Image from https://capitalbikeshare.com/

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Welcome to the README of Data Analysis Project: Capital Bikeshare System.

The Dataset 📈

This repository uses the Capital Bikeshare dataset, available here. Weather information are extracted from here. The data for this repository is present within the DATASET folder downloaded from here.

The Devs ✒️

This repository is developed as Final Assignment of Belajar Analisis Data dengan Python module, a part of Data Science learning path of Dicoding awarded by IDCamp 2023.

The Problems 📝

This repository is focusing on these following bulletpoints:

• Trend of bike rides over given years
• Peaks during time - monthly, weekly, hourly (most requested hour of the days)
• Casual riders vs Registered members, customer behaviour on usage of bikeshare
• Contribution of weather condition on bike demands
• Season wise hourly distribution of bike rentals

The Directory 📂

• /assets : contains pictures which are used in this project
• /dashboard: contains the file bikeshare_dashboard.py which stores the functions needed by the dashboard
• /dataset: stores dataset used in this project
• notebook.ipynb: interactive jupyter notebook files to analyze data
• README.md: file that provides information about this GitHub project
• license.txt : file that maintain license of copy right of the dataset owners
• requirements.txt: file that stores information about the libraries used in this project

The Libraries 📚

• numpy library to carry out numerical computation such as sets, arrays, multidimension matrixes, and vectors
• pandas library to undergo data processing, analysing, and manipulation.
• seaborn library to develop statistical data visualization based on matplotlib
• matplotlib library to perform visualization using plotting
• plotly.express library to perform interactive plotting
• streamlit library to develop interactive dashboard

The Execution ▶

notebook.ipynb

1. Clone this Repository by running git clone https://github.com/nickoaryad/IDCamp2023-Capital-Bikeshare.git.
2. Open Windows terminal or power shell.
3. Run pipenv install to install Python virtual environment.
4. Run pipenv shell --fancy to activate the virtual environment.
5. Run pip install -r requirements.txt to install all libraries.
6. Run jupyter-notebook from shell open Jupyter Notebook.
7. Select notebook.ipynb.
8. Connect to hosted runtime.
9. Run the code cells.

/dashboard/dashboard.py

1. Clone this repository by running git clone https://github.com/nickoaryad/IDCamp2023-Capital-Bikeshare.git.
2. Open Windows terminal or power shell.
3. Run pip install streamlit to install Streamlit.
4. Run pipenv install to install Python virtual environment.
5. Run pipenv shell --fancy to activate the virtual environment.
6. Run pip install -r requirements.txt to install all libraries.
7. Run streamlit run dashboard.py to execute the dashboard Python file.

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Click to open dashboard application in Streamlit ➜

Copyright © Nicko Arya Dharma 2023 All Rights Reserved