Bike Rentals - Final Project Data Analytics

This is a final project from Dicoding in the "Belajar Analisis Data Dengan Python" course to make analysis and create a dashboard from the bike sharing dataset. In the notebook file, I attached the way I did the analysis from Data Wrangling, Exploratory Data Analysis, and Data Visualization. Besides that, I also make the dashboard using streamlit, and you can check it by clicking on the link in the right sidebar or in here.

For further information, like the background of this dataset, dataset characteristics, file structures, and more, you can check out the Readme file. So in here, I won't explain it any further.

1. File Structures

.
├── dashboard
│   ├── dashboard.py
│   └── day.csv
├── data
│   ├── Readme.txt
│   ├── day.csv
|   └── hour.csv
├── screenshots
|   ├── Screenshots (91).png
|   ├── Screenshots (92).png
|   ├── Screenshots (93).png
|   └── Screenshots (94).png
├── README.md
├── notebook.ipynb
└── requirements.txt

2. Project work cycle

1. Data Wrangling:

• Gathering data
• Assessing data
• Cleaning data

2. Exploratory Data Analysis:

• Defined business questions for data exploration
• Create Data exploration

3. Data Visualization:

• Create Data Visualization that answer business questions

4. Dashboard:

• Set up the DataFrame which will be used
• Make filter components on the dashboard
• Complete the dashboard with various data visualizations

Note: Numbers 1 to 3 are in the dicoding-collection-exercise and number 4 is in dashboard.

3. Getting Started

notebook.ipynb

1. Download this project.
2. Open your favorite IDE like Jupyter Notebook or Google Colaboratory (but in here I will use Google Colab).
3. Create a New Notebook.
4. Upload and select the file with .ipynb extension.
5. Connect to hosted runtime.
6. Lastly, run the code cells.

dashboard/dashboard.py

1. Download this project.
2. Install the Streamlit in your terminal or command prompt using pip install streamlit. Install another libraries like pandas, numpy, scipy, matplotlib, and seaborn if you haven't.
3. Please note, don't move the csv file because it acts a data source. keep it in one folder as dashboard.py
4. Open your VSCode and run the file by clicking the terminal and write it streamlit run dashboard.py.

4. Screenshots