipynb' Jupyter Notebook file. You can run the code by opening the notebook and running the cells.

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Identified and investigated fluctuations and patterns of tube temperatures on the London Underground network over an eight-year period, focusing on examining the various factors that influence tube temperatures and how they affect the overall temperature trends.

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